Robotic-assisted Rehabilitation of the Extremities

Number: 0778

Table Of Contents

Applicable CPT / HCPCS / ICD-10 Codes


Aetna considers robotic-assisted rehabilitation of the upper limb and lower limb experimental and investigational for the following indications (not an all-inclusive list) because of insufficient evidence of its effectiveness.

  • Humeral fracture
  • Incomplete spinal cord injury
  • Neuromuscular diseases (e.g., cerebral palsy, multiple sclerosis, and Parkinson disease)
  • Stroke
  • Traumatic brain injury

Aetna considers the Intrepid Dynamic Exoskeletal Orthosis (IDEO), the Myomo e100 robotic arm brace, and the Myomo MyoPro myoelectric limb orthosis experimental and investigational for medical purposes because their effectiveness has not been established.  The Myomo MyoPro myoelectric limb orthosis are considered exercise equipment by the FDA.  Note: Aetna considers the Myomo MyoPro myoelectric limb orthosis (and similar devices) as exercise equipment.  Most Aetna benefit plans exclude coverage of exercise equipment.

Aetna considers powered hip orthoses for persons with spinal cord injury experimental and investigational because their effectiveness has not been established.

Related Policies


CPT Codes / HCPCS Codes / ICD-10 Codes

Code Code Description

Information in the [brackets] below has been added for clarification purposes.   Codes requiring a 7th character are represented by "+":

Robotic-assisted Rehabilitation - no specific code:

HCPCS codes not covered for indications listed in the CPB:

Intrepid Dynamic Exoskeletal Orthosis (IDEO), powered hip orthoses, Myomo e100 robotic arm brace, Myomo MyoPro myoelectric limb orthosis - no specific code:

L8701 Powered upper extremity range of motion assist device, elbow, wrist, hand with single or double upright(s), includes microprocessor, sensors, all components and accessories, custom fabricated
L8702 Powered upper extremity range of motion assist device, elbow, wrist, hand, finger, single or double upright(s), includes microprocessor, sensors, all components and accessories, custom fabricated

ICD-10 codes not covered for indications listed in the CPB (not all-inclusive):

G20 - G21.9 Parkinson's disease
G35 Multiple sclerosis
G70.00 - G70.9
G73.1 - G73.3
Myasthenia gravis and other myoneural disorders
G80.0 - G80.2
G80.4 - G80.9
Cerebral Palsy
I69.031 - I69.069
I69.131 - I69.169
I69.231 - I69.269
I69.331 - I69.369
I69.831 - I69.869
I69.931 - I69.969
Sequelae of cerebrovascular disease, monoplegia, hemiplegia and hemiparesis, and other paralytic syndrome
I69.090 - I69.098
I69.190 - I69.198
I69.290 - I69.298
I69.390 - I69.398
I69.890 - I69.898
I69.990 - I69.998
Other sequelae of cerebrovascular disease
I69.093, I69.193, I69.293
I69.393, I69.893, I69.993
Sequelae of cerebrovascular disease, ataxia
S06.0X0A - S06.A1XS Traumatic brain injury
S14.101+ - S14.149, S14.151+ - S14.159+, S24.101+ - S24.119, S24.131+ - S24.149+, S24.151+ - S24.159+, S34.101+ - S34.119+, S34.121+ - S34.129+, S34.131+, S34.132, S34.139+ Incomplete lesion of spinal cord
S42.201A - S42.296S Fracture of upper end of humerus


According to the American Heart Association, stroke is a major cause of long-term disability in the United States.  Over 50 % of patients with upper limb paresis resulting from stroke face long-term impaired arm function and ensuing disability in daily life (Verbunt et al, 2008).  Reducing the degree of permanent disability is the goal of post-stroke neurorehabilitation programs.  Therapy that incorporates active assistance of motor tasks is a common technique in upper extremity rehabilitation after stroke.  It has been proposed that this type of therapy may be facilitated by robotic devices.  Exoskeletal or "wearable" robots are intended to provide therapeutic exercise or to function as powered orthoses to help compensate for chronic weakness. 

Myoelectric orthotic devices are intended for use in persons with upper limb deficiencies. According to the manufacturers of these devices, they enable individuals who have been afflicted by a stroke or other neuromuscular conditions to self-initiate movement of a partially paralyzed arm using their own muscle signals. They explain that, when the user tries to bend the affected limb, sensors in the brace detect the muscle signal, which activates the motor to move the arm in the desired direction. Examples of this brace include, but may not be limited to, the MyoPro myoelectric limb orthosis and the Myomo e100.

In a randomized controlled pilot study, Kahn and associates (2006a) investigated the effects of robotically administered active-assistive exercise compared to free reaching voluntary exercise in improving arm movement ability after chronic stroke.  A total of 19 individuals at least 1 year post-stroke were randomized into 1 of 2 groups.  One group performed 24 sessions of active-assistive reaching exercise with a simple robotic device, while a 2nd group performed a task-matched amount of un-assisted reaching.  The main outcome measures were range and speed of supported arm movement, range, straightness and smoothness of un-supported reaching, and the Rancho Los Amigos Functional Test of Upper Extremity Function.  There were significant improvements with training for range of motion (ROM) and velocity of supported reaching, straightness of un-supported reaching, and functional movement ability.  These improvements were not significantly different between the 2 groups.  The group that performed un-assisted reaching exercise improved the smoothness of their reaching movements more than the robot-assisted group.  The authors concluded that improvements with both forms of exercise confirmed that repeated, task-related voluntary activation of the damaged motor system is a key stimulus to motor recovery following stroke and that robotically assisting in reaching improved arm movement ability, although it did not provide any detectable, additional value beyond the movement practice that occurred concurrently with it.  The authors stated that the inability to detect any additional value of robot-assisted reaching may have been due to the limited sample size of the study and the specific diagnoses of the participants, or the inclusion of only individuals with chronic stroke.

The Myomo e100 robotic arm brace (Myomo, Inc., Boston, MA) is an electromechanically powered elbow brace that received 510(k) marketing clearance in April 2007.  It is intended to facilitate arm movement and maintain or increase ROM of the arm for stroke patients undergoing rehabilitation.  The device contains a computerized system that detects changes in the patient's resting muscle potential through electromyographic (EMG) sensors placed on the skin.  The computerized system translates these electrical signals into the desired motion and then responds in real time with a power boost from the device's motorized elbow brace to assist the desired motion.  The device would be included as part of prescribed physical therapy to enable stroke patients to exercise that would otherwise be unable to independently do so.  The amount of assistance provided by the Myomo e100 can vary as the patient fatigues or gains strength.  The objective of the EMG-triggered action is to engage and reinforce both neurological and motor pathways to help the patient relearn how to move affected muscles.  The Myomo e100 can be configured for either the left or right arm, and to detect electrical activity from either the biceps or triceps.  Unlike some earlier robotic therapy devices that were stationary, the Myomo e100 is a wearable device.  It is designed to act as an aid for exercise training and may be developed for use as an actively powered orthosis to assist with difficult motions.

Stein et al (2007) reported the results of the Myomo e100 device on 6 stroke patients with severe chronic hemiparesis.  Each patient used the device for a total of 18 hours of exercise therapy (2 to 3 hours per week) for a period of 6 weeks.  The average age of the patients was 53 years, and the average time since their stroke was 3.67 years.  A 7th patient did not have sufficient EMG signals to control the device.  Patients performed exercises including a defined set of functional tasks (moving blocks or turning light switches on or off) with the robotic brace.  They were able to control the motorized brace to assist in these motions.  Assessment by both the Fugl-Meyer scale and the modified Ashworth scale (a measure of muscle spasticity) showed improvement in upper extremity motor function.  The authors concluded that the EMG-controlled powered elbow orthoses show promise as a new modality for assisted exercise training after stroke.  They stated that further studies are needed to confirm these preliminary results.

Chang et al (2007) analyzed the results of a training program (40 mins/session, 3 sessions/week for 8 weeks) consisting of 10 mins of conventional rehabilitation and 30 mins of robot-aided, bilateral force-induced, isokinetic arm movement training to improve paretic upper-limb motor function.  The post-test and retention test in arm motor function significantly improved in terms of grip (p = 0.009), push (p = 0.001), and pull (p = 0.001) strengths, and Fugl-Meyer Assessment upper-limb scale (p < 0.001).  Reaching kinematics significantly improved in terms of movement time (p = 0.015), peak velocity (p = 0.035), percentage of time to peak velocity (p = 0.004), and normalized jerk score (p = 0.008).  Improvement in reaching ability was not sustained in the retention test.  The authors concluded that these preliminary results showed that conventional rehabilitation combined with robot-aided, bilateral force-induced, isokinetic arm training might enhance the recovery of strength and motor control ability in the paretic upper limb of patients with chronic stroke.

Kwakkel et al (2008) conducted a systematic review on the effects of robot-assisted therapy on motor and functional recovery of the upper limb in stroke patients.  Randomized clinical trials published up to October 2006 that satisfied the following selection criteria were included:
  1. patients diagnosed with cerebral vascular accident,
  2. effects of robot-assisted therapy for the upper limb, and
  3. outcomes reported in terms of motor and/or functional recovery of the upper paretic limb. 
For each outcome measure, the estimated effect size (ES) and the summary effect size (SES) expressed in standard deviation units (SDU) were calculated for motor recovery and functional ability (activities of daily living [ADLs]) using fixed and random effect models.  Ten studies, involving 218 patients, were included in the synthesis.  Their methodological quality ranged from 4 to 8 on a (maximum) 10-point scale.  Meta-analysis showed a non-significant heterogeneous SES in terms of upper limb motor recovery.  Sensitivity analysis of studies involving only shoulder-elbow robotics subsequently demonstrated a significant homogeneous SES for motor recovery of the upper paretic limb.  No significant SES was observed for functional ability (ADL).  The authors reported that as a result of marked heterogeneity in studies between distal and proximal arm robotics, no overall significant effect in favor of robot-assisted therapy was found.  However, subsequent sensitivity analysis showed a significant improvement in upper limb motor function after stroke for upper arm robotics.  No significant improvement was found in ADL function.  However, the administered ADL scales in the reviewed studies failed to adequately reflect recovery of the paretic upper limb, whereas valid instruments that measured outcome of dexterity of the paretic arm and hand were mostly absent in the selected studies.  The authors concluded that future research into the effects of robot-assisted therapy should therefore distinguish between upper and lower robotics arm training and concentrate on kinematical analysis to differentiate between genuine upper limb motor recovery and functional recovery due to compensation strategies by proximal control of the trunk and upper limb.  An evaluation of this systematic evidence review by the Center for Reviews and Dissemination (2009) stated that the conclusions of this systematic review "should be treated with caution in view of the uncertain clinical and statistical significance of the results and the small sizes of the included trials" and that the authors suggestions for further research seemed appropriate. 

A Cochrane systematic review (Mehrholz et al, 2008) evaluated the evidence of the effectiveness of electromechanical and robot-assisted training for improving arm function after stroke.  Randomized controlled trials comparing electromechanical and robot-assisted arm training for recovery of arm function with other rehabilitation interventions or no treatment for patients after stroke were selected for review.  Eleven trials (328 participants) met the inclusion criteria.  The authors reported that electromechanical and robot-assisted arm training did not improve ADLs but arm motor function and arm motor strength improved.  These results must be interpreted with caution, however, because there were variations between the trials in the duration, amount of training and type of treatment, and in the patient characteristics.  The authors concluded, "It is, therefore, not clear if such devices should be applied in routine rehabilitation, or when and how often they should be used."  A Cochrane systematic evidence review also found that there is insufficient evidence for the use of robotic-assisted gait training after spinal cord injury (SCI) (Mehrholz et al, 2008).  Two review authors independently selected trials for inclusion, assessed trial quality and extracted the data.  The primary outcomes were the speed of walking and walking capacity at follow-up.  A total of 4 randomized controlled trials (RCTs) involving 222 patients were included in this review.  Overall, the results were inconclusive.  There was no statistically significant effect of locomotor training on walking function after SCI comparing body-weight supported treadmill training with or without functional electrical stimulation or robotic-assisted locomotor training.  The authors concluded that there is insufficient evidence from RCTs to conclude that any one locomotor training strategy improves walking function more than another for people with SCI.  Research in the form of large RCTs is needed to address specific questions about the type of locomotor training which might be most effective in improving walking function of people with SCI.

In a RCT, Hornby et al (2008) examined the effects of robotic-assisted versus therapist-assisted locomotor training (LT).  Both groups received 12 LT sessions for 30 mins at similar speeds, with guided symmetrical locomotor assistance using a robotic orthosis versus manual facilitation from a single therapist using an assist-as-needed paradigm.  Outcome measures included gait speed and symmetry, and clinical measures of activity and participation.  Greater improvements in speed and single limb stance time on the impaired leg were observed in subjects who received therapist-assisted LT, with larger speed improvements in those with less severe gait deficits.  Perceived rating of the effects of physical limitations on quality of life improved only in subjects with severe gait deficits who received therapist-assisted LT.  The authors concluded that therapist-assisted LT facilitates greater improvements in walking ability in ambulatory stroke survivors as compared to a similar dosage of robotic-assisted LT.

In a multi-center, randomized clinical trial, Hilder and colleagues (2009) compared the effectiveness of robotic-assisted gait training with the Lokomat to conventional gait training in individuals with subacute stroke.  A total of 63 participants less than 6 months post-stroke with an initial walking speed between 0.1 to 0.6 m/s completed the study.  All participants received 24 1-hr sessions of either Lokomat or conventional gait training.  Outcome measures were evaluated prior to training, after 12 and 24 sessions, and at a 3-month follow-up examination.  Self-selected overground walking speed and distance walked in 6 mins were the primary outcome measures, whereas secondary outcome measures included balance, mobility and function, cadence and symmetry, level of disability, and quality of life measures.  Participants who received conventional gait training experienced significantly greater gains in walking speed (p = 0.002) and distance (p = 0.03) than those trained on the Lokomat.  These differences were maintained at the 3-month follow-up evaluation.  Secondary measures were not different between the 2 groups, although a 2-fold greater improvement in cadence was observed in the conventional versus Lokomat group.  The authors concluded that for subacute stroke patients with moderate-to-severe gait impairments, the diversity of conventional gait training interventions appears to be more effective than robotic-assisted gait training for facilitating returns in walking ability.

In a randomized clinical trial, Lewek et al (2009) determined whether LT with physical assistance as needed was superior to guided, symmetrical, robotic-assisted LT for improving kinematic coordination during walking post-stroke.  A total of 19 people with chronic stroke (greater than 6 months' duration) participating in a RCT comparing therapist-assisted versus robotic-assisted LT were recruited.  Prior to and following 4 weeks of LT, gait analysis was performed at each participant's self-selected speed during overground walking.  Kinematic coordination was defined as the consistency of intra-limb hip and knee angular trajectories over repeated gait cycles and was compared before and after treatment for each group.  Locomotor training with therapist assistance resulted in significant improvements in the consistency of intra-limb movements of the impaired limb.  Providing consistent kinematic assistance during robotic-assisted LT did not result in improvements in intra-limb consistency.  Only minimal changes in discrete kinematics were observed in either group.  The authors concluded that coordination of intra-limb kinematics appears to improve in response to LT with therapist assistance as needed.  Fixed assistance, as provided by this form of robotic guidance during LT, however, did not alter intra-limb coordination.

In a non-blinded prospective RCT, Schwartz and co-workers (2009) assessed the effectiveness of early and prolonged LT with the use of a robotic-assisted gait training (RAGT) device (Lokomat; Hocoma Inc., Zurich, Switzerland) on the functional outcomes of patients after subacute stroke.  A total of 67 patients in the first 3 months after subacute stroke were randomized into 2 groups as follows:
  1.  37 patients were treated with RAGT, and
  2. 30 were treated with regular physiotherapy. 
Inclusion criteria were first stroke, independent ambulation before the stroke, and neurological severity between 6 and 20 according to the National Institutes of Health Stroke Scale (NIHSS).  RAGT treatment was administered 3 times a week for 30 mins, combined with regular physiotherapy for 6 weeks.  Control patients received the equivalent additional time of regular physiotherapy.  The primary outcome was the ability to walk independently, as assessed by use of the functional ambulatory capacity scale.  The secondary outcomes included the neurological status according to the NIHSS; functional motor assessment (determined by use of the stroke activity scale); and gait parameters, including gait velocity, endurance, and number of climbed stairs.  In the intention-to-treat analysis, subjects in the RAGT group exhibited greater gains than the control group in their ability to walk independently, as expressed by a greater functional ambulatory capacity score (p < 0.01), and in their neurological status according to NIHSS (p < 0.01).  Among those who achieved independent walking, non-significant differences between groups were noted according to secondary outcome measures of gait parameters except from step climbing.  The authors concluded that this controlled study showed, at the end of a 6-week trial, that LT with the use of RAGT combined with regular physiotherapy produced promising effects on functional and motor outcomes in patients after subacute stroke as compared with regular physiotherapy alone.

In a preliminary study, Kutner et al (2010) examined changes in patient-reported, health-related quality of life associated with robotic-assisted therapy combined with reduced therapist-supervised training in patients with subacute stroke.  A total of 17 individuals who were 3 to 9 months post-stroke participated in this study.  Sixty hours of therapist-supervised repetitive task practice (RTP) was compared with 30 hours of RTP combined with 30 hours of robotic-assisted therapy.  Participants completed the Stroke Impact Scale (SIS) at baseline, immediately post-intervention, and 2 months post-intervention.  Change in SIS score domains was assessed in a mixed model analysis.  The combined therapy group had a greater increase in rating of mood from pre-intervention to post-intervention, and the RTP-only group had a greater increase in rating of social participation from pre-intervention to follow-up.  Both groups had statistically significant improvement in activities of daily living and instrumental activities of daily living scores from pre-intervention to post-intervention.  Both groups reported significant improvement in hand function post-intervention and at follow-up, and the magnitude of these changes suggested clinical significance.  The combined therapy group had significant improvements in stroke recovery rating post-intervention and at follow-up, which appeared clinically significant; this also was true for stroke recovery rating from pre-intervention to follow-up in the RTP-only group.   The major limitation of this study was that outcome of 30 hours of RTP in the absence of robotic-assisted therapy remain unknown.  The authors concluded that robotic-assisted therapy may be an effective alternative or adjunct to the delivery of intensive task practice interventions to enhance hand function recovery in patients with stroke.  These prelininary findings need to be validated by further investigation.

In a case-series study, Meyer-Heim and colleagues (2009) measured functional gait improvements of robotic-assisted locomotion training in children with cerebral palsy (CP).  A total of 22 children (mean age of 8.6 years, range of 4.6 to 11.7) with CP and a gross motor function classification system level II to IV were enrolled in this study.  Subjects received 3 to 5 sessions of 45 to 60 mins/week during a 3- to 5-week period of driven gait orthosis training.  Main outcome measures included 10-meter walk test (10MWT), 6-min walk test (6MinWT), gross motor function measure (GMFM-66) dimension D (standing) and dimension E (walking), and functional ambulation categories (FAC).  The mean (SD) maximum gait speed (0.78 (0.57) to 0.91 (0.61) m/s; p < 0.01) as well as the mean (SD) dimension D of the GMFM-66 (40.3 % (31.3 %) to 46.6 % (28.7 %); p < 0.05) improved significantly after the intervention period.  The mean (SD) 6MinWT (176.3 (141.8) to 199.5 (157.7) m), the mean FAC (2.6 (1.7) to 3.0 (1.6)) and the mean (SD) dimension E of the GMFM-66 (29.5 % (30.3 %) to 31.6 % (29.2 %)) also showed an increase, but did not reach a statistically significant level.  These authors concluded that these findings suggested that children with CP benefit from robotic-assisted gait training in improving functional gait parameters.  These findings need to be validated by well-deisgned studies.

In a RCT, Druzbicki et al (2013) evaluated gait in children with spastic diplegic CP (n = 52) rehabilitated with the use of Lokomat active orthosis.  Temporo-spatial parameters of gait and selected kinematic parameters were assessed.  Childrem from the study group used active orthosis in addition to following a program of individual exercises.  Children in the control group participated only in individual exercises.  The difference between the initial and control examinations was statistically insignificant.  After the program was finished, there was a slight improvement in walking speed in both groups.  Improvement in the mean walking speed was not significantly different between the groups (p = 0.5905).  Range of motion decreased slightly in both groups, and the difference between mean amounts of change was not significant (p = 0.8676).  There was significant improvement in maximal range of flexion in the hip joint (p = 0.0065) in the study.  It was shown that with a decrease in the mean value of adduction in hip joint, the mean walking speed increased (r = -0.53, p = 0.0011).  The authors concluded that this study had several limitations, thus, these results should be regarded as preliminary.  Moreover, they stated that further research consistent with the above indications is needed to investigate the impact of this new treatment option in patients with CP.

In a systematic review, Hayward et al (2010) examined the effect of interventions that promote upper limb (UL) recovery in stroke survivors with severe paresis.  A systematic search of the scientific literature from January 1970 to March 2009 was conducted using CINAHL, Cochrane, PEDro, Pubmed and Web of Science.  Keywords used included stroke, severe, hemiplegia, upper limb, task-oriented, robot, non-robot and electrical stimulation.  Methodological quality of the studies was assessed using the PEDro rating scale.  Studies were grouped into 1 of 3 intervention categories:
  1. robotic therapy,
  2. electrical stimulation or
  3. "other" therapy. 
A total of 17 RCTs met the inclusion criteria.  A "best evidence synthesis" indicated strong evidence that robotic therapy provides a large beneficial effect and limited evidence that electrical stimulation and "other" interventions provide a large beneficial effect on function.  There is no evidence that these interventions influence use of the arm in everyday tasks.  The authors concluded that there are a number of newly developed interventions that enable stroke survivors with severe paresis to actively participate in task-oriented practice to promote UL recovery.  While these interventions offer some promise for stroke survivors with severe paresis, ultimately, the effectiveness of these interventions will be based on whether they lead to restoration of function to the point at which the stroke survivor can practice everyday tasks.

Swinnen et al (2010) evaluated the quality of current evidence as to the effectiveness of RAGT in patients with SCI, focusing on walking ability and performance.  A search was conducted in MEDLINE, Web of Knowledge, Cochrane Library, Physiotherapy Evidence Database (PEDro) and Digital Academic Repositories (DAREnet) (1990 to 2009).  Key words included "spinal cord injury", "(robot-assisted) gait rehabilitation" and "driven gait orthosis".  Articles were included when complete and incomplete adult spinal cord injured patients participated in RAGT intervention studies.  The methodological quality was rated independently by 2 researchers using "van Tulder criteria list" and "evaluation of quality of an intervention study".  Descriptive analyses were performed using the Population Intervention Comparison Outcome (PICO) method.  Two RCTs (mean quality score: 11.5/19) and 4 pre-experimental trials (mean quality score: 24.25 (standard deviation; SD 0.28/48) involving 43 patients with incomplete, acute or chronic lesions between C3 and L1 were analysed.  Five studies used the Lokomat and 1 used the LokoHelp.  Although some improvements were reported related to body functions and activities, there is insufficient evidence to draw firm conclusions, due to small samples sizes, methodological flaws and heterogeneity of training procedures.  The authors concluded that there is currently no evidence that RAGT improves walking function more than other locomotor training strategies.  They stated that well-designed RCTs are needed.

The Veterans Health Administration and the Department of Defense's clinical practice guideline for the management of stroke rehabilitation (2010) stated that "[t]here is no sufficient evidence supporting use of robotic devices during gait training in patients post stroke" (regarding gait training strategies for lower extremities).

In a pilot study, Zariffa et al (2012) examined the use of an upper limb robotic rehabilitation device (Armeo Spring, Hocoma AG, Switzerland) in a subacute cervical SCI population.  A total of 12 subjects (motor level C4 to C6, ASIA Impairment Scale A-D) completed the training, which consisted of 16.1 +/- 4.6 sessions over 5.2 +/- 1.4 weeks.  Two types of outcomes were recorded:
  1. feasibility of incorporating the device into an inpatient rehabilitation program (compliance with training schedule, reduction in therapist time required and subject questionnaires) and
  2. efficacy of the robotic rehabilitation for improving functional outcomes (Graded and Redefined Assessment of Strength, Sensibility and Prehension (GRASSP), action research arm test, grip dynamometry and range of motion).
By the end of the training period, the robot-assisted training was shown to require active therapist involvement for 25 +/- 11 % (mean +/- S.D.) of the total session time.  In the group of all subjects and in a subgroup composed of motor-incomplete subjects, no statistically significant differences were found between intervention and control limbs for any of the outcome measures.  In a subgroup of subjects with partial hand function at baseline, the GRASSP-Sensibility component showed a statistically significant increase (6.0 +/- 1.6 (mean +/- S.E.M.) point increase between baseline and discharge for the intervention limbs versus 1.9 +/- 0.9 points for the control limbs).  The authors concluded that these findings suggested that individuals with some preserved hand function after SCI may be better candidates for rehabilitation training using the Armeo Spring device.

Schwartz et al (2011) evaluated the effect of an additive RAGT using the Lokomat system on the neurological and functional outcomes of patients with subacute SCI.  A total of 28 subacute SCI patients were treated by RAGT, 2 to 3 times a week, 30 to 45 mins every treatment, concomitantly with regular physiotherapy.  As control, for each patient, these investigators matched a comparable patient treated in the same department in previous years, according to age, severity of injury, level of injury and cause.  The main outcomes were: the AIS (American Spinal Injury Association impairment scale) the spinal cord independence measurement (SCIM) score, the walking index for SCI II (WISCI II) and functional ambulation category scale (FAC).  At the end of rehabilitation, both groups showed a significant improvement in both the FAC score and the WISCI score (p < 0.01) without differences between the groups.  Functional abilities, according to the SCIM score, were also improved, with a significant interaction effect; the RAGT patients improve by 30 +/- 20 points, which was significantly greater gain as compared with the controls, 21 +/- 14 points (p = 0.05).  This improvement was mainly due to the change in the SCIM motor subscales.  The authors concluded that RAGT is an important additional treatment to improve the functional outcome of subacute SCI patients.  They stated that larger, controlled studies are still needed to determine the optimal timing and protocol design for the maximal efficacy of RAGT in SCI patients.

In an open-label pilot study, Stein et al (2011) tested a new robotic device for hand rehabilitation in stroke survivors.  A total of 12 individuals with chronic moderate hemiparesis after stroke were enrolled in this study.  Participants underwent a 6-week training program using a hand robotic device.  They received a total of 18 hours of robotic therapy.  Improvements were found in multiple measures of motor performance, including the Upper Extremity Fugl-Meyer test, the Motor Activity Log, the Manual Ability Measure-36, and the Jebsen Hand Function Test.  All subjects tolerated the treatment well and no complications were observed.  The authors concluded that robotic therapy for hand paresis after stroke is safe and feasible, and further studies of efficacy are justified by these preliminary results.

Norouzi-Gheidari et al (2012) systematically reviewed and analyzed the literature to find RCTs that employed robotic devices in upper-limb rehabilitation of people with stroke.  Out of 574 studies, 12 matching the selection criteria were found.  The Fugl-Meyer, Functional Independence Measure, Motor Power Scale, and Motor Status Scale outcome measures from the selected RCTs were pooled together, and the corresponding effect sizes were estimated.  These researchers found that when the duration/intensity of conventional therapy (CT) was matched with that of the robot-assisted therapy (RT), no difference exists between the intensive CT and RT groups in terms of motor recovery, ADL, strength, and motor control.  However, depending on the stage of recovery, extra sessions of RT in addition to regular CT are more beneficial than regular CT alone in motor recovery of the hemiparetic shoulder and elbow of patients with stroke; gains are similar to those that have been observed in intensive CT.

In a Cochrane review, Mehrholz et al (2012) evaluated the effectiveness of electromechanical and robot-assisted arm training for improving generic ADL, arm function, and arm muscle strength in patients after stroke.  These investigators also assessed the acceptability and safety of the therapy.  They searched the Cochrane Stroke Group's Trials Register (last searched July 2011), the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library 2011, Issue 7), MEDLINE (1950 to July 2011), EMBASE (1980 to July 2011), CINAHL (1982 to July 2011), AMED (1985 to July 2011), SPORTDiscus (1949 to July 2011), PEDro (searched August 2011), COMPENDEX (1972 to July 2011), and INSPEC (1969 to July 2011).  They also hand-searched relevant conference proceedings, searched trials and research registers, checked reference lists, and contacted trialists, experts and researchers in the field, as well as manufacturers of commercial devices.  Randomized controlled trials comparing electromechanical and robot-assisted arm training for recovery of arm function with other rehabilitation or placebo interventions, or no treatment, for patients after stroke were selected for analysis.  Two review authors independently selected trials for inclusion, assessed trial quality, and extracted data.  They contacted trialists for additional information.  They analysed the results as standardized mean differences (SMDs) for continuous variables and risk differences (RDs) for dichotomous variables.  These researchers included 19 trials (involving 666 participants) in this updated review.  Electromechanical and robot-assisted arm training did improve activities of daily living (SMD 0.43, 95 % confidence interval (CI): 0.11 to 0.75, p = 0.009, I(2) = 67 %) as well as arm function (SMD 0.45, 9 5% CI: 0.20 to 0.69, p = 0.0004, I(2) = 45 %), but arm muscle strength did not improve (SMD 0.48, 95 % CI: -0.06 to 1.03, p = 0.08, I(2) = 79 %).  Electromechanical and robot-assisted arm training did not increase the risk of patients to drop-out (RD 0.00, 95 % CI: -0.04 to 0.04, p = 0.82, I(2) = 0.0 %), and adverse events were rare.  The authors concluded that patients who receive electromechanical and robot-assisted arm training after stroke are more likely to improve their generic ADL.  Paretic arm function may also improve, but not arm muscle strength.  However, the authors stated that results must be interpreted with caution because there were variations between the trials in the duration and amount of training, type of treatment, and in the patient characteristics.

Hussain et al (2011) stated that the rehabilitation engineering community is working towards the development of robotic devices that can assist during gait training of patients suffering from neurologic injuries such as stroke and SCI.  The field of robot-assisted treadmill training has rapidly evolved during the last decade.  The robotic devices can provide repetitive, systematic and prolonged gait training sessions.  These researchers presented a review of the treadmill-based robotic gait training devices.  An overview of design configurations and actuation methods used for these devices was provided.  Training strategies designed to actively involve the patient in robot-assisted treadmill training were studied.  These training strategies assist the patient according to the level of disability and type of neurologic injury.  The authors stated that although the effectiveness of these training strategies is not clinically proven, adaptive strategies may result in substantial improvements.

Alcobendas-Maestro et al (2012) compared a walking re-education program using Lokomat with conventional over-ground training among individuals with incomplete SCI of both traumatic and non-traumatic etiology.  A total of 80 participants from 3 to 6 months after onset admitted to 1 site for rehabilitation were included in a single-blind RCT of 2 parallel groups, with blind evaluation by independent observers.  Patients received 40 walking re-education sessions of equal time using a Lokomat program with over-ground practice or over-ground mobility therapy alone.  Primary measurements of outcome were walking speed and the WISCI II; secondary outcomes were the 6-min walk test, locomotor section of the functional independence measure, lower extremity motor score (LEMS), Ashworth Scale, and visual analog scale for pain.  No significant differences were found at entry between treatment groups.  Walking speed for Lokomat (0.4 m/s [0.6 to 0.2]) and over-ground therapy (0.3 m/s [0.5 to 0.2]) groups did not differ.  The WISCI II for the Lokomat group (16 [8.5 to 19]) was better than for over-ground therapy (9 [8 to 16]).  The 6-min walk test and LEMS displayed significant differences in favor of Lokomat therapy but were not corrected for multiple comparisons.  The authors concluded that robotic-assisted training was equivalent to conventional walk training in patients with a variety of non-progressive spinal cord pathologies for walking speed, but the need for orthotics and assistive devices was reduced, perhaps because of greater leg strength in the robotic group.

In a Cochrane review, Mehrholz et al (2013) examined the effects of automated electromechanical and robotic-assisted gait training devices for improving walking after stroke.  These investigators searched the Cochrane Stroke Group Trials Register (last searched April 2012), the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library 2012, Issue 2), MEDLINE (1966 to November 2012), EMBASE (1980 to November 2012), CINAHL (1982 to November 2012), AMED (1985 to November 2012), SPORTDiscus (1949 to September 2012), the Physiotherapy Evidence Database (PEDro, searched November 2012) and the engineering databases COMPENDEX (1972 to November 2012) and INSPEC (1969 to November 2012).  They also  hand-searched relevant conference proceedings, searched trials and research registers, checked reference lists and contacted authors in an effort to identify further published, unpublished and ongoing trials.  These researchers included all randomized and randomized cross-over trials consisting of people over 18 years old diagnosed with stroke of any severity, at any stage, or in any setting, evaluating electromechanical and robotic-assisted gait training versus normal care.  Two review authors independently selected trials for inclusion, assessed methodological quality and extracted the data.  The primary outcome was the proportion of participants walking independently at follow-up.  In this update of their review, these investigators included 23 trials involving 999 participants.  Electromechanical-assisted gait training in combination with physiotherapy increased the odds of participants becoming independent in walking (odds ratio (OR) (random effects) 2.39, 95 % CI: 1.67 to 3.43; p < 0.00001; I² = 0 %) but did not significantly increase walking velocity (mean difference (MD) = 0.04 meters/s, 95% CI: -0.03 to 0.11; p = 0.26; I² = 73 %) or walking capacity (MD = 3 meters walked in 6 minutes, 95 % CI: -29 to 35; p = 0.86; I² = 70 %).  The results must be interpreted with caution because
  1. some trials investigated people who were independent in walking at the start of the study,
  2. these researchers found variations between the trials with respect to devices used and duration and frequency of treatment, and
  3. some trials included devices with functional electrical stimulation.
The planned subgroup analysis suggested that people in the acute phase may benefit but people in the chronic phase may not benefit from electromechanical-assisted gait training.  Post-hoc analysis showed that people who are non-ambulatory at intervention onset may benefit but ambulatory people may not benefit from this type of training.  Furthermore, post-hoc analysis showed no differences between the types of devices used in studies regarding ability to walk, but significant differences were found between devices in terms of walking velocity.  The authors concluded that people who receive electromechanical-assisted gait training in combination with physiotherapy after stroke are more likely to achieve independent walking than people who receive gait training without these devices. Specifically, people in the first 3 months after stroke and those who are not able to walk seem to benefit most from this type of intervention.  The role of the type of device is still not clear.  They stated that further research should consist of a large definitive, pragmatic, phase III trial undertaken to address specific questions such as the following: What frequency or duration of electromechanical-assisted gait training might be most effective?  How long does the benefit last?

Morawietz and Moffat (2013) provided an overview of, and evaluated the current evidence on, locomotor training approaches for gait rehabilitation in individuals with incomplete SCI to identify the most effective therapies.  The following electronic databases were searched systematically from first date of publication until May 2013: Allied and Complementary Medicine Database, Cumulative Index to Nursing and Allied Health Literature, Cochrane Database of Systematic Reviews, Medline, Physiotherapy Evidence Database, and PubMed.  References of relevant clinical trials and systematic reviews were also hand-searched.  Only RCTs evaluating locomotor therapies after incomplete SCI in an adult population were included.  Full-text versions of all relevant articles were selected and evaluated by both authors.  Eligible studies were identified, and methodological quality was assessed with the Physiotherapy Evidence Database scale.  Articles scoring less than 4 points on the scale were excluded.  Sample population, interventions, outcome measures, and findings were evaluated with regard to walking capacity, velocity, duration, and quality of gait.  Data were analyzed by systematic comparison of findings.  A total of 8 articles were included in this review; 5 compared body-weight-supported treadmill training (BWSTT) or robotic-assisted BWSTT with conventional gait training in acute/subacute subjects (less than or equal to 1 year post-injury).  The remaining studies each compared 3 or 4 different locomotor interventions in chronic participants (greater than1y post-injury).  Sample sizes were small, and study designs differed considerably impeding comparison.  Only minor differences in outcomes measures were found between groups.  Gait parameters improved slightly more after BWSTT and robotic gait training for acute participants.  For chronic participants, improvements were greater after BWSTT with functional electrical stimulation (FES) and over-ground training with FES/body-weight support compared with BWSTT with manual assistance, robotic gait training, or conventional physiotherapy.  The authors concluded that evidence on the effectiveness of locomotor therapy is limited.  All approaches show some potential for improvement of ambulatory function without superiority of 1 approach over another.  They stated that more research on this topic is required.

Dobkin and Duncan (2012) stated that body weight-supported treadmill training (BWSTT) and robotic-assisted step training (RAST) have not, so far, led to better outcomes than a comparable dose of progressive over-ground training (OGT) for disabled persons with stroke, SCI, multiple sclerosis (MS), Parkinson's disease (PD), or CP.  The conceptual bases for these promising rehabilitation interventions had once seemed quite plausible, but the results of well-designed, RCTs have been disappointing.  The authors re-assessed the under-pinning concepts for BWSTT and RAST, which were derived from mammalian studies of treadmill-induced hind-limb stepping associated with central pattern generation after low thoracic spinal cord transection, as well as human studies of the triple-crown icons of task-oriented locomotor training, massed practice, and activity-induced neuroplasticity.  The authors retrospectively considered where theory and practice may have fallen short in the pilot studies that aimed to produce thoroughbred interventions.  Based on these shortcomings, the authors moved forward with recommendations for the future development of workhorse interventions for walking.  The authors concluded that in the absence of evidence for physical therapists to employ these strategies, however, BWSTT and RAST should not be provided routinely to disabled, vulnerable persons in place of OGT outside of a scientifically conducted efficacy trial.

Vaney et al (2012) examined if RAGT (Lokomat) is superior to over-ground walking training in terms of quality of life, activity level, and gait in patients with MS.  A total of 67 patients with MS with the Expanded Disability Status Scale (EDSS) 3.0 to 6.5 were randomized to walking or RAGT, in addition to multi-modal rehabilitation.  Primary outcomes were walking speed, activity level (estimated metabolic equivalent, metabolic equivalents [METs], using an accelerometer), and quality of life (Well-Being visual analog scale (VAS) and EQ-5D European VAS.  In all, 49 patients finished the interventions.  Mean age was 56 years (range of 36 to 74 years), mean EDSS was 5.8 (3.0 to 6.5), and the preferred walking speed at baseline was 0.56 m/s (0.06 to 1.43 m/s).  Before rehabilitation, participants spent on average 68 min/day at an MET greater than or equal to 3.  The walking group improved gait speed non-significantly more than the RAGT; the upper bound of the CI did not exclude a clinically relevant benefit (defined as a difference of 0.05 m/s) in favor of the walking group; the lower bound of the CI did exclude a clinically important benefit in favor of the Lokomat.  Quality of life improved in both groups, with a non-significant between-group difference in favor of the walking group. Both groups had reduced their activity by 8 weeks after the rehabilitation.  The authors concluded that it is unlikely that RAGT is better than over-ground walking training in patients with an EDSS between 3.0 and 6.5.

In a RCT, Picelli et al (2012) examined if a rehabilitation program of RAGT is more effective than conventional physiotherapy to improve walking in patients with PD.  A total of 41 patients with PD were randomly assigned to 45-min treatment sessions (12 in all), 3 days a week, for 4 consecutive weeks of either robotic stepper training (RST; n = 21) using the Gait Trainer or physiotherapy (PT; n = 20) with active joint mobilization and a modest amount of conventional gait training.  Participants were evaluated before, immediately after, and 1 month after treatment.  Primary outcomes were 10-m walking speed and distance walked in 6 mins.  Baseline measures revealed no statistical differences between groups, but the PT group walked 0.12 m/s slower; 5 patients withdrew.  A statistically significant improvement was found in favor of the RST group (walking speed 1.22 ± 0.19 m/s [p = 0.035]; distance 366.06 ± 78.54 m [p < 0.001]) compared with the PT group (0.98 ± 0.32 m/s; 280.11 ± 106.61 m).  The RAGT mean speed increased by 0.13 m/s, which is probably not clinically important.  Improvements were maintained 1 month later.  The authors concluded that RAGT may improve aspects of walking ability in patients with PD.  Moreover, they stated that future trials should compare robotic assistive training with treadmill or equal amounts of over-ground walking practice.

Yang and colleagues (2014) evaluated the plantar pressure distribution during the robotic-assisted walking, guided through normal symmetrical hip and knee physiological kinematic trajectories, with unassisted walking in post-stroke hemiplegic patients.  A total of 15 hemiplegic stroke patients (who were able to walk a minimum of 10 meters independently but with asymmetric gait patterns) were enrolled in this study.  All the patients performed both the robotic-assisted walking (Lokomat) and the unassisted walking on the treadmill with the same body support in random order.  The contact area, contact pressure, trajectory length of center of pressure (COP), temporal data on both limbs and asymmetric index of both limbs were obtained during both walking conditions, using the F-Scan in-shoe pressure measurement system.  The contact areas of mid-foot and total foot on the affected side were significantly increased in robotic-assisted walking as compared to unassisted walking (p < 0.01).  The contact pressures of mid-foot and total foot on affected limbs were also significantly increased in robotic-assisted walking (p < 0.05).  The antero-posterior and medio-lateral trajectory length of COP were not significantly different between the 2 walking conditions, but their trajectory variability of COP was significantly improved (p < 0.05).  The asymmetric index of area, stance time, and swing time during robotic-assisted walking were statistically improved as compared with unassisted walking (p < 0.05).  The authors concluded that the robotic-assisted walking may be helpful in improving the gait stability and symmetry, but not the physiologic ankle rocker function.

In a randomized controlled trial, Gandolfi and associates (2014) compared the effectiveness of end-effector RAGT and sensory integration balance training (SIBT) in improving walking and balance performance in patients with MS.  A total of 22 patients with MS (EDSS: 1.5 to 6.5) were randomly assigned to 2 groups.  The RAGT group (n = 12) underwent end-effector system training; the SIBT group (n = 10) underwent specific balance exercises.  Each patient received 12 50-min treatment sessions (2 days/week).  A blinded rater evaluated patients before and after treatment as well as 1 month post-treatment.  Primary outcomes were walking speed and Berg Balance Scale.  Secondary outcomes were the Activities-specific Balance Confidence Scale, Sensory Organization Balance Test, Stabilometric Assessment, Fatigue Severity Scale, cadence, step-length, single and double support time, Multiple Sclerosis Quality of Life-54.  Between groups comparisons showed no significant differences on primary and secondary outcome measures over time.  Within group comparisons showed significant improvements in both groups on the Berg Balance Scale (p = 0.001).  Changes approaching significance were found on gait speed (p = 0.07) only in the RAGT group.  Significant changes in balance task-related domains during standing and walking conditions were found in the SIBT group.  The authors concluded that balance disorders in patients with MS may be ameliorated by RAGT and by SIBT.

In a randomized controlled trial, Picelli and colleagues (2015) compared RAGT versus balance training for reducing postural instability in patients with PD.  The secondary aim was to compare their effects on the level of confidence during activities of daily living requiring balance, functional mobility and severity of disease.  A total of 66 patients with PD at Hoehn and Yahr Stage 3 were enrolled in this study.  After balanced randomization, all patients received 12, 45-min treatment sessions, 3 days a week, for 4 consecutive weeks.  A group underwent RAGT with progressive gait speed increasing and body-weight support decreasing.  The other group underwent balance training aimed at improving postural reactions (self and externally induced destabilization, coordination, loco-motor dexterity exercises).  Patients were evaluated before, after and 1 month post-treatment.  Main outcome measure was Berg Balance Scale; secondary outcomes included Activities-Specific Balance Confidence Scale; Timed Up and Go Test; Unified Parkinson's Disease Rating Scale.  No significant differences were found between the groups for the Berg Balance Scale either immediately after intervention (mean score in the RAGT group 51.58 ± 3.94; mean score in the balance training group 51.15 ± 3.46), or 1-month follow-up (mean score in the robotic training group 51.03 ± 4.63; mean score in the balance training group 50.97 ± 4.28).  Similar results were found for all the secondary outcome measures.  The authors concluded that these findings indicated that RAGT is not superior to balance training for improving postural instability in patients with mild-to-moderate PD.

Rodger and colleagues (2020) noted that loss of arm function is common following stroke; and robot-assisted training may improve arm outcomes.  In an observer-blind, multi-center,  RCT with embedded health economic and process evaluations, these researchers examined the clinical effectiveness and cost-effectiveness of robot-assisted training, compared with an EULT program and with usual care.  The trial was set in 4 NHS trial centers.  Subjects were patients with moderate or severe upper limb functional limitation, between 1 week and 5 years following the 1st stroke.  Robot-assisted training using the Massachusetts Institute of Technology-Manus robotic gym system (InMotion commercial version, Interactive Motion Technologies, Inc., Watertown, MA), an EULT program comprising repetitive functional task practice, and usual care.  The primary outcome was upper limb functional recovery “success” (assessed using the Action Research Arm Test) at 3 months.  Secondary outcomes at 3 and 6 months were the Action Research Arm Test results, upper limb impairment (measured using the Fugl-Meyer Assessment), ADL (measured using the Barthel Activities of Daily Living Index), quality of life (QOL; measured using the Stroke Impact Scale), resource use costs and quality-adjusted life-years (QALYs).  A total of 770 subjects were randomized (robot-assisted training, n = 257; EULT, n = 259; usual care, n = 254).  Upper limb functional recovery “success” was achieved in the robot-assisted training [103/232 (44 %)], EULT [118/234 (50 %)] and usual care groups [85/203 (42 %)].  These differences were not statistically significant; the adjusted ORs were as follows: robot-assisted training versus usual care, 1.2 (98.33 % CI: 0.7 to 2.0); EULT versus usual care, 1.5 (98.33 % CI: 0.9 to 2.5); and robot-assisted training versus EULT, 0.8 (98.33 % CI: 0.5 to 1.3).  The robot-assisted training group had less upper limb impairment (as measured by the Fugl-Meyer Assessment motor subscale) than the usual care group at 3 and 6 months.  The EULT group had less upper limb impairment (as measured by the Fugl-Meyer Assessment motor subscale), better mobility (as measured by the Stroke Impact Scale mobility domain) and better performance in ADL (as measured by the Stroke Impact Scale activities of daily living domain) than the usual care group, at 3 months.  The robot-assisted training group performed less well in ADL (as measured by the Stroke Impact Scale ADL domain) than the EULT group at 3 months.  No other differences were clinically important and statistically significant.  Subjects found the robot-assisted training and the EULT group programs acceptable.  Neither intervention, as provided in this trial, was cost-effective at current National Institute for Health and Care Excellence willingness-to-pay thresholds for a QALY.  The authors concluded that robot-assisted training did not improve upper limb function compared with usual care.  Although robot-assisted training improved upper limb impairment, this did not translate into improvements in other outcomes; EULT resulted in potentially important improvements on upper limb impairment, in performance of ADL, and in mobility.  Neither intervention was cost-effective.  Moreover, these researchers stated that further research is needed to find ways to translate the improvements in upper limb impairment observed with robot-assisted training into improvements in upper limb function and ADL.  Innovations to make rehabilitation programs more cost-effective are needed.

The authors stated that the drawbacks of this study were pragmatic inclusion criteria led to the recruitment of some subjects with little prospect of recovery.  The attrition rate was higher in the usual care group than in the robot-assisted training or EULT groups, and differential attrition was a potential source of bias.  They stated that obtaining accurate information regarding the usual care that subjects were receiving was a challenge.

Fernandez-Garcia and associates (2021) examined if robot-assisted training is cost-effective compared with an EULT program or usual care.  This trial was carried out in 4 National Health Service (NHS) centers in the UK: Queen's Hospital, Barking, Havering and Redbridge University Hospitals NHS Trust; Northwick Park Hospital, London Northwest Healthcare NHS Trust; Queen Elizabeth University Hospital, NHS Greater Glasgow and Clyde; and North Tyneside General Hospital, Northumbria Healthcare NHS Foundation Trust.  A total of 770 subjects aged 18 years or older with moderate or severe upper limb functional limitation from first-ever stroke were included in this study; they were randomized to 1 of 3 programs provided over a 12-week period: robot-assisted training plus usual care; the EULT program plus usual care or usual care.  Main economic outcome measures included mean healthcare resource use; costs to the NHS and personal social services in 2018 pounds; utility scores based on EQ-5D-5L responses and QALYs.  Cost-effectiveness reported as incremental cost per QALY and cost-effectiveness acceptability curves.  At 6 months, on average usual care was the least costly option (£3,785) followed by EULT (£4,451) with robot-assisted training being the most-costly option (£5,387).  The MD in total costs between the usual care and robot-assisted training groups (£1,601) was statistically significant (p < 0.001).  Mean QALYs were highest for the EULT group (0.23) but no evidence of a difference (p = 0.995) was observed between the robot-assisted training (0.21) and usual care groups (0.21).  The incremental cost per QALY at 6 months for subjects randomized to EULT compared with usual care was £74,100.  Cost-effectiveness acceptability curves showed that robot-assisted training was unlikely to be cost-effective and that EULT had a 19 % chance of being cost-effective at the £20,000 willingness to pay (WTP) threshold.  Usual care was most likely to be cost-effective at all the WTP values considered in the analysis.  The authors concluded that the cost-effectiveness analysis suggested that neither robot-assisted training nor EULT, as delivered in this trial, was likely to be cost-effective at any of the cost per QALY thresholds considered.

Reis and co-workers (2021) stated that robot-assisted therapy and non-invasive brain stimulation (NIBS) are promising strategies for stroke rehabilitation.  In a systematic review and meta-analysis, these researchers examined the evidence of NIBS as an add-on intervention to robotic therapy to improve outcomes of upper-limb motor impairment or activity in individuals with stroke.  This study was carried out according to the PRISMA protocol.  A total of 7 databases and gray literature were systematically searched by 2 reviewers, and 1,176 registers were accessed; 8 randomized clinical trials with upper-limb body structure/function or activity limitation outcome measures were included.  Subgroup analyses were carried out according to phase post-stroke, device characteristics (i.e., arm support, joints involved, unimanual or bimanual training), NIBS paradigm, timing of stimulation, and number of sessions.  The Grade-Pro Software was used to assess quality of the evidence.  A non-significant homogeneous summary effect size was found both for body structure function domain (MD = 0.15; 95 % CI: -3.10 to 3.40; p = 0.93; I2 = 0 %) and activity limitation domain (standard MD [SMD] = 0.03; 95%  CI: -0.28 to 0.33; p = 0.87; I2 = 0 %).  The authors concluded that according to this systematic review and meta-analysis, there are not enough data regarding the benefits of NIBS as an add-on intervention to robot-assisted therapy on upper-limb motor function or activity in individuals with stroke.

Morone et al (2021) noted that upper limb motor impairment is one of the most frequent stroke consequences.  Robot therapy may represent an option for upper limb stroke rehabilitation; however, there are still gaps between research evidence and their use in clinical practice.  In a systematic review, these researchers examined the quality, scope, and consistency of guidelines clinical practice recommendations for upper limb robotic rehabilitation in stroke populations.  They searched for guideline recommendations on stroke published between January 1, 2010 and January 1, 2020.  Only the most recent guidelines for writing group were selected.  Electronic databases (n = 4), guideline repertories and professional rehabilitation networks (n = 12) were searched.  These investigators systematically reviewed and evaluated guidelines containing recommendation statements about upper limb robotic rehabilitation for adults with stroke.  A total of 4 independent reviewers used the Appraisal of Guidelines for Research and Evaluation (AGREE) II instrument, and textual syntheses were used to appraise and compare recommendations.  From 1,324 papers that were screened, 8 eligible guidelines were identified from 6 different regions/countries.  Half of the included guidelines focused on stroke management, the other half on stroke rehabilitation.  Rehabilitation aided by robotic devices is generally recommended to improve upper limb motor function and strength.  The exact characteristics of patients who could benefit from this treatment as well as the correct timing to use it are unknown.  The authors concluded that despite the increasing evidence of robotics effectiveness on upper limb strength and motor function, guidelines need to be improved, especially in the fields of applicability and in particular should clarify the selected patient subgroup that could benefit from robotic devices as well as the optimal time window and dose of this therapeutic approach.  These investigators stated that future research should focus on the robotic treatment measures among a general specific guidance on assessment of the upper limb measures.

Baniqued et al (2021) stated that hand rehabilitation is important in helping stroke survivors regain ADL.  Recent studies have suggested that the use of electroencephalography (EEG)-based brain-computer interfaces (BCI) can promote this process.  These investigators reported the 1st systematic examination of the literature on the use of BCI-robot systems for the rehabilitation of fine motor skills associated with hand movement and profiled these systems from a technical and clinical perspective.  These investigators carried out searches for articles (January 2010 to October 2019) using Ovid Medline, Embase, PEDro, PsycINFO, IEEE Xplore and Cochrane Library databases.  The selection criteria included BCI-hand robotic systems for rehabilitation at different stages of development involving tests on healthy subjects or individuals who have had a stroke.  Data fields included those related to study design, participant characteristics, technical specifications of the system, and clinical outcome measures.  A total of 30 studies were identified as eligible for qualitative review and among these, 11 studies involved testing a BCI-hand robot on chronic and subacute stroke patients.  Statistically significant improvements in motor assessment scores relative to controls were observed for 3 BCI-hand robot interventions.  The degree of robot control for the majority of studies was limited to triggering the device to perform grasping or pinching movements using motor imagery.  Most employed a combination of kinesthetic and visual response via the robotic device and display screen, respectively, to match feedback to motor imagery.  The authors concluded that 19 out of 30 studies on BCI-robotic systems for hand rehabilitation reported systems at prototype or pre-clinical stages of development.  These researchers identified large heterogeneity in reporting and emphasized the need to develop a standard protocol for evaluating technical and clinical outcomes so that the necessary evidence based on efficiency and efficacy can be developed.

Robotic-Assisted Rehabilitation for Traumatic Brain Injury

Meyer-Heim et al (2007) stated that intensive, task-specific training enabled by a driven gait orthosis (DGO) may be a cost-effective means of improving walking performance in children.  A pediatric DGO has recently been developed.  This study was the first pediatric trial aimed to determine the feasibility of robotic-assisted treadmill training in children with central gait impairment (n = 26; 11 females, 15 males; mean age of 10 years 1 month [SD 4 years]; range of 5 years 2 months to 19 years 5 months).  Diagnoses of the study group included cerebral palsy (n = 19; Gross Motor Function Classification System Levels I-IV), traumatic brain injury (TBI, n = 1), Guillain-Barre syndrome (n = 2), incomplete paraplegia (n = 2), and hemorrhagic shock (n = 1), and encephalopathy (n = 1); 16 children were in-patients and 10 were outpatients.  Twenty-four of the 26 patients completed the training which consisted of a mean of 19 sessions (SD 2.2; range of 13 to 21) in the in-patient group and 12 sessions (SD 1.0; range of 10 to 13) in the outpatient group.  Gait speed and 6MinWT increased significantly (p < 0.01).  Functional Ambulation Categories and Standing dimension (in-patient group p < 0.01; outpatient group p < 0.05) of the Gross Motor Function Measure improved significantly.  The authors concluded that DGO training was successfully integrated into the rehabilitation program and findings suggested an improvement of locomotor performance.  Thee preliminary findings need to be validated by well-designed studies.

Sacco and colleagues (2011) stated that it has been demonstrated that automated locomotor training can improve walking capabilities in SCI subjects but its effectiveness on brain damaged patients has not been well-established.  A possible explanation of the discordant results on the effectiveness of robotic training in patients with cerebral lesions could be that these patients, besides stimulation of physiological motor patterns through passive leg movements, also need to train the cognitive aspects of motor control.  Indeed, another way to stimulate cerebral motor areas in paretic patients is to use the cognitive function of motor imagery.  A promising possibility is thus to combine sensorimotor training with the use of motor imagery.  These researchers evaluated changes in brain activations after a combined sensorimotor and cognitive training for gait rehabilitation.  The protocol consisted of the integrated use of a robotic gait orthosis prototype with locomotor imagery tasks.  Assessment was conducted on 2 patients with chronic TBI and major gait impairments, using functional magnetic resonance imaging.  Physiatric functional scales were used to assess clinical outcomes.  Results showed greater activation post-training in the sensorimotor and supplementary motor cortices, as well as enhanced functional connectivity within the motor network.  Improvements in balance and, to a lesser extent, in gait outcomes were also found.  The authors concluded that concluded that "Our robotic and cognitive gait rehabilitation (RCGR) protocol appears to be a useful tool for gait rehabilitation in TBI patients, whose primary impact is on balance impairment.  It may enhance both the subcortical motor automatisms and the cortical processes of motor learning.  Systematic studies involving a greater number of participants and follow-up assessments are necessary in order to confirm our suggestions".

In a review on "Efficacy of rehabilitation robotics for walking training in neurological disorders", Tefertiller et al (2011) stated that "The evidence in TBI and PD [Parkinson’s disease] is insufficient to suggest the use of locomotor training with robotic assistance is of benefit in these populations".

In a randomized, prospective study, Esquenazi et al (2013) compared the effects of robotic-assisted treadmill training (RATT) and manually assisted treadmill training (MATT) in participants with TBI and determined the potential impact on the symmetry of temporal walking parameters, 6MinWT, and the mobility domain of the Stroke Impact Scale, version 3.0 (SIS).  A total of 16 participants with TBI and a baseline over ground walking self-selected velocity (SSV) of greater than or equal to 0.2 m/s to 0.6 m/s were randomly assigned to either the RATT or MATT group.  Participant received gait training for 45 minutes, 3 times a week with either RATT or MATT for a total of 18 training sessions.  Primary outcome measures were over-ground walking SSV, maximal velocity.  Secondary outcome measures were spatio-temporal symmetry, 6MinWT, and SIS.  Between-group differences were not statistically significant for any measure.  However, from pre-training to post-training, the average SSV increased by 49.8 % for the RATT group (p = 0.01) and by 31 % for MATT group (p = 0.06).  The average maximal velocity increased by 14.9 % for the RATT group (p = 0.06) and by 30.8 % for the MATT group (p = 0.01).  Less staffing and effort was needed for RATT in this study.  Step-length asymmetry ratio improved during SSV by 33.1 % for the RATT group (p = 0.01) and by 9.1 % for the MATT group (p = 0.73).  The distance walked increased by 11.7 % for the robotic group (p = 0.21) and by 19.3 % for manual group (p = 0.03).  A statistically significant improvement in the mobility domain of the SIS was found for both groups (p ≤ 0.03).  The authors concluded that the results of this study demonstrated greater improvement in symmetry of gait (step length) for RATT and no significant differences between RATT and MATT with regard to improvement in gait velocity, endurance, and SIS.  They stated that the findings of this study provided evidence that participants with a chronic TBI can experience improvements in gait parameters with gait training with either MATT or RATT.

Wolf and colleagues (2015) stated that robotic therapy may enhance tele-rehabilitation by delivering consistent and state-of-the art therapy while allowing remote monitoring and adjusting therapy for under-served populations. The Hand Mentor Pro (HMP) was incorporated within a home exercise program (HEP) to improve upper-extremity (UE) functional capabilities post-stroke.  In a prospective, single-blinded, multi-site RCT, these investigators examined the effectiveness of a home-based tele-monitored robotic-assisted therapy as part of a HEP compared with a dose-matched HEP-only intervention among individuals less than 6 months post-stroke and characterized as under-served.  A total of 99 hemi-paretic participants with limited access to UE rehabilitation were randomized to either
  1. the experimental group, which received combined HEP and HMP for 3 hours/day × 5 days × 8 weeks, or
  2. the control group, which received HEP only at an identical dosage. 
Weekly communication between the supervising therapist and participant promoted compliance and progression of the HEP and HMP prescription.  The Action Research Arm Test and Wolf Motor Function Test along with the Fugl-Meyer Assessment (UE) were primary and secondary outcome measures, respectively, undertaken before and after the interventions.  Both groups demonstrated improvement across all UE outcomes.  The authors concluded that robotic + HEP and HEP only were both effectively delivered remotely.  There was no difference between groups in change in motor function over time.  They stated that additional research is needed to determine the appropriate dosage of HMP and HEP.
In a prospective, open, blinded end-point, randomized, multi-center exploratory clinical trial, Takahashi et al (2016) assessed the effectiveness of robotic therapy as an adjuvant to standard therapy during post-stroke rehabilitation. A total of 60 individuals with mild-to-moderate hemiplegia 4 to 8 weeks post-stroke were randomized to receive standard therapy plus 40 minutes of either robotic or self-guided therapy for 6 weeks (7 days/week); UE impairment before and after intervention was measured using the Fugl-Meyer assessment, Wolf Motor Function Test, and Motor Activity Log.  Robotic therapy significantly improved Fugl-Meyer assessment flexor synergy (2.1 ± 2.7 versus -0.1 ± 2.4; p < 0.01) and proximal UE (4.8 ± 5.0 versus 1.9 ± 5.5; p < 0.05) compared with self-guided therapy.  No significant changes in Wolf Motor Function Test or Motor Activity Log were observed.  Robotic therapy also significantly improved Fugl-Meyer assessment proximal UE among low-functioning patients (baseline Fugl-Meyer assessment score of less than 30) and among patients with Wolf Motor Function Test greater than or equal to 120 at baseline compared with self-guided therapy (p < 0.05 for both).  The authors concluded that robotic therapy as an adjuvant to standard rehabilitation may improve UE recovery in moderately impaired post-stroke patients.  However, they stated that results of this exploratory study should be interpreted with caution.
In a RCT, Taveggia et al (2016) evaluated the effectiveness of robotic-assisted motion and activity in additional to Physical and Rehabilitation Medicine (PRM), of the upper limb in post-stroke inpatients. A total of 54 patients (57 % female, mean ± SD age of 71 ± 12 years), with upper limb function deficit post-stroke were included in this study.  The experimental group received a passive mobilization of the upper limb through the robotic device ARMEO Spring and the control group received PRM for 6 consecutive weeks (5 days/week) in addition to traditional PRM.  These investigators evaluated the impact on functional recovery (Functional Independence Measure-FIM scale), strength (ARM Motricity Index [MI]), spasticity (Modified Ashworth Scale [MAS]) and pain (Numeric Rating Pain Scale [NRPS]).  All patients were evaluated by a blinded observer using the outcomes tests at enrollment (T0), after the treatment (T1) and at follow-up 6 weeks later (T2).  Both control and experimental groups evidenced an improvement of the outcomes after the treatment (MI, MAS and NRPS with p < 0.05).  The experimental group showed further improvements after the follow-up (all outcomes with p < 0.01).  The authors concluded that in the treatment of pain, disability and spasticity in upper limb post-stroke, robot-assisted mobilization associated to PRM is as effective as traditional rehabilitation.  The main drawbacks of this study were its relatively small sample size and short-term follow-up.  These findings need to be validated by further research.
Pirondini et al (2016) noted that exoskeletons for lower and upper extremities have been introduced in neuro-rehabilitation because they can guide the patient's limb following its anatomy, covering many degrees of freedom and most of its natural workspace, and allowing the control of the articular joints. These researchers evaluated the possible use of a novel exoskeleton, the Arm Light Exoskeleton (ALEx), for robot-aided neuro-rehabilitation and examined the effects of some rehabilitative strategies adopted in robot-assisted training.  They studied movement execution and muscle activities of 16 upper limb muscles in 6 healthy subjects, focusing on end-effector and joint kinematics, muscle synergies, and spinal maps.  The subjects performed three dimensional (3D) point-to-point reaching movements, without and with the exoskeleton in different assistive modalities and control strategies.  The results showed that ALEx supported the upper limb in all modalities and control strategies: it reduced the muscular activity of the shoulder's abductors and it increased the activity of the elbow flexors.  The different assistive modalities favored kinematics and muscle coordination similar to natural movements, but the muscle activity during the movements assisted by the exoskeleton was reduced with respect to the movements actively performed by the subjects.  Moreover, natural trajectories recorded from the movements actively performed by the subjects seemed to promote an activity of muscles and spinal circuitries more similar to the natural one.  The authors concluded that the preliminary analysis on healthy subjects supported the use of ALEx for post-stroke upper limb robotic-assisted rehabilitation, and it provided clues on the effects of different rehabilitative strategies on movement and muscle coordination.

Morone and associates (2016) noted that patients affected by mild stroke benefit more from physiological over-ground walking training than walking-like training performed in place using specific devices.  These researchers evaluated the effects of over-ground robotic walking training performed with the servo-assistive robotic rollator (i-Walker) on walking, balance, gait stability and falls in a community setting in patients with mild subacute stroke.  A total of 44 patients were randomly assigned to 2 different groups that received the same therapy in 2 daily 40-min sessions 5 days a week for 4 weeks; 20 sessions of standard therapy were performed by both groups.  In the other 20 sessions the subjects enrolled in the i-Walker-Group (iWG) performed with the i-Walker and the Control-Group patients (CG) performed the same amount of conventional walking oriented therapy.  Clinical and instrumented gait assessments were made pre- and post-treatment.  The follow-up observation consisted of recording the number of fallers in the community setting after 6 months.  Treatment effectiveness was higher in the iWG group in terms of balance improvement (Tinetti: 68.4 ± 27.6 % versus 48.1 ± 33.9 %, p = 0.033) and 10-meter and 6-min timed walking tests (significant interaction between group and time: F(1,40) = 14.252, p = 0.001; and F(1,40) = 7.883, p = 0.008, respectively).  When measured, latero-lateral upper body accelerations were reduced in iWG (F = 4.727, p = 0.036), suggesting increased gait stability, which was supported by a reduced number of falls at home.  The authors concluded that a robotic servo-assisted i-Walker improved walking performance and balance in patients affected by mild/moderate stroke, leading to increased gait stability and reduced falls in the community.

The authors stated that 2 main limitations were that the study was registered only after the end of data collection and that the follow-up assessment was limited to records concerning falls and no clinical or instrumental tool was used to assess balance and walking capabilities.  Further, the number of falls was self-reported by patients; therefore, it was conceivable that subjects under-reported the incidence of falls.  Another drawback was that it was unclear whether the improvements obtained using the i-Walker could also have been achieved by the control group if their training had been performed in more variable contexts.  In any case, this would have been very difficult to obtain because it would have involved greater effort on the part of the physiotherapist (or the intervention of more than 1 therapist) and could have led to safety problems related to patients’ falling (or fear of falling).  The authors stated that future research should evaluate the effect of the i-Walker in a larger sample and should include a follow-up group; it would be useful to explore the usefulness of the i-Walker as an assistive device for use in the home.

Lehman and colleagues (2017) stated that RAGT affords an opportunity to increase walking practice with mechanical assistance from robotic devices, rather than therapists, where the child may not be able to generate a sufficient or correct motion with enough repetitions to promote improvement.  However the devices are expensive and clinicians and families need to understand if the approach is worthwhile for their children, and how it may be best delivered.  These researchers appraised the existing evidence for the effectiveness of RAGT for pediatric gait disorders, including modes of delivery and potential benefit.  A total of 6 databases were searched from 1980 to October 2016, using relevant search terms.  Any clinical trial that evaluated a clinical aspect of RAGT for children/adolescents with altered gait was selected for inclusion.  Data were extracted following the PRISMA approach.  A total of 17 trials were identified, assessed for level of evidence and risk of bias, and appropriate data extracted for reporting; 3 RCTs were identified, with the remainder of lower level design.  Most individual trials reported some positive benefits for RAGT with children with CP, on activity parameters such as standing ability, walking speed and distance.  However a meta-analysis of the 2 eligible RCTs did not confirm this finding (p = 0.72).  Training schedules were highly variable in duration and frequency and adverse events (AEs) were either not reported or were minimal.  There was a paucity of evidence for diagnoses other than CP.  The authors concluded that there is weak and inconsistent evidence regarding the use of RAGT for children with gait disorders.  If clinicians (and their clients) choose to use RAGT, they should monitor individual progress closely with appropriate outcome measures including monitoring of AEs.  They stated that further research is needed using higher level trial design, increased numbers, in specific populations and with relevant outcome measures to both confirm effectiveness and clarify training schedules.

Dierick and co-workers (2017) compared gait and posture outcome measures between ambulatory hemorrhagic patients and ischemic patients, who received a similar 4 weeks' intervention blending a conventional bottom-up physiotherapy approach and an exoskeleton top-down RAGT approach with Lokomat.  A total of 40 adult hemiparetic stroke inpatient subjects were recruited: 20 hemorrhagic and 20 ischemic, matched by age, gender, side of hemisphere lesion, stroke severity, and locomotor impairments.  Functional Ambulation Category, Postural Assessment Scale for Stroke, Tinetti Performance Oriented Mobility Assessment, 6- Minute Walk Test (6MWT), Timed Up and Go and 10-Meter Walk Test were performed before and after a 4-week long intervention.  Functional gains were calculated for all tests.  Hemorrhagic and ischemic subjects showed significant improvements in Functional Ambulation Category (p < 0.001 and p = 0.008, respectively), Postural Assessment Scale for Stroke (p < 0.001 and p = 0.003), 6MWT (p = 0.003 and p = 0.015) and 10-Meter Walk Test (p = 0.001 and p = 0.024).  Ischemic patients also showed significant improvements in Timed Up and Go.  Significantly greater mean Functional Ambulation Category and Tinetti Performance Oriented Mobility Assessment gains were observed for hemorrhagic compared to ischemic, with large (dz = 0.81) and medium (dz = 0.66) effect sizes, respectively.  The authors concluded that overall, both groups exhibited quasi similar functional improvements and benefits from the same type, length and frequency of blended conventional physiotherapy and RAGT protocol.  They stated that the use of intensive treatment plans blending top-down physiotherapy and bottom-up robotic approaches is promising for post-stroke rehabilitation.

Borboni and colleagues (2017) examined if passive robotic-assisted hand motion, in addition to standard rehabilitation, would reduce hand pain, edema, or spasticity in all patients following acute stroke, in patients with and without hand paralysis.  A total of 35 participants, aged 45 to 80 years, with functional impairments of their upper extremities after a stroke were recruited for the study from September 2013 to October 2013.  One group consisted of 16 patients (mean age ± SD of 68 ± 9 years) with full paralysis and the other groups included 14 patients (mean age ± SD of 67 ± 8 years) with partial paralysis.  Patients in the both groups used the Gloreha device for passive mobilization of the hand twice-daily for 2 consecutive weeks.  The primary outcome measure was hand edema; secondary outcome measures included pain intensity and spasticity.  All outcome measures were collected at baseline and immediately after the intervention (2 weeks).  Analysis of variance revealed that the partial paralysis group experienced a significantly greater reduction of edema at the wrist (p = 0.005) and pain (p = 0.04) when compared with the full paralysis group.  Other outcomes were similar for the groups.  The authors concluded that the findings of this study suggested that the partial paralysis group experienced a significantly greater reduction of edema at the wrist and pain when compared with the full paralysis group; however, the reduction in pain did not meet the threshold of a minimal clinically important difference.

In a systematic review, Mehrholz and associates (2017) compared the effectiveness of BWSTT and RAGT with over-ground gait training and other forms of physiotherapy in individuals with traumatic SCI.  These researchers performed an extensive search for RCTs involving people with traumatic SCI that compared either BWSTT or RAGT with over-ground gait training and other forms of physiotherapy.  The 2 outcomes of interest were walking speed (m s-1) and walking distance (m).  BWSTT and RAGT were analyzed separately, and data were pooled across trials to derive mean between-group differences using a random-effects model.  A total of 13 RCTs involving 586 people were identified; 10 trials involving 462 participants compared BWSTT to over-ground gait training and other forms of physiotherapy, but only 9 trials provided useable data.  The pooled mean (95 % CI) between-group differences for walking speed and walking distance were -0.03 m s-1 (-0.10 to 0.04) and -7 m (-45 to 31), respectively, favoring over-ground gait training; 5 trials involving 344 participants compared RAGT to over-ground gait training and other forms of physiotherapy, but only 3 provided useable data.  The pooled mean (95 % CI) between-group differences for walking speed and walking distance were -0.04 m s-1 (95 % CI: -0.21 to 0.13) and -6 m (95 % CI: -86 to 74), respectively, favoring over-ground gait training.  The authors concluded that BWSTT and RAGT did not increase walking speed more than over-ground gait training and other forms of physiotherapy did, but their effects on walking distance were unclear.

Cheung and colleagues (2017) examined the effects of robotic-assisted training on the recovery of people with SCI; RCTs or quasi-RCTs involving people with SCI that compared robotic-assisted upper limbs or lower limbs training to a control of other treatment approach or no treatment were selected for analysis.  These investigators included studies involving people with complete or incomplete SCI.  They searched in Medline, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Cochrane Central Register of Controlled Trials (Cochrane Library) and Excerpta Medica dataBASE (Embase) to August, 2016.  Bibliography of relevant articles on the effect of BWSTT on SCI subjects were screened to avoid missing relevant articles from the search of databases.  All kinds of objective assessments concerning physical ability, mobility and/or functional ability were included.  Assessments could be clinical tests (namely 6MWT and Functional Independence Measure) or laboratory test (i.e., gait analysis).  Subjective outcome measures were excluded from the present review.  A total of 11 RCT studies involving 443 subjects were included in the study.  Meta-analysis was performed on the included studies.  Walking independence (3.73 with 95 % CI: -4.92 to -2.53; p < 0.00001; I2 = 38 %) and endurance (53.32 m with 95 % CI: - 73.15 to -33.48; p < 0.00001; I2 = 0 %) were found to have better improvement in robotic-assisted training groups.  Lower limb robotic-assisted training was also found to be as effective as other types of body weight supported training.  There is a lack of upper limb robotic-assisted training studies, so a meta-analysis was not possible to be performed.  The authors concluded that robotic-assisted training is an adjunct therapy for physical and functional recovery for patients with SCI.  Moreover, they stated that future high-quality studies are needed to investigate the effects of robotic-assisted training on functional and cardiopulmonary recovery of SCI patients.

Intrepid Dynamic Exoskeletal Orthosis (IDEO)

The Intrepid Dynamic Exoskeletal Orthosis (IDEO) is a customized energy storing ankle-foot orthosis (AFO) developed by the U.S. Army for individuals who have suffered massive tissue, nerve and bone damage to supposedly return capabilities to the injured ankle.  It is designed to support and protect an extensive array of lower extremity limb injuries.  The device supposedly supplies energy storage and return capabilities that an injured ankle is no longer able to provide.  Purportedly, the individual can return to a high level of activity, such as running. The IDEO device is molded out of lightweight black carbon that includes a foot plate and a strut that runs up the back of the calf to a cuff that is situated just below the knee. Reportedly, when force is applied to the foot plate, the strut bends. As the individual steps down, it bends the foot plate, transferring energy forward. 
The IDEO is intended to return functionality to patients who have undergone ankle fusion procedures and to enable some patients with nerve and muscle loss to forgo ankle fusion or tendon transfer.  The IDEO is modular throughout the rehabilitation period to adapt to a patient’s changes in strength and motion.  Once the patient has progressed to an adequate level of recovery, the initial modular IDEO is replaced with a lighter, more dynamic definitive IDEO system.  Currently, there is insufficient evidence to support the clinical value of this device.
Bedigrew et al (2014) noted that patients with severe lower extremity trauma have significant disability 2 years after injury that worsens by 7 years.  Up to 15 % seek late amputation.  Recently, an energy-storing orthosis (IDEO) demonstrated improved function compared with standard orthoses; however, the effect when integrated with rehabilitation over time is unknown.  These researchers questioned
  1. Does an 8-week integrated orthotic and rehabilitation initiative improve physical performance, pain, and outcomes in patients with lower extremity functional deficits or pain?
  2. Is the magnitude of recovery different if enrolled more than 2 years after their injury versus earlier?
  3. Does participation decrease the number considering late amputation? 
These investigators prospectively evaluated 84 service members (53 less than and 31 greater than 2 years after injury) who enrolled in the initiative.  A total of 58 sustained fractures, 53 sustained nerve injuries with weakness, and 6 had arthritis (there was some overlap in the patients with fractures and nerve injuries, which resulted in a total of greater than 84).  They completed 4 weeks of physical therapy without the orthosis followed by 4 weeks with it.  Testing was conducted at weeks 0, 4, and 8.  Validated physical performance tests and patient-reported outcome surveys were used as well as questions pertaining to whether patients were considering an amputation.  By 8 weeks, patients improved in all physical performance measures and all relevant patient-reported outcomes.  Patients less than and greater than 2 years after injury improved similarly; 41 of 50 patients initially considering amputation favored limb salvage at the end of 8 weeks.  The authors found that this integrated orthotic and rehabilitation initiative improved physical performance, pain, and patient-reported outcomes in patients with severe, traumatic lower extremity deficits and that these improvements were sustained for more than 2 years after injury.  They stated that efforts are underway to examine if the "Return to Run" clinical pathway with the IDEO can be successfully implemented at additional military centers in patients greater than 2 years from injury while sustaining similar improvements in patient outcomes.  The authors noted that the ability to translate this integrated orthotic and rehabilitation program into the civilian setting is unknown and warrants further investigation.
Russell et al (2014) noted that AFOs are commonly prescribed during rehabilitation after limb salvage; and AFO stiffness is selected to help mitigate gait deficiencies.  A new custom dynamic AFO, the IDEO, is available to injured service members but prescription guidelines are limited.  In this study, these researchers asked
  1. does dynamic AFO stiffness affect gait parameters such as joint angles, moments, and powers; and
  2. can a given dynamic AFO stiffness normalize gait mechanics to non-injured control subjects? 
A total of 13 patients with lower limb salvage (ankle arthrodesis, neuropathy, foot/ankle reconstruction, etc.) after major lower extremity trauma and 13 control subjects who had no lower extremity trauma and wore no orthosis underwent gait analysis at a standardized speed.  Patients wore their custom IDEO with posterior struts of 3 different stiffnesses:
  1. nominal (clinically prescribed stiffness),
  2. compliant (20 % less stiff), and
  3. stiff (20 % stiffer).
Joint angles, moments, powers, and ground reaction forces were compared across the varying stiffnesses of the orthoses tested and between the patient and control groups.  An increase in AFO compliance resulted in 20 % to 26 % less knee flexion relative to the nominal (p = 0.003) and stiff (p = 0.001) conditions, respectively.  Ankle ROM and power generation were, on average, 56 % (p < 0.001) and 63 % (p < 0.001), respectively, less than controls as a result of the relatively fixed ankle position.  The authors concluded that patients with limb salvage readily adapted to different dynamic AFO stiffnesses and demonstrated few biomechanical differences among conditions during walking.  None of the stiffness conditions normalized gait to controls.  These investigators stated that the general lack of differences across a 40 % range of strut stiffness suggested that orthotists do not need to invest large amounts of time identifying optimal device stiffness for patients who use dynamic AFOs for low-impact activities such as walking.  However, choosing a stiffer strut may more readily translate to higher-impact activities and offer less chance of mechanical failure.
There are 2 clinical trials on IDEO:
  1. the PRIORITI-MTF Study-Testing Patient Response to the IDEO and
  2. the Influence of Heel Wedge Properties on Roll-over of the Intrepid Dynamic Exoskeletal Orthosis (IDEO).
The PRIORITI-MTF Study-Testing Patient Response to the IDEO trial is currently recruiting participants.  The primary objective is to examine if a new type of custom designed brace (IDEO) along with a physical therapy program (Return to Run) improves physical function.  (Last updated November 10, 2014). 
The Influence of Heel Wedge Properties on Roll-over of the Intrepid Dynamic Exoskeletal Orthosis (IDEO) is not yet open for participant recruitment.  The primary objective is to determine how heel wedge properties may contribute to the smoothness of roll-over during gait.  Insight into the effects of heel wedge properties on roll-over will help optimize the design of the IDEO-heel wedge-shoe "system" and may produce guidelines for the customization of these features.  (Last verified July 2015). 

Velez-Guerrero and colleagues (2021) noted that processing and control systems based on artificial intelligence (AI) have progressively improved mobile robotic exoskeletons used in upper-limb motor rehabilitation.  In a systematic review, these investigators presented the advances and trends of those technologies.  They carried out a literature search in Scopus, IEEE Xplore, Web of Science, and PubMed using the PRISMA methodology with 3 main inclusion criteria: motor or neuromotor rehabilitation for upper limbs, mobile robotic exoskeletons, and AI.  The period under investigation spanned from 2016 to 2020, resulting in 30 articles that met the criteria.  The literature showed the use of artificial neural networks (40 %), adaptive algorithms (20 %), and other mixed AI techniques (40 %).  Furthermore, it was found that in only 16 % of the articles, developments focused on neuromotor rehabilitation.  The main trend in the research is the development of wearable robotic exoskeletons (53 %) and the fusion of data collected from multiple sensors that enriched the training of intelligent algorithms.  These researchers stated that there is a latent need to develop more reliable systems via clinical validation and improvement of technical characteristics, such as weight/dimensions of devices, in order to have positive impacts on the rehabilitation process and improve the interactions among patients, teams of health professionals, and technology.  The authors concluded that the current status of upper limb rehabilitation systems based on portable robotic exoskeletons shows that some relevant gaps should be filled in, where intelligent control and information processing systems can play key roles.  Furthermore, with the improvement of materials and the incorporation of better mechanical designs, the capabilities of exoskeletons can be largely improved.

Powered Hip Orthoses in Persons with Spinal Cord Injury

Arazpour and colleagues (2014) stated that gait training has been shown to improve the walking performance of spinal cord-injured (SCI) patients. The use of powered hip orthoses (PHO) during gait training is one approach which could potentially improve rehabilitative outcomes for such subjects. These researchers evaluated the influence of a PHO on the kinematics and temporal-spatial parameters of walking by SCI patients. The PHO used for the gait training of the volunteer SCI patients was custom made and fitted according to patient’s lower limb length, and the ankle foot orthosis portions of the orthosis were made after casting the lower extremities. The structure of orthosis and its efficacy when worn by one SCI patient has been described in a previously publication (Arazpour, et al., 2012). A total of 4 SCI patients participated in this study.  Gait evaluation was performed at baseline and at 10 weeks following intervention with the use of a PHO and gait re-training.  Walking speed, step length, vertical and horizontal compensatory motions and hip joint kinematics were analyzed prior to and following the training regime.  Significant increases in walking speed and step length were demonstrated by the SCI patients when walking with the PHO following orthotic gait training.  Sagittal plane hip range of motion also increased, but not significantly.  However, vertical and horizontal compensatory motions decreased significantly.  The authors concluded that positive effects on the kinematics and temporal-spatial parameters of gait by SCI subjects were demonstrated following a period of gait training with a PHO.  Moreover, they stated that further studies are needed to confirm their long-term effects on the rehabilitation of SCI subjects.
Arazpour and associates (2015) noted that powered orthoses are a new generation of assistive devices for people with SCI, which are designed to induce motion to paralyzed lower limb joints using external power via electric motors or pneumatic or hydraulic actuators. Powered gait orthoses provide activated movement of lower limb joints to limit the forces applied through the upper limb joints and trunk muscles during ambulation due to the need to use an external walking aid, while simultaneously improving the kinetics and kinematics of walking in subjects with SCI. These investigators reviewed the walking efficacy of powered orthoses when used by people with paraplegia.  A literature search was performed in ISI Web of Knowledge, PubMed, Google Scholar, ScienceDirect, and Scopus databases.  Efficacy was demonstrated in producing activated motion of lower limb joints.  Powered gait orthoses have a beneficial effect on the kinetics, kinematics, and temporal-spatial parameters of gait, but their effect on muscle activity in individuals with SCI is still unclear.  The authors concluded that further research is needed regarding the design and construction of powered gait orthoses using significant power application to the ankle joints and their effect on lower limb muscle activity and gait patterns in subjects with SCI.
Ahmadi Bani and co-workers (2015) stated that the most simple and common approach in providing standing and walking by subjects with SCI is the use of mechanical orthoses. These include traditional orthoses, medial linkage orthoses (MLOs) and reciprocating gait orthoses (RGOs). Independence, energy expenditure, gait parameters, system reliability and cosmesis are important factors in orthotic design.  These researchers compared the evidence of existing mechanical orthoses to that of other types regarding these factors.  The preferred reporting items for systematic reviews and meta-analyses (PRISMA) method was used by an experience researcher based on selected keywords and their composition and an electronic search was performed in well-known databases.  A total of 20 articles were selected for final evaluation.  Many were case studies, and also had limited and heterogeneous sample sizes with different instruments used for evaluation.  The results of the analysis demonstrated that independence and cosmesis were improved when using MLOs, but gait parameters, energy expenditure and stability were all improved when using RGOs.  The authors concluded that those mechanical orthoses which have reciprocal motion and congruency between the anatomical and orthotic joints have been shown to provide positive effects on patient lifestyles.  However, they stated that further improvement is needed to more effectively meet the needs of SCI patients.
Arazpour et al (2016) noted that orthoses for various joints sections are considered to greatly influence the gait function and energy expenditure in SCI patients. These investigators determined the influence of orthoses characteristics and options on the improvement of walking in patients with SCI.  They performed a search using the Population Intervention Comparison Outcome (PICO) method, based on selected keywords; studies were identified electronically in the Science Direct, Google Scholar, Scopus, Web of Knowledge and PubMed databases.  The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method was used to report the results.  Assessment of the quality of all articles was performed based on the Physiotherapy Evidence Database (PEDro scale).  A total of 12 studies evaluated the effects of different hip joint options on walking parameters and energy expenditure; 5 studies investigated the role of knee joint options on gait parameters and compensatory trunk motion.  Only 5 studies analyzed modified ankle joints on gait parameters in SCI patients; 9 studies analyzed gait parameters in SCI patients as powered orthoses and exoskeleton.  These studies had a low level of evidence according to the PEDro score (2/10).

Spinal Cord Injuries

Singh and associates (2018) provided an overview of the feasibility and outcomes of robotic-assisted upper extremity training for individuals with cervical SCI, and to identify gaps in current research and articulate future research directions.  A systematic search was conducted using Medline, Embase, PsycINFO, CCTR, CDSR, CINAHL and PubMed on June 7, 2017.  Search terms included 3 themes: robotics; SCI; and upper extremity. Studies using robots for upper extremity rehabilitation among individuals with cervical SCI were included. Identified articles were independently reviewed by two researchers and compared to pre-specified criteria.  Disagreements regarding article inclusion were resolved through discussion.  The modified Downs and Black checklist was used to assess article quality.  Participant characteristics, study and intervention details, training outcomes, robot features, study limitations and recommendations for future studies were abstracted from included articles.  A total of 12 articles (1 randomized clinical trial, 6 case series, 5 case studies) met the inclusion criteria; 5 robots were exoskeletons and 3 were end-effectors.  Sample sizes ranged from 1 to 17 subjects.  Articles had variable quality, with quality scores ranging from 8 to 20.  Studies had a low internal validity primarily from lack of blinding or a control group.  Individuals with mild-moderate impairments showed the greatest improvements on body structure/function and performance-level measures.  This review was limited by the small number of articles, low-sample sizes and the diversity of devices and their associated training protocols, and outcome measures.  The authors concluded that preliminary evidence suggested that robot-assisted interventions are safe, feasible and can reduce active assistance provided by therapists.  Moreover, they stated that future research in robotics rehabilitation with individuals with SCI is needed to determine the optimal device and training protocol as well as effectiveness.
Hayes and colleagues (2018) systematically reviewed the literature and identify if over-ground or treadmill based RAGT use in SCI individuals elicited differences in temporal-spatial characteristics and functional outcome measures.  A systematic search of the literature investigating over-ground and treadmill RAGT in SCIs was undertaken excluding case-studies and case-series.  Studies were included if the primary outcomes were temporal-spatial gait parameters.  Study inclusion and methodological quality were assessed and determined independently by 2 reviewers.  Methodological quality was assessed using a validated scoring system for randomized and non-randomized trials.  A total of 12 studies met all inclusion criteria.  Participant numbers ranged from 5 to 130 with injury levels from C2 to T12, American Spinal Injuries Association A-D; 3 studies used over-ground RAGT systems and the remaining 9 focused on treadmill based RAGT systems.  Primary outcome measures were walking speed and walking distance.  The use of treadmill or over-ground based RAGT did not result in an increase in walking speed beyond that of conventional gait training and no studies reviewed enabled a large enough improvement to facilitate community ambulation.  The authors concluded that the use of RAGT in SCI individuals has the potential to benefit upright locomotion of SCI individuals.  Moreover, they stated that its use should not replace other therapies but be incorporated into a multi-modality rehabilitation approach.
Yozbatiran and Francisco (2019) noted that tetraplegia resulting from cervical injury is the most frequent neurologic category following SCI and causes substantial disability.  The residual strength of partially paralyzed muscles is an important determinant of independence and function in tetraplegia.  Small improvements in UE function can make a clinically significant difference in daily activities.  Major advances in rehabilitation technologies over the past 20 years have allowed testing of robotic devices in rehabilitation of motor impairments.  The authors provided an overview of robotic-assisted training research for improving arm and hand functions following cervical SCI.  They concluded that robot-assisted rehabilitation of the UE following cervical SCI is safe and feasible; but lacks sufficient evidence of clinical effectiveness.


Gandolfi and colleagues (2018) noted that bilateral arm training (BAT) has shown promise in expediting progress toward upper limb recovery in chronic stroke patients, but its neural correlates are poorly understood.  In a pilot study, these researchers evaluated changes in upper limb function and electroencephalographic (EEG) power after a robot-assisted BAT in chronic stroke patients.  In a within-subject design, 7 right-handed chronic stroke patients with upper limb paresis received 21 sessions (3 days/week) of the robot-assisted BAT.  The outcomes were changes in score on the upper limb section of the Fugl-Meyer assessment (FM), Motricity Index (MI), and Modified Ashworth Scale (MAS) evaluated at the baseline (T0), post-training (T1), and 1-month follow-up (T2).  Event-related desynchronization/synchronization were calculated in the upper alpha and the beta frequency ranges.  Significant improvement in all outcomes was measured over the course of the study.  Changes in FM were significant at T2, and in MAS at T1 and T2.  After training, desynchronization on the ipsilesional sensorimotor areas increased during passive and active movement, as compared with T0.  The authors concluded that a repetitive robotic-assisted BAT program may improve upper limb motor function and reduce spasticity in the chronically impaired paretic arm.  Effects on spasticity were associated with EEG changes over the ipsilesional sensorimotor network.  These researchers speculated that the reduction in spasticity may have facilitated EEG changes over the ipsilesional sensorimotor network.  They stated that the utility of a bilateral repetitive robot-assisted program as an adjuvant to physical therapy needs further consideration.
The authors stated that the main drawback of the present study was its small sample size (n = 7).  Moreover, the lack of homogeneity between brain lesion size and location would have precluded statistically significant results.  The event-related desynchronization (ERD; i.e., power band decrease)/event-related synchronization (ERS; i.e., power band increase) maps of the patients shown were different among themselves, and each map was also different with the control group in different ways.  The current results varied across patients and precluded to conclude.  According to these preliminary results, future studies would enroll larger sample size, and patients would be stratified according to lesion features.  It would allow discussing EEG power changes after specific robot-assisted upper limb training (i.e., active, passive, unilateral, and bilateral).  Other drawbacks were the lack of follow-up beyond 1 month and the lack of a control group receiving conventional therapy.  Moreover, control group should be age-matched, in order to compare it to a group of subjects affected by stroke.  However, since the peak frequency of the mu wave increased with age until maturation into adulthood, when it reached its final and stable frequency of 8 to 13 Hz, the age of the subjects should not significantly affect the EEG desynchronization process during movement.
Cho and associates (2018) evaluated the effects of RAGT on gait-related function in patients with acute/subacute stroke.  These researchers conducted a systematic review of RCTs published between May 2012 and April 2016.  This search included 334 articles (Cochrane, 51 articles; Embase, 175 articles; PubMed, 108 articles).  Based on the inclusion and exclusion criteria, 7 studies were selected for this review.  These investigators performed a quality evaluation using the PEDro scale.  In this review, 3 studies used an exoskeletal robot, and 4 studies used an end-effector robot as interventions.  As a result, RAGT was found to be effective in improving walking ability in subacute stroke patients.  Significant improvements in gait speed, functional ambulatory category, and Rivermead mobility index were found with RAGT compared with conventional physical therapy (p < 0.05).  The authors concluded that aggressive weight support and gait training at an early stage using a robotic device are helpful, and robotic intervention should be applied according to the patient's functional level and onset time of stroke.
The authors stated that the main drawback of this review was that it included a small number of studies (and subjects).  They stated that future review studies should include a qualitative analysis of the frequency and intensity of interventions, including more studies on subacute stroke patients.  In addition they stated that further studies are needed to demonstrate the effectiveness of RAGT according to the functional level of stroke patients in not only the subacute phase but also the chronic phase.
Dehem and associates (2018) stated that the impact of transcranial direct current stimulation (tDCS) is controversial in the neurorehabilitation literature.  It has been suggested that tDCS should be combined with other therapy to improve their efficacy.  In a randomized, controlled, double-blind, cross-over study, these researchers examined the effectiveness of a single-session of upper limb robotic-assisted therapy (RAT) combined with real or sham-tDCS in chronic stroke patients.  A total of 21 hemiparetic chronic stroke patients were included in this trial.  Participants underwent 2 sessions 7 days apart in a randomized order: 20-min of real dual-tDCS associated with RAT (REAL+RAT); and 20-min of sham dual-tDCS associated with RAT (SHAM+RAT).  Patient dexterity (Box and Block and Purdue Pegboard tests) and upper limb kinematics were evaluated before and just after each intervention.  The assistance provided by the robot during the intervention was also recorded.  Gross manual dexterity (1.8 ± 0.7 blocks, p = 0.008) and straightness of movement (0.01 ± 0.03, p < 0.05) improved slightly after REAL+RAT compared with before the intervention.  There was no improvement after SHAM+RAT.  The post-hoc analyses did not indicate any difference between interventions: REAL+RAT and SHAM+RAT (p > 0.05).  The assistance provided by the robot was similar during both interventions (p > 0.05).  The authors concluded that the results showed a slight improvement in hand dexterity and arm movement following the REAL+RAT tDCS intervention.  They noted that the observed effect after a single-session was small and not clinically relevant; repetitive sessions could increase the benefits of this combined approach.
Rodgers and colleagues (2019) noted that loss of arm function is a common problem following stroke.  Robot-assisted training might improve arm function and ADL. In a multi-center RCT, these researchers compared the effectiveness of robot-assisted training using the MIT-Manus robotic gym with an enhanced upper limb therapy (EULT) program based on repetitive functional task practice and with usual care.  This trial was carried out at 4 UK centers.  Stroke patients aged at least 18 years with moderate or severe upper limb functional limitation, between 1 week and 5 years after their 1st stroke, were randomly assigned (1:1:1) to receive robot-assisted training, EULT, or usual care.  Robot-assisted training and EULT were provided for 45 mins, thricely-weekly for 12 weeks.  Randomization was internet-based using permuted block sequences.  Treatment allocation was masked from outcome assessors but not from participants or therapists.  The primary outcome was upper limb function success (defined using the Action Research Arm Test [ARAT]) at 3 months.  Analyses were performed on an intention-to-treat (ITT) basis.  Between April 14, 2014, and April 30, 2018, a total of 770 participants were enrolled and randomly assigned to either robot-assisted training (n = 257), EULT (n = 259), or usual care (n = 254).  The primary outcome of ARAT success was achieved by 103 (44 %) of 232 patients in the robot-assisted training group, 118 (50 %) of 234 in the EULT group, and 85 (42 %) of 203 in the usual care group.  Compared with usual care, robot-assisted training (adjusted OR [aOR] 1.17 [98.3 % CI: 0.70 to 1.96]) and EULT (aOR 1.51 [0.90 to 2.51]) did not improve upper limb function; the effects of robot-assisted training did not differ from EULT (aOR 0.78 [0.48 to 1.27]).  More participants in the robot-assisted training group (39 [15 %] of 257) and EULT group (33 [13 %] of 259) had serious AEs than in the usual care group (20 [8 %] of 254), but none was attributable to the intervention.  The authors concluded that robot-assisted training and EULT did not improve upper limb function following stroke compared with usual care for patients with moderate or severe upper limb functional limitation.  These researchers stated that these findings did not support the use of robot-assisted training as provided in this trial in routine clinical practice.

Humeral Fracture

Nerz and colleagues (2017) noted that the incidence of proximal humeral fractures (PHFs) increases with age.  The functional recovery of the upper arm after such fractures is slow, and results are often disappointing.  Treatment of PHF is associated with long immobilization periods.  Evidence-based exercise guidelines are missing.  Loss of muscle mass as well as reduced ROM and motor performance are common consequences.  These losses could be partly counteracted by training interventions using robot-assisted arm support of the affected arm derived from neurorehabilitation.  Thus, shorter immobilization could be reached; however, this approach has been tested in only a few small studies.  These researchers examined if assistive robotic training augmenting conventional occupational and physical therapy can improve functional shoulder outcomes.  Patients aged between 35 and 66 years with PHF and surgical treatment will be recruited at 3 different clinics in Germany and randomized into an intervention group and a control group (n = 26 for each group).  Participants will be assessed before randomization and followed after completing an intervention period of 3 weeks and additionally after 3, 6 and 12 months.  The baseline assessment will include cognition (Short Orientation-Memory-Concentration Test); level of pain in the affected arm; ability to work; gait speed (10-m walk); disability of the arm, shoulder and hand (Disabilities of the Arm, Shoulder and Hand Outcome Measure [DASH]); ROM of the affected arm (goniometer measurement); visual acuity; and motor function of orthopedic patients (Wolf Motor Function Test–Orthopedic version [WMFT-O]).  Clinical follow-up directly after the intervention will include assessment of DASH as well as ROM and motor function (WMFT-O).  The primary outcome parameter will be the DASH, and the secondary outcome parameter will be the WMFT-O.  The long-term results will be assessed prospectively by postal follow-up.  All patients will receive conventional occupational and physical therapy.  The intervention group will receive additional robot-assisted training using the Armeo®Spring robot for 3 weeks.  The authors concluded that this study protocol describes a phase-II, randomized, controlled, single-blind, multi-center intervention study.  The results will guide and possibly improve methods of rehabilitation after proximal humeral fracture.
The authors stated that this trial/protocol have several limitations: First, the sample size is relatively small (n = 26 for each group) and powered only for a functional end-point (DASH).  Social or economic end-points such as return to work or cost-effectiveness of this intervention would require larger sample sizes and is not the purpose of this early-stage RCT.  Second, the set-up with 3 different associated centers will lead to some difficulties in the standardization of the assessments.  It is expected that different observers and therapists in the 3 institutions have subjective differences in the accomplishment of the tests.  Assessment of the WMFT will be videotaped to standardize this as much as possible.  Lastly, heterogeneous treatment modalities will also exist to some extent for rehabilitation after PHF in the conventional occupational and physical therapy in terms of duration, intensity and frequency. Theoretically, participation in the robotic group could lead to increased or decreased motivation to participate in other types of exercises. Adherence will therefore be documented.
Furthermore, UpToDate reviews on "Proximal humeral fractures in adults" (Bassett, 2018a), "Midshaft humeral fractures in adults" (Bassett , 2018b), "Proximal humeral fractures in children" (Ryan, 2018a), and "Midshaft humeral fractures in children" (Ryan, 2018b) do not mention robotic-assisted rehabilitation as a management option.

Myoelectric Elbow-Wrist-Hand Orthosis

In an observational, cohort study, Peters and colleagues (2017) determined the immediate effect of a portable, myoelectric elbow-wrist-hand orthosis (MEWHO) on paretic UE impairment in chronic, stable, moderately impaired stroke survivors (n = 18).  Participants were administered a battery of measures testing UE impairment and function.  They then donned a fabricated MEWHO and were again tested on the same battery of measures while wearing the device.  The primary outcome measure was the UE Section of the Fugl-Meyer Scale.  Subjects were also administered a battery of functional tasks and the Box and Block (BB) test.  Subjects exhibited significantly reduced UE impairment while wearing the MEWHO (FM: t17 = 8.56, p < 0.0001) and increased quality in performing all functional tasks while wearing the MEWHO, with 3 sub-tasks showing significant increases (feeding [grasp]: z = 2.251, p = 0.024; feeding [elbow]: z = 2.966, p = 0.003; drinking [grasp]: z = 3.187, p = 0.001).  Additionally, subjects showed significant decreases in time taken to grasp a cup (z = 1.286, p = 0.016) and increased gross manual dexterity while wearing a MEWHO (BB test: z = 3.42, p < 0.001).  The authors concluded that findings of this study suggested that UE impairment, as measured by the Fugl-Meyer Scale, was significantly reduced when donning a MEWHO, and these changes exceeded the Fugl-Meyer Scale's clinically important difference threshold.  Furthermore, utilization of a MEWHO significantly increased gross manual dexterity and performance of certain functional tasks.  These researchers stated that future work will integrate education sessions to increase subjects' ability to perform multi-joint functional movements and attain consistent functional changes.  The authors noted that this was the first study comparing subjects with and without a MEWHO.  Well-designed studies with large sample sizes and control groups are needed.
Dunaway and associates (2017) described the application of a commercially available, custom MEWHO, on a veteran diagnosed with chronic stroke with residual left hemiparesis.  The MEWHO provides powered active assistance for elbow flexion/extension and 3 jaw chuck grip.  It is a non-invasive orthosis that is driven by the user's EMG signal.  Experience with the MEWHO and associated outcomes were reported.  The participant completed 21 out-patient occupational therapy sessions that incorporated the use of a custom MEWHO without grasp capability into traditional occupational therapy interventions.  He then up-graded to an advanced version of that MEWHO that incorporated grasp capability and completed an additional 14 sessions.  Strength, ROM, spasticity (MAS), the BB test, the Fugl-Meyer assessment and observation of functional tasks were used to track progress.  The participant also completed a home log and a manufacturers' survey to track usage and user satisfaction over a 6-month period.  Active left UE ROM and strength increased significantly (both with and without the MEWHO) and tone decreased, demonstrating both a training and an assistive effect.  The participant also demonstrated an improved ability to incorporate his affected extremity (with the MEWHO) into a wide variety of bilateral, gross motor ADLs such as carrying a laundry basket, lifting heavy objects (e.g., a chair), using a tape measure, meal preparation, and opening doors.  The authors concluded that custom myoelectric orthoses offer an exciting opportunity for individuals diagnosed with a variety of neurological conditions to make advancements toward their recovery and independence, and warrant further research into their training effects as well as their use as assistive devices.

Myomo MyoPro

Webber et al (2021) noted that individuals with brachial plexus injuries (BPIs) can be prescribed assistive devices, including myoelectric elbow orthoses (MEOs), for rehabilitation or functional use after failed treatment for elbow flexion restoration.  Although recent case studies indicate potential for clinical improvements following the use of an MEO after BPI, patients' perspectives on such use are still unknown.  In a study using both a focus group and semi-structured interviews, these investigators examined patient perspectives on the use of an MEO following surgical treatment for a traumatic BPI.  Patients with BPI who used an MEO were recruited.  A total of 5 patients participated in an in-person focus group, whereas 3 patients participated in individual phone interviews.  Themes that emerged from the focus group were compared against those that emerged from the personal interviews.  Feedback was grouped into 3 themes: device usage, hardware performance, and device design.  Within each theme, positive elements, areas for improvement, and additional considerations emerged.  Patients indicated a positive attitude toward using an MEO as a rehabilitation tool.  They desired a streamlined, stronger device to support them and assist during activities of daily living (ADL).  The authors concluded that for patients with BPI, a well-designed MEO that meets their needs could assist with rehabilitation and increase independence in ADL.  Continued patient engagement in the evaluation and development of both medical devices and treatment plans offers the best opportunity for improved outcomes that are important to the patient.

The authors stated that this study had several drawbacks.  Although the clinic where participants were recruited is a large international center for diagnosis and treatment of BPIs, it may not represent all centers that treat BPIs; and preferences may vary geographically or culturally.  Furthermore, this study’s small sample size (n = 8) could have implications on reaching data saturation.  Although the authors confirmed the perspectives presented in the focus group with individual interviews, additional patients could be contacted for member checking.  Regardless, the themes generated by this study could help providers understand the lived experiences of individuals with BPIs.  Although this study’s cohort reflected the patient population at large (90 % male), including additional females in the study could have further presented unique perspectives that should be considered (e.g., anatomy and ADL).  In addition, while experience with the device was controlled for, daily wear time was not, possibly affecting participant views of the MEO.  Furthermore, the MEO model was not controlled for, and, as such, participants had various versions of the device; therefore, components like batteries and EMG sensors on the device varied depending on which device version was available at the time each participant was prescribed the MEO.  This may have also influenced their experiences and perspectives expressed.

Pulos et al (2021) stated that adult traumatic BPIs could result in severe impairment following penetrating wounds, falls, and motor vehicle accidents (MVAs) or other high-energy trauma.  In a retrospective study, these researchers examined functional outcomes of adult patients with a BPI using a MEO to restore elbow flexion.  A clinic specializing in the BPI treatment at a large academic medical center tested 19 adult patients with BPI.  These patients had failed to achieve anti-gravity elbow flexion following their injury and observation or surgical reconstruction.  They were provided a MEO if they had detectable EMG signals.  There was significant improvement in strength and significant reductions in function and pain when using an MEO.  Following initiation of the MEO, 12 of the 19 patients had clinical improvements in muscle strength, 15 patients showed improvement in their DASH, and 13 patients reported improvements in their VAS.  The authors concluded that the use of an MEO improved elbow flexion strength, increased function, and reduced pain in the majority of patients with BPI and inadequate elbow flexion following observation or surgical reconstruction.

These researchers stated that they recognized the drawbacks inherent in this retrospective study.  Given the heterogeneity of this injury, time from injury to being seen in the clinic, and patient factors, studies in patients with adult traumatic BPI can be difficult to interpret.  For example, free-functioning muscle transfers have out-performed nerve transfers for restoration of elbow flexion strength in patients with complete BPIs and patients with free-functioning muscle transfers were provided an MEO earlier than those with nerve transfers in this trial.  There may be a potential selection bias in who was able to obtain a MEO secondary to socio-economic factors that were not examined in this study; however, the indications for application of the MEO were clearly defined.  Finally, the objective of the study was to determine the applicability of a MEO for elbow flexion in patients with BPI and not to evaluate the cost and availability of the MEO.

Constantino et al (2022) stated that robot-assisted therapy is an innovative approach to upper-limb rehabilitation that uses intensive, repetitive, interactive, and individualized practice as an optimal strategy to enhance motor learning.  An example of upper-limb robot-assisted therapy is the myoelectric orthosis MyoPro.  It is a custom-fabricated myoelectric elbow-wrist-hand orthosis (MEWHO) with built-in surface sensors that detect the user's EMG signals during muscle contraction.  Studies on the MEWHO have focused mostly on elderly chronic stroke patients; none had discussed its use on the adolescent population and the considerations they face in wearing the orthosis.  A 15-year-old male 10th-grade student with a diagnosis of right spastic hemiplegia secondary to CP was prescribed a MEWHO because of muscle weakness of his right upper extremity, decreased functional status, and fine motor skills deficits.  After 2 occupational therapy (OT) cycles, the patient demonstrated improvements in functional strength and performance of physical activities.  Despite these improvements, the patient only used the MEWHO during therapy and was less engaged with its use at home and school.  The authors concluded that this case report presented insights on why the patient was not as proficient and interested in using the orthosis at home and school.  Recommendations to address these issues included peer modeling, community outings, early intervention, and the use of family-centered approaches.  These researchers stated that future studies are also suggested to further understand MEWHO use and the considerations for successful orthotic management in this group of patients.

Pundik et al (2022) noted that technologies that enhance motor learning-based therapy and are clinically deployable may improve outcome for those with neurological deficits.  The MyoPro is a customized myoelectric upper extremity orthosis that employs volitionally generated weak EMG signals from paretic muscles to assist movement of an impaired arm.  In a pilot study, these researchers examined the use of MyoPro as a tool for motor learning-based therapy for individuals with chronic upper limb weakness.  This trial included 13 individuals with chronic moderate/severe arm weakness due to either stroke (n = 7) or TBI (n = 6) who participated in a single group interventional study consisting of 2 phases.  The in-clinic phase included 18 sessions (2 times per week, 27 hours of face-to-face therapy) plus a home exercise program.  The home phase included practice of the home exercise program.  The study did not include a control group.  Outcomes were collected at baseline and at weeks 3, 5, 7, 9, 12, 15, and 18.  Statistics included mixed model regression analysis.  Statistically significant and clinically meaningful improvements were observed on Fugl-Meyer (+ 7.5 points).  Gains were observed at week 3, increased further through the in-clinic phase and were maintained during the home phase.  Statistically significant changes in Modified Ashworth Scale, ROM, and Chedoke Arm and Hand Activity Inventory were observed early during the in-clinic phase.  Orthotic and Prosthetic User's Survey demonstrated satisfaction with the device throughout study participation.  Both stroke and TBI participants responded to the intervention.  The authors concluded that the use of MyoPro in motor learning-based therapy resulted in clinically significant gains with a relatively short duration of in-person treatment.  Moreover, these investigators stated that further studies using a randomized, controlled design are needed.

These researchers stated that while the results are encouraging, this study had several drawbacks.  The sample size was small (n = 13), no blinding was employed, and no comparison group was included.  This curtailed generalization of the results.  However, these investigators observed changes across impairment and function that deserve further study with a more rigorously controlled study design.  In addition, this was a cohort of mixed diagnoses and heterogenous in terms of level of impairment.


The above policy is based on the following references:

  1. Ahmadi Bani M, Arazpour M, Farahmand F, et al. The efficiency of mechanical orthoses in affecting parameters associated with daily living in spinal cord injury patients: A literature review. Disabil Rehabil Assist Technol. 2015;10(3):183-190.
  2. Alcobendas-Maestro M, Esclarín-Ruz A, Casado-Lopez RM, et al. Lokomat robotic-assisted versus overground training within 3 to 6 months of incomplete spinal cord lesion: Randomized controlled trial. Neurorehabil Neural Repair. 2012;26(9):1058-1063.
  3. Arazpour M, Ahmadi Bani M, Hutchins SW, et al. Influence of orthotic gait training with powered hip orthosis on walking in paraplegic patients. Disabil Rehabil Assist Technol. 2014;9(3):226-230.
  4. Arazpour M, Chitsazan A, Hutchins SW, et al. Evaluation of a novel powered hip orthosis for walking by a spinal cord injury patient: A single case study. Prosthet Orthot Int. 2012;36:105-112.
  5. Arazpour M, Hutchins SW, Ahmadi Bani M. The efficacy of powered orthoses on walking in persons with paraplegia. Prosthet Orthot Int. 2015;39(2):90-99.
  6. Arazpour M, Samadian M, Ebrahimzadeh K, et al. The influence of orthosis options on walking parameters in spinal cord-injured patients: A literature review. Spinal Cord. 2016;54(6):412-422.
  7. Baniqued PDE, Stanyer EC, Awais M, et al. Brain-computer interface robotics for hand rehabilitation after stroke: A systematic review. J Neuroeng Rehabil. 2021;18(1):15.
  8. Bassett R. Midshaft humeral fractures in adults. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed June 2018b.
  9. Bassett R. Proximal humeral fractures in adults. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed June 2018a.
  10. Bedigrew KM, Patzkowski JC, Wilken JM, et al. Can an integrated orthotic and rehabilitation program decrease pain and improve function after lower extremity trauma? Clin Orthop Relat Res. 2014;472(10):3017-3025.
  11. Borboni A, Villafañe JH, Mullè C, et al. Robot-assisted rehabilitation of hand paralysis after stroke reduces wrist edema and pain: A prospective clinical trial. J Manipulative Physiol Ther. 2017;40(1):21-30.
  12. Brewer BR, McDowell SK, Worthen-Chaudhari LC. Poststroke upper extremity rehabilitation: A review of robotic systems and clinical results. Top Stroke Rehabil. 2007;14(6):22-44.
  13. Centre for Reviews and Dissemination (CRD). Effects of robot-assisted therapy on upper limb recovery after stroke: A systematic review. Database of Abstracts of Reviews of Effectiveness (DARE). York, UK: University of York; 2009.
  14. Chang JJ, Tung WL, Wu WL, et al. Effects of robot-aided bilateral force-induced isokinetic arm training combined with conventional rehabilitation on arm motor function in patients with chronic stroke. Arch Phys Med Rehabil. 2007;88(10):1332-1338.
  15. Cheung EY, Ng TK, Yu KK, et al. Robot-assisted training for people with spinal cord injury: A meta-analysis. Arch Phys Med Rehabil. 2017;98(11):2320-2331.
  16. Cho JE, Yoo JS, Kim KE, et al. Systematic review of appropriate robotic intervention for gait function in subacute stroke patients. Biomed Res Int. 2018;2018:4085298.
  17. Constantino C, May E, Flanagan A, et al. Myoelectric elbow-wrist-hand orthosis for an adolescent with hemiparesis: A case report. J Prosthetics Orthotics. 2022;34(2):e99-e102.
  18. Dehem S, Gilliaux M, Lejeune T, et al. Effectiveness of a single session of dual-transcranial direct current stimulation in combination with upper limb robotic-assisted rehabilitation in chronic stroke patients: A randomized, double-blind, cross-over study. Int J Rehabil Res. 2018;41(2):138-145.
  19. Dierick F, Dehas M, Isambert JL, et al. Hemorrhagic versus ischemic stroke: Who can best benefit from blended conventional physiotherapy with robotic-assisted gait therapy? PLoS One. 2017;12(6):e0178636.
  20. Dobkin BH, Duncan PW. Should body weight-supported treadmill training and robotic-assistive steppers for locomotor training trot back to the starting gate? Neurorehabil Neural Repair. 2012;26(4):308-317.
  21. Druzbicki M, Rusek W, Snela S, et al. Functional effects of robotic-assisted locomotor treadmill thearapy in children with cerebral palsy. J Rehabil Med. 2013;45(4):358-363.
  22. Dunaway S, Dezsi DB, Perkins J, et al. Case report on the use of a custom myoelectric elbow-wrist-hand orthosis for the remediation of upper extremity paresis and loss of function in chronic stroke. Mil Med. 2017;182(7):e1963-e1968.
  23. Esquenazi A, Lee S, Packel AT, Braitman L. A randomized comparative study of manually assisted versus robotic-assisted body weight supported treadmill training in persons with a traumatic brain injury. PMR. 2013;5(4):280-290.
  24. Fasoli SE, Krebs HI, Stein J, et al. Effects of robotic therapy on motor impairment and recovery in chronic stroke. Arch Phys Med Rehabil. 2003;84(4):477-482.
  25. Fernandez-Garcia C, Ternent L, Homer TM, et al. Economic evaluation of robot-assisted training versus an enhanced upper limb therapy programme or usual care for patients with moderate or severe upper limb functional limitation due to stroke: Results from the RATULS randomised controlled trial. BMJ Open. 2021;11(5):e042081.
  26. Gandolfi M, Formaggio E, Geroin C, et al. Quantification of upper limb motor recovery and EEG power changes after robot-assisted bilateral arm training in chronic stroke patients: A prospective pilot study. Neural Plast. 2018;2018:8105480.
  27. Gandolfi M, Geroin C, Picelli A, et al. Robot-assisted vs. sensory integration training in treating gait and balance dysfunctions in patients with multiple sclerosis: A randomized controlled trial. Front Hum Neurosci. 2014;8:318.
  28. Goetz G, Walter M, Wohlhöfner K, et al. Robotics and functional electrical stimulation for stroke rehabilitation. AIHTA Project report No.128. Vienna, Austria: HTA Austria – Austrian Institute for Health Technology Assessment GmbH; April 2021.
  29. Hayes SC, James Wilcox CR, Forbes White HS, Vanicek N. The effects of robot assisted gait training on temporal-spatial characteristics of people with spinal cord injuries: A systematic review. J Spinal Cord Med. 2018;41(5):529-543.
  30. Hayward K, Barker R, Brauer S. Interventions to promote upper limb recovery in stroke survivors with severe paresis: A systematic review. Disabil Rehabil. 2010;32(24):1973-1986.
  31. Hesse S, Schmidt H, Werner C, et al. Upper and lower extremity robotic devices for rehabilitation and for studying motor control. Curr Opin Neurol. 2003;16(6):705-710.
  32. Hidler J, Nichols D, Pelliccio M, et al. Multicenter randomized clinical trial evaluating the effectiveness of the Lokomat in subacute stroke. Neurorehabil Neural Repair. 2009;23(1):5-13.
  33. Hornby TG, Campbell DD, Kahn JH, et al. Enhanced gait-related improvements after therapist- versus robotic-assisted locomotor training in subjects with chronic stroke: A randomized controlled study. Stroke. 2008;39(6):1786-1792.
  34. Hussain S, Xie SQ, Liu G. Robot assisted treadmill training: Mechanisms and training strategies. Med Eng Phys. 2011;33(5):527-533.
  35. Kahn LE, Lum PS, Rymer WZ, Reinkensmeyer DJ. Robot-assisted movement training for the stroke-impaired arm: Does it matter what the robot does? J Rehabil Res Dev. 2006(b);43(5):619-30.
  36. Kahn LE, Zygman ML, Rymer WZ, Reinkensmeyer DJ. Robot-assisted reaching exercise promotes arm movement recovery in chronic hemiparetic stroke: A randomized controlled pilot study. J Neuroeng Rehabil. 2006(a);3:12.
  37. Krebs HI, Mernoff S, Fasoli SE, et al. A comparison of functional and impairment-based robotic training in severe to moderate chronic stroke: A pilot study. NeuroRehabilitation. 2008;23(1):81-87.
  38. Kutner NG, Zhang R, Butler AJ, et al. Quality-of-life change associated with robotic-assisted therapy to improve hand motor function in patients with subacute stroke: A randomized clinical trial. Phys Ther. 2010;90(4):493-504.
  39. Kwakkel G, Kollen B. Predicting improvement in the upper paretic limb after stroke: A longitudinal prospective study. Restor Neurol Neurosci. 2007;25(5-6):453-60.
  40. Kwakkel G, Kollen BJ, Krebs HI. Effects of robot-assisted therapy on upper limb recovery after stroke: A systematic review. Neurorehabil Neural Repair. 2008;22(2):111-121.
  41. Lefmann S, Russo R, Hillier S. The effectiveness of robotic-assisted gait training for paediatric gait disorders: Systematic review. J Neuroeng Rehabil. 2017;14(1):1.
  42. Lewek MD, Cruz TH, Moore JL, et al. Allowing intralimb kinematic variability during locomotor training poststroke improves kinematic consistency: A subgroup analysis from a randomized clinical trial. Phys Ther. 2009;89(8):829-839.
  43. Lloyd-Jones D, Adams R, Carnethon M, et al; American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Heart disease and stroke statistics -- 2009 update. A report from the American Heart Association Statistics Committee and Stroke Statistics Subcommittee. Circulation. 2009;119(3):e21-e181.
  44. Lum PS, Burgar CG, Shor PC, et al. Robot-assisted movement training compared with conventional therapy techniques for the rehabilitation of upper-limb motor function after stroke. Arch Phys Med Rehabil. 2002;83(7):952-959.
  45. Management of Stroke Rehabilitation Working Group. Management of stroke rehabilitation. VA/DOD Clinical Practice Guideline. VA/DOD Evidence Based Practice. Version 2.0, 2010. Washington, DC: Veterans Health Administration, Department of Defense; 2010.
  46. Masiero S, Celia A, Rosati G, et al. Robotic-assisted rehabilitation of the upper limb after acute stroke. Arch Phys Med Rehabil. 2007;88(2):142-149.
  47. Mehrholz J, Elsner B, Werner C, et al. Electromechanical-assisted training for walking after stroke. Cochrane Database Syst Rev. 2013;7:CD006185.
  48. Mehrholz J, Hädrich A, Platz T, et al. Electromechanical and robot-assisted arm training for improving generic activities of daily living, arm function, and arm muscle strength after stroke. Cochrane Database Syst Rev. 2012;6:CD006876.
  49. Mehrholz J, Harvey LA, Thomas S, Elsner B. Is body-weight-supported treadmill training or robotic-assisted gait training superior to overground gait training and other forms of physiotherapy in people with spinal cord injury? A systematic review. Spinal Cord. 2017;55(8):722-729.
  50. Mehrholz J, Kugler J, Pohl M. Locomotor training for walking after spinal cord injury. Cochrane Database Syst Rev. 2008;(2):CD006676.
  51. Mehrholz J, Platz T, Kugler J, Pohl M. Electromechanical and robot-assisted arm training for improving arm function and activities of daily living after stroke. Cochrane Database of Syst Rev. 2008;(4):CD006876.
  52. Meyer-Heim A, Ammann-Reiffer C, Schmartz A, et al. Improvement of walking abilities after robotic-assisted locomotion training in children with cerebral palsy. Arch Dis Child. 2009;94(8):615-620.
  53. Meyer-Heim A, Borggraefe I, Ammann-Reiffer C, et al. Feasibility of robotic-assisted locomotor training in children with central gait impairment. Dev Med Child Neurol. 2007;49(12):900-906.
  54. Morawietz C, Moffat F. Effects of locomotor training after incomplete spinal cord injury: A systematic review. Arch Phys Med Rehabil. 2013;94(11):2297-2308.
  55. Morone G, Annicchiarico R, Iosa M, et al. Overground walking training with the i-Walker, a robotic servo-assistive device, enhances balance in patients with subacute stroke: A randomized controlled trial. J Neuroeng Rehabil. 2016;13(1):47.
  56. Morone G, Palomba A, Cinnera AM, et al. Systematic review of guidelines to identify recommendations for upper limb robotic rehabilitation after stroke. Eur J Phys Rehabil Med. 2021;57(2):238-245.
  57. Myomo, Inc. Myomo Therapy [website]. Boston, MA; Myomo; 2008. Available at: Accessed January 5, 2009.
  58. Naziri Q, Mixa PJ, Murray DP, et al. Robotic-assisted and computer-navigated unicompartmental knee arthroplasties: A systematic review. Surg Technol Int. 2018;32:271-278.
  59. Nerz C, Schwickert L, Becker C, et al. Effectiveness of robot-assisted training added to conventional rehabilitation in patients with humeral fracture early after surgical treatment: Protocol of a randomised, controlled, multicentre trial. Trials. 2017;18:589.
  60. No authors listed. MyoPro 25920. GUDID 00855846007092. FDA report. 2022. Available at: Accesed September 13, 2022.
  61. Norouzi-Gheidari N, Archambault PS, Fung J. Effects of robot-assisted therapy on stroke rehabilitation in upper limbs: Systematic review and meta-analysis of the literature. J Rehabil Res Dev. 2012;49(4):479-496.
  62. Park JH, Shin YI, You JSH, Park MS. Comparative effects of robotic-assisted gait training combined with conventional physical therapy on paretic hip joint stiffness and kinematics between subacute and chronic hemiparetic stroke. NeuroRehabilitation. 2018;42(2):181-190.
  63. Peters HT, Page SJ, Persch A. Giving them a hand: Wearing a myoelectric elbow-wrist-hand orthosis reduces upper extremity impairment in chronic stroke. Arch Phys Med Rehabil. 2017;98(9):1821-1827.
  64. Picelli A, Melotti C, Origano F, et al. Robot-assisted gait training in patients with Parkinson disease: A randomized controlled trial. Neurorehabil Neural Repair. 2012;26(4):353-361.
  65. Picelli A, Melotti C, Origano F, et al. Robot-assisted gait training is not superior to balance training for improving postural instability in patients with mild to moderate Parkinson's disease: A single-blind randomized controlled trial. Clin Rehabil. 2015;29(4):339-347.
  66. Pirondini E, Coscia M, Marcheschi S, et al. Evaluation of the effects of the Arm Light Exoskeleton on movement execution and muscle activities: A pilot study on healthy subjects. J Neuroeng Rehabil. 2016;13:9.
  67. Prange GB, Jannink MJ, Groothuis-Oudshoorn CG, et al. Systematic review of the effect of robot-aided therapy on recovery of the hemiparetic arm after stroke. J Rehabil Res Dev. 2006;43(2):171-184.
  68. Pulos N, van den Berg C, Kaufman KR, Shin AY. Application of myoelectric elbow flexion assist orthosis in adult traumatic brachial plexus injury: A retrospective clinical study. Prosthet Orthot Int. 2021;45(6):521-525.
  69. Pundik S, McCabe J, Skelly M, e tal. Myoelectric arm orthosis in motor learning-based therapy for chronic deficits after stroke and traumatic brain injury. Front Neurol. 2022;13:791144.
  70. Rahman T, Sample W, Seliktar R, et al. Design and testing of a functional arm orthosis in patients with neuromuscular diseases. IEEE Trans Neural Syst Rehabil Eng. 2007;15(2):244-251.
  71. Reis SB, Bernardo WM, Oshiro CA, et al. Effects of robotic therapy associated with noninvasive brain stimulation on upper-limb rehabilitation after stroke: systematic review and meta-analysis of randomized clinical trials. Neurorehabil Neural Repair. 2021;35(3):256-266.
  72. Riener R. Robot-aided rehabilitation of neural function in the upper extremities. Acta Neurochir Suppl. 2007;97(Pt 1):465-471.
  73. Rodgers H, Bosomworth H, Krebs HI, et al. Robot assisted training for the upper limb after stroke (RATULS): A multicentre randomised controlled trial. Lancet. 2019;394(10192):51-62. 
  74. Rodgers H, Bosomworth H, Krebs HI, et al. Robot-assisted training compared with an enhanced upper limb therapy programme and with usual care for upper limb functional limitation after stroke: The RATULS three-group RCT. Health Technol Assess. 2020;24(54):1-232.
  75. Russell Esposito E, Blanck RV, Harper NG, et al. How does ankle-foot orthosis stiffness affect gait in patients with lower limb salvage? Clin Orthop Relat Res. 2014;472(10):3026-3035.
  76. Ryan LM. Midshaft humeral fractures in children. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed June 2018b.
  77. Ryan LM. Proximal humeral fractures in children. UpToDate [online serial]. Waltham, MA: UpToDate; reviewed June 2018a.
  78. Sacco K, Cauda F, D’Agata F, et al. A combined robotic and cognitive training for locomotor rehabilitation: Evidences of cerebral functional reorganization in two chronic traumatic brain injured patients. Front Hum Neurosci. 2011;5:146.
  79. Schwartz I, Sajin A, Fisher I, et al. The effectiveness of locomotor therapy using robotic-assisted gait training in subacute stroke patients: A randomized controlled trial. PM R. 2009;1(6):516-523.
  80. Schwartz I, Sajina A, Neeb M, et al. Locomotor training using a robotic device in patients with subacute spinal cord injury. Spinal Cord. 2011;49(10):1062-1067.
  81. Singh H, Unger J, Zariffa J, et al. Robot-assisted upper extremity rehabilitation for cervical spinal cord injuries: A systematic scoping review. Disabil Rehabil Assist Technol. 2018;13(7):704-715.
  82. Stein J, Bishop L, Gillen G, Helbok R. Robot-assisted exercise for hand weakness after stroke: A pilot study. Am J Phys Med Rehabil. 2011;90(11):887-894.
  83. Stein J, Narendran K, McBean J, et al. Electromyography-controlled exoskeletal upper-limb-powered orthosis for exercise training after stroke. Am J Phys Med Rehabil. 2007;86(4):255-261.
  84. Stein J. e100 NeuroRobotic system. Expert Rev Med Devices. 2009;6(1):15-19.
  85. Swinnen E, Duerinck S, Baeyens JP, et al. Effectiveness of robot-assisted gait training in persons with spinal cord injury: A systematic review. J Rehabil Med. 2010;42(6):520-526.
  86. Takahashi K, Domen K, Sakamoto T, et al. Efficacy of upper extremity robotic therapy in subacute poststroke hemiplegia: An exploratory randomized trial. Stroke. 2016;47(5):1385-1388.
  87. Taveggia G, Borboni A, Salvi L, et al. Efficacy of robot-assisted rehabilitation to functional recovery upper limb in post stroke patients: A randomized controlled study. Eur J Phys Rehabil Med. 2016;52(6):767-773.
  88. Tefertiller C, Pharo B, Evans N, Winchester P. Efficacy of rehabilitation robotics for walking training in neurological disorders: A review. J Rehabil Res Dev. 2011;48(4):387-416.
  89. U.S. Food and Drug Administration (FDA). Myomo e100. Summary of Safety and Effectiveness. 510(k) No. K062631. Rockville, MD: FDA; April 12, 2007.
  90. Vaney C, Gattlen B, Lugon-Moulin V, et al. Robotic-assisted step training (lokomat) not superior to equal intensity of over-ground rehabilitation in patients with multiple sclerosis. Neurorehabil Neural Repair. 2012;26(3):212-221.
  91. Velez-Guerrero MA, Callejas-Cuervo M, Mazzoleni S. Artificial intelligence-based wearable robotic exoskeletons for upper limb rehabilitation: A review. Sensors (Basel). 2021;21(6):2146.
  92. Verbunt JA, Seelen HA, Ramos FP, et al. Mental practice-based rehabilitation training to improve arm function and daily activity performance in stroke patients: A randomized clinical trial. BMC Neurol. 2008;8:7.
  93. Volpe BT, Krebs HI, Hogan N. Robot-aided sensorimotor training in stroke rehabilitation. Adv Neurol. 2003;92:429-33.
  94. Webber CM, Egginton JS, Shin AY, Kaufman KR. Application of a myoelectric elbow flexion assist orthosis in adult traumatic brachial plexus injury: Patient perspectives. Prosthet Orthot Int. 2021;45(6):526-531.
  95. Wolf SL, Sahu K, Bay RC, et al. The HAAPI (Home Arm Assistance Progression Initiative) Trial: A novel robotics delivery approach in stroke rehabilitation. Neurorehabil Neural Repair. 2015;29(10):958-968.
  96. Yang JK, Ahn NE, Kim DH, Kim DY. Plantar pressure distribution during robotic-assisted gait in post-stroke hemiplegic patients. Ann Rehabil Med. 2014;38(2):145-152.
  97. Yozbatiran N, Francisco GE. Robot-assisted therapy for the upper limb after cervical spinal cord injury. Phys Med Rehabil Clin N Am. 2019;30(2):367-384.
  98. Zariffa J, Kapadia N, Kramer JL, et al. Feasibility and efficacy of upper limb robotic rehabilitation in a subacute cervical spinal cord injury population. Spinal Cord. 2012;50(3):220-226.