Effects of robotic therapy of the arm after stroke

Quantifying Quality of Reaching Movements Longitudinally Post-Stroke: A Systematic Review

Background

Disambiguation of behavioral restitution from compensation is important to better understand recovery of upper limb motor control post-stroke and subsequently design better interventions. Measuring quality of movement (QoM) during standardized performance assays and functional tasks using kinematic and kinetic metrics potentially allows for this disambiguation.

Objectives

To identify longitudinal studies that used kinematic and/or kinetic metrics to investigate post-stroke recovery of reaching and assess whether these studies distinguish behavioral restitution from compensation.

Methods

A systematic literature search was conducted using the databases PubMed, Embase, Scopus, and Wiley/Cochrane Library up to July 1st, 2020. Studies were identified if they performed longitudinal kinematic and/or kinetic measurements during reaching, starting within the first 6 months post-stroke.

Results

Thirty-two longitudinal studies were identified, which reported a total of forty-six different kinematic metrics. Although the majority investigated improvements in kinetics or kinematics to quantify recovery of QoM, none of these studies explicitly addressed the distinction between behavioral restitution and compensation. One study obtained kinematic metrics for both performance assays and a functional task.

Conclusions

Despite the growing number of kinematic and kinetic studies on post-stroke recovery, longitudinal studies that explicitly seek to delineate between behavioral restitution and compensation are still lacking in the literature. To rectify this situation, future studies should measure kinematics and/or kinetics during performance assays to isolate restitution and during a standardized functional task to determine the contributions of restitution and compensation.

Effects of arm weight support on neuromuscular activation during reaching in chronic stroke patients

To better understand how arm weight support (WS) can be used to alleviate upper limb impairment after stroke, we investigated the effects of WS on muscle activity, muscle synergy expression, and corticomotor excitability (CME) in 13 chronic stroke patients and 6 age-similar healthy controls. For patients, lesion location and corticospinal tract integrity were assessed using magnetic resonance imaging. Upper limb impairment was assessed using the Fugl-Meyer upper extremity assessment with patients categorised as either mild or moderate-severe. Three levels of WS were examined: low = 0, medium = 50 and high = 100% of full support. Surface EMG was recorded from 8 upper limb muscles, and muscle synergies were decomposed using non-negative matrix factorisation from data obtained during reaching movements to an array of 14 targets using the paretic or dominant arm. Interactions between impairment level and WS were found for the number of targets hit, and EMG measures. Overall, greater WS resulted in lower EMG levels, although the degree of modulation between WS levels was less for patients with moderate-severe compared to mild impairment. Healthy controls expressed more synergies than patients with moderate-severe impairment. Healthy controls and patients with mild impairment showed more synergies with high compared to low weight support. Transcranial magnetic stimulation was used to elicit motor-evoked potentials (MEPs) to which stimulus-response curves were fitted as a measure of corticomotor excitability (CME). The effect of WS on CME varied between muscles and across impairment level. These preliminary findings demonstrate that WS has direct and indirect effects on muscle activity, synergies, and CME and warrants further study in order to reduce upper limb impairment after stroke.

Upper limb robot-assisted rehabilitation versus physical therapy on subacute stroke patients: A follow-up study

This study aims to analyse the long-term effects (6 months follow-up) of upper limb Robot-assisted Therapy (RT) compared to Traditional physical Therapy (TT), in subacute stroke patients. Although the literature on upper-limb rehabilitation with robots shows increasing evidence of its effectiveness in stroke survivors, the length of time for which the re-learned motor abilities could be maintained is still understudied. A randomized controlled follow-up study was conducted on 48 subacute stroke patients who performed the upper-limb therapy using a planar end-effector robotic system (Experimental Group-EG) or TT (Control Group-CG). The clinical assessments were collected at T0 (baseline), T1 (end of treatment) and T2 (6 months follow-up): Upper Limb part of Fugl-Meyer assessment (FM-UL), total passive Range Of Motion (pROM), Modified Ashworth Scale Shoulder (MAS-S) and Elbow (MAS-E). At T1, the intra-group analysis showed significant gain of FM-UL in both EG and CG, while significant improvement in MAS-S, MAS-E, and pROM were found in the EG only. At T2, significant increase in MAS-S were revealed only in the CG. In FM-UL, pROM and MAS-E the improvements obtained at the end of treatment seem to be maintained at 6 months follow-up in both groups. The inter-groups analysis of FM-UL values at T1 and T2 demonstrated significant differences in favour of EG. In conclusion, upper limb Robot-assisted Therapy may lead a greater reduction of motor impairment in subacute stroke patients compared to Traditional Therapy. The gains observed at the end of treatment persisted over time. No serious adverse events related to the study occurred.

Robot-Assisted Reach Training With an Active Assistant Protocol for Long-Term Upper Extremity Impairment Poststroke: A Randomized Controlled Trial

OBJECTIVE

To assess whether robot-assisted reach training (RART) with an active assistant protocol can improve upper extremity function and kinematic performance in chronic stroke survivors.

DESIGN

This study was conducted as a randomized controlled trial.

SETTING

National rehabilitation center.

PARTICIPANTS

Chronic stroke survivors (N=38) were randomized into 2 groups: a robot-assisted reach training with assist-as-needed (RT-AAN) group and a robot-assisted reach training with guidance force (RT-G) group.

INTERVENTION

The RT-AAN group received robot-assisted reach training with an assist-as-needed mode for 40 minutes per day, 3 times per week over a 6-week period, and the RT-G group participated in the RART with a guidance mode for 40 minutes per day, 3 times per week over a 6-week period.

MAIN OUTCOME MEASURES

Upper extremity functions were measured with Fugl-Meyer Assessment (FMA), Action Research Arm Test (ARAT), and Box and Block Test. In addition, movement velocities were measured as an index for upper extremity kinematic performances in 6 directions.

RESULTS

Both groups showed significant improvements in FMA, ARAT, and kinematics (movement velocity) in all directions (targets 1-6, P<.05). However, the RT-AAN group showed significantly more improvement than the RT-G group in FMA and ARAT (P<.05).

CONCLUSIONS

RART with an active assistant protocol showed improvements of upper extremity function and kinematic performance in chronic stroke survivors. In particular, assist-as-needed robot control was effective for upper extremity rehabilitation. Therefore robot-assisted training may be suggested as an effective intervention to improve upper extremity function in chronic stroke survivors.

Upper limb robotic rehabilitation for chronic stroke survivors: a single-group preliminary study

[Purpose] This study aimed to assess whether robotic rehabilitation can improve upper limb function, activities of daily living performance, and kinematic performance of chronic stroke survivors. [Subjects and Methods] Participants were 21 chronic stroke survivors (19 men; 60.8 years; Mini-Mental State Examination score: 28; onset duration: 10.2 years). Training exercises were performed with a Whole Arm Manipulator and a 120-inch projective display to provide visual and auditory feedback. Once the training began, red and grey balls appeared on the projective display, and participants performed reaching movements, in the assist-as-needed mode, toward 6 directional targets in a 3-dimensional space. All participants received training for 40 minutes per day, thrice per week, for 6 weeks. Main outcome measures were upper limb function (Fugl-Meyer Assessment, Action Research Arm Test, and Box and Blocks Test scores), activities of daily living performance (Modified Barthel Index), and kinematic performance (movement velocity) in 6 directions. [Results] After 6 weeks, significant improvement was observed in upper limb function, activities of daily living performance, and kinematic performance. [Conclusion] This study demonstrated the positive effects of robotic rehabilitation on upper limb function, activities of daily living performance, and kinematic performance in chronic stroke survivors.

Closed-Loop Task Difficulty Adaptation during Virtual Reality Reach-to-Grasp Training Assisted with an Exoskeleton for Stroke Rehabilitation

Stroke patients with severe motor deficits of the upper extremity may practice rehabilitation exercises with the assistance of a multi-joint exoskeleton. Although this technology enables intensive task-oriented training, it may also lead to slacking when the assistance is too supportive. Preserving the engagement of the patients while providing “assistance-as-needed” during the exercises, therefore remains an ongoing challenge. We applied a commercially available seven degree-of-freedom arm exoskeleton to provide passive gravity compensation during task-oriented training in a virtual environment. During this 4-week pilot study, five severely affected chronic stroke patients performed reach-to-grasp exercises resembling activities of daily living. The subjects received virtual reality feedback from their three-dimensional movements. The level of difficulty for the exercise was adjusted by a performance-dependent real-time adaptation algorithm. The goal of this algorithm was the automated improvement of the range of motion. In the course of 20 training and feedback sessions, this unsupervised adaptive training concept led to a progressive increase of the virtual training space (p < 0.001) in accordance with the subjects' abilities. This learning curve was paralleled by a concurrent improvement of real world kinematic parameters, i.e., range of motion (p = 0.008), accuracy of movement (p = 0.01), and movement velocity (p < 0.001). Notably, these kinematic gains were paralleled by motor improvements such as increased elbow movement (p = 0.001), grip force (p < 0.001), and upper extremity Fugl-Meyer-Assessment score from 14.3 ± 5 to 16.9 ± 6.1 (p = 0.026). Combining gravity-compensating assistance with adaptive closed-loop feedback in virtual reality provides customized rehabilitation environments for severely affected stroke patients. This approach may facilitate motor learning by progressively challenging the subject in accordance with the individual capacity for functional restoration. It might be necessary to apply concurrent restorative interventions to translate these improvements into relevant functional gains of severely motor impaired patients in activities of daily living.

Robot-assisted and conventional therapies produce distinct rehabilitative trends in stroke survivors

Background

Comparing the efficacy of alternative therapeutic strategies for the rehabilitation of motor function in chronically impaired individuals is often inconclusive. For example, a recent randomized clinical trial (RCT) compared robot-assisted vs. conventional therapy in 77 patients who had had chronic motor impairment after a cerebrovascular accident. While patients assigned to robotic therapy had greater improvements in the primary outcome measure (change in score on the upper extremity section of the Fugl-Meyer assessment), the absolute difference between therapies was small, which left the clinical relevance in question.

Methods

Here we revisit that study to test whether the multidimensional rehabilitative response of these patients can better distinguish between treatment outcomes. We used principal components analysis to find the correlation of changes across seven outcome measures between the start and end of 8 weeks of therapy. Permutation tests verified the robustness of the principal components found.

Results

Each therapy in fact produces different rehabilitative trends of recovery across the clinical, functional, and quality of life domains. A rehabilitative trend is a principal component that quantifies the correlations among changes in outcomes with each therapy.

Conclusions

These findings challenge the traditional emphasis of RCTs on using a single primary outcome measure to compare rehabilitative responses that are naturally multidimensional. This alternative approach to, and interpretation of, the results of RCTs may will lead to more effective therapies targeted for the multidimensional mechanisms of recovery.

Trial registration

ClinicalTrials.gov number NCT00719433. Registered July 17, 2008.

Electronic supplementary material

The online version of this article (doi:10.1186/s12984-016-0199-5) contains supplementary material, which is available to authorized users.

Effects of Robot-Assisted Therapy for the Upper Limb After Stroke

BACKGROUND

Robot technology for poststroke rehabilitation is developing rapidly. A number of new randomized controlled trials (RCTs) have investigated the effects of robot-assisted therapy for the paretic upper limb (RT-UL).

OBJECTIVE

To systematically review the effects of poststroke RT-UL on measures of motor control of the paretic arm, muscle strength and tone, upper limb capacity, and basic activities of daily living (ADL) in comparison with nonrobotic treatment.

METHODS

Relevant RCTs were identified in electronic searches. Meta-analyses were performed for measures of motor control (eg, Fugl-Meyer Assessment of the arm; FMA arm), muscle strength and tone, upper limb capacity, and basic ADL. Subgroup analyses were applied for the number of joints involved, robot type, timing poststroke, and treatment contrast.

RESULTS

Forty-four RCTs (N = 1362) were included. No serious adverse events were reported. Meta-analyses of 38 trials (N = 1206) showed significant but small improvements in motor control (~2 points FMA arm) and muscle strength of the paretic arm and a negative effect on muscle tone. No effects were found for upper limb capacity and basic ADL. Shoulder/elbow robotics showed small but significant effects on motor control and muscle strength, while elbow/wrist robotics had small but significant effects on motor control.

CONCLUSIONS

RT-UL allows patients to increase the number of repetitions and hence intensity of practice poststroke, and appears to be a safe therapy. Effects on motor control are small and specific to the joints targeted by RT-UL, whereas no generalization is found to improvements in upper limb capacity. The impact of RT-UL started in the first weeks poststroke remains unclear. These limited findings could mainly be related to poor understanding of robot-induced motor learning as well as inadequate designing of RT-UL trials, by not applying an appropriate selection of stroke patients with a potential to recovery at baseline as well as the lack of fixed timing of baseline assessments and using an insufficient treatment contrast early poststroke.

Posture interacts with arm weight support to modulate corticomotor excitability to the upper limb

The use of arm weight support (WS) to optimize movement quality may be an avenue for improved upper limb stroke rehabilitation; however, the underlying neurophysiological effects of WS are not well understood. Rehabilitation exercises may be performed when sitting or standing, but the interaction of posture with WS has not been examined until now. We explored the effect of posture with WS on corticomotor excitability (CME) in healthy adults. Thirteen participants performed static shoulder abduction in two postures (sitting and standing) at three levels of WS (0, 45, and 90 % of full support). Transcranial magnetic stimulation of primary motor cortex was used to elicit motor-evoked potentials (MEPs) in eight upper limb muscles. Stimulus-response (SR) curves were fitted to the MEP data using nonlinear regression. Whole-body posture interacted with WS to influence tonic activity and CME in all muscles examined. SR curve parameters revealed greater CME when standing compared to sitting for upper arm muscles, but lower CME to the shoulder, forearm, and hand. Distal to the shoulder, tonic activity and CME were modulated independent of any explicit differences in task requirements. Overall, these results support a model of integrated upper limb control influenced by whole-body posture and WS. These findings have implications for the application of WS in settings such as upper limb rehabilitation after stroke.

Modeling and design of a tendon actuated soft robotic exoskeleton for hemiparetic upper limb rehabilitation

Robotic technology has recently been explored as a means to rehabilitate and assist individuals suffering from hemiparesis of their upper limbs. Robotic approaches allow for targeted rehabilitation routines which are more personalized and adaptable while providing quantitative measurements of patient outcomes. Development of these technologies into inherently safe and portable devices has the potential to extend the therapy outside of the clinical setting and into the patient's home with benefits to the cost and accessibility of care. To this end, a soft, cable actuated robotic glove and sleeve was designed, modeled, and constructed to provide assistance of finger and elbow movements in a way that mimics the biological function of the tendons. The resulting design increases safety through greater compliance as well as greater tolerance for misalignment with the user's skeletal frame over traditional rigid exoskeletons. Overall this design provides a platform to expand and study the concepts around soft robotic rehabilitation.

Closed-Loop Neuroprosthesis for Reach-to-Grasp Assistance: Combining Adaptive Multi-channel Neuromuscular Stimulation with a Multi-joint Arm Exoskeleton

Stroke patients with severe motor deficits cannot execute task-oriented rehabilitation exercises with their affected upper extremity. Advanced rehabilitation technology may support them in performing such reach-to-grasp movements. The challenge is, however, to provide assistance as needed, while maintaining the participants' commitment during the exercises. In this feasibility study, we introduced a closed-loop neuroprosthesis for reach-to-grasp assistance which combines adaptive multi-channel neuromuscular stimulation with a multi-joint arm exoskeleton. Eighteen severely affected chronic stroke patients were assisted by a gravity-compensating, seven-degree-of-freedom exoskeleton which was attached to the paretic arm for performing reach-to-grasp exercises resembling activities of daily living in a virtual environment. During the exercises, adaptive electrical stimulation was applied to seven different muscles of the upper extremity in a performance-dependent way to enhance the task-oriented movement trajectory. The stimulation intensity was individualized for each targeted muscle and remained subthreshold, i.e., induced no overt support. Closed-loop neuromuscular stimulation could be well integrated into the exoskeleton-based training, and increased the task-related range of motion (p = 0.0004) and movement velocity (p = 0.015), while preserving accuracy. The highest relative stimulation intensity was required to facilitate the grasping function. The facilitated range of motion correlated with the upper extremity Fugl-Meyer Assessment score of the patients (p = 0.028). Combining adaptive multi-channel neuromuscular stimulation with antigravity assistance amplifies the residual motor capabilities of severely affected stroke patients during rehabilitation exercises and may thus provide a customized training environment for patient-tailored support while preserving the participants' engagement.

Design and Optimization of an EEG-Based Brain Machine Interface (BMI) to an Upper-Limb Exoskeleton for Stroke Survivors

This study demonstrates the feasibility of detecting motor intent from brain activity of chronic stroke patients using an asynchronous electroencephalography (EEG)-based brain machine interface (BMI). Intent was inferred from movement related cortical potentials (MRCPs) measured over an optimized set of EEG electrodes. Successful intent detection triggered the motion of an upper-limb exoskeleton (MAHI Exo-II), to guide movement and to encourage active user participation by providing instantaneous sensory feedback. Several BMI design features were optimized to increase system performance in the presence of single-trial variability of MRCPs in the injured brain: (1) an adaptive time window was used for extracting features during BMI calibration; (2) training data from two consecutive days were pooled for BMI calibration to increase robustness to handle the day-to-day variations typical of EEG, and (3) BMI predictions were gated by residual electromyography (EMG) activity from the impaired arm, to reduce the number of false positives. This patient-specific BMI calibration approach can accommodate a broad spectrum of stroke patients with diverse motor capabilities. Following BMI optimization on day 3, testing of the closed-loop BMI-MAHI exoskeleton, on 4th and 5th days of the study, showed consistent BMI performance with overall mean true positive rate (TPR) = 62.7 ± 21.4% on day 4 and 67.1 ± 14.6% on day 5. The overall false positive rate (FPR) across subjects was 27.74 ± 37.46% on day 4 and 27.5 ± 35.64% on day 5; however for two subjects who had residual motor function and could benefit from the EMG-gated BMI, the mean FPR was quite low (< 10%). On average, motor intent was detected -367 ± 328 ms before movement onset during closed-loop operation. These findings provide evidence that closed-loop EEG-based BMI for stroke patients can be designed and optimized to perform well across multiple days without system recalibration.

Partial weight support of the arm affects corticomotor selectivity of biceps brachii

BACKGROUND

Weight support of the arm (WS) can be used in stroke rehabilitation to facilitate upper limb therapy, but the neurophysiological effects of this technique are not well understood. While an overall reduction in muscle activity is expected, the mechanism by which WS may alter the expression of muscle synergies has not been examined until now. We explored the neurophysiological effect of WS on the selectivity of biceps brachii (BB) activation in healthy adults.

METHODS

Thirteen participants completed counterbalanced movement tasks in a repeated measures design. Three levels of WS (0, 45, and 90 % of full support) were provided to the arm using a commercial device (Saebo Mobile Arm Support). At each level of WS, participants maintained a flexed shoulder posture while performing rhythmic isometric elbow flexion (BB agonist) or forearm pronation (BB antagonist). Single-pulse transcranial magnetic stimulation of primary motor cortex was used to elicit motor-evoked potentials (MEPs) in BB 100-300 ms before muscle contraction. Baseline muscle activity and MEP amplitude were the primary dependent measures. Effects of movement TASK and SUPPORT LEVEL were statistically analyzed using linear mixed effects models.

RESULTS

As expected, with increased support tonic activity was reduced across all muscles. This effect was greatest in the anti-gravity muscle anterior deltoid, and evident in biceps brachii and pronator teres as well. For BB MEP amplitude, TASK and SUPPORT LEVEL, interacted such that for elbow flexion, MEP amplitudes were smaller with incrementally greater WS whereas, for forearm pronation MEP amplitudes were smaller only at high WS.

CONCLUSIONS

Weight support of the arm influences corticomotor selectivity of biceps brachii. WS may impact coordination independently of a global reduction in muscle activity. The amount of supportive force applied to the arm influences the neuromechanical control profile for the limb. These findings may inform the application of WS in upper limb stroke rehabilitation.

Brain state-dependent robotic reaching movement with a multi-joint arm exoskeleton: combining brain-machine interfacing and robotic rehabilitation

While robot-assisted arm and hand training after stroke allows for intensive task-oriented practice, it has provided only limited additional benefit over dose-matched physiotherapy up to now. These rehabilitation devices are possibly too supportive during the exercises. Neurophysiological signals might be one way of avoiding slacking and providing robotic support only when the brain is particularly responsive to peripheral input. We tested the feasibility of three-dimensional robotic assistance for reaching movements with a multi-joint exoskeleton during motor imagery (MI)-related desynchronization of sensorimotor oscillations in the β-band. We also registered task-related network changes of cortical functional connectivity by electroencephalography via the imaginary part of the coherence function. Healthy subjects and stroke survivors showed similar patterns—but different aptitudes—of controlling the robotic movement. All participants in this pilot study with nine healthy subjects and two stroke patients achieved their maximum performance during the early stages of the task. Robotic control was significantly higher and less variable when proprioceptive feedback was provided in addition to visual feedback, i.e., when the orthosis was actually attached to the subject’s arm during the task. A distributed cortical network of task-related coherent activity in the θ-band showed significant differences between healthy subjects and stroke patients as well as between early and late periods of the task. Brain-robot interfaces (BRIs) may successfully link three-dimensional robotic training to the participants’ efforts and allow for task-oriented practice of activities of daily living with a physiologically controlled multi-joint exoskeleton. Changes of cortical physiology during the task might also help to make subject-specific adjustments of task difficulty and guide adjunct interventions to facilitate motor learning for functional restoration, a proposal that warrants further investigation in a larger cohort of stroke patients.

Correlation of reaching and grasping kinematics and clinical measures of upper extremity function in persons with stroke related hemiplegia

Timed measures of standardized functional tasks are commonly used to measure treatment effects in persons with upper extremity (UE) paresis due to stroke. The effectiveness of their ability to measure motor recovery has come into question because of their inability to distinguish between motor recovery and compensations. This paper presents three linear regression models generated from twelve kinematic measures collected during the performance of a two phase reach/grasp and transport /release activity as performed by 21 persons with upper extremity hemiparesis due to chronic stroke. One of these models demonstrated a statistically significant correlation with the subjects' scores on the Wolf Motor Function Test (WMFT), a battery of fifteen standardized upper extremity functional activities. The second and third models demonstrated a statistically significant correlation with the subjects' WMFT change scores elicited by a two week intensive upper extremity motor rehabilitation intervention. The high correlation suggests that models of kinematic measurements can be used to predict neurologic improvement and the effectiveness of treatment.

NeuroControl of movement: system identification approach for clinical benefit

Progress in diagnosis and treatment of movement disorders after neurological diseases like stroke, cerebral palsy (CP), dystonia and at old age requires understanding of the altered capacity to adequately respond to physical obstacles in the environment. With posture and movement disorders, the control of muscles is hampered, resulting in aberrant force generation and improper impedance regulation. Understanding of this improper regulation not only requires the understanding of the role of the neural controller, but also attention for: (1) the interaction between the neural controller and the "plant", comprising the biomechanical properties of the musculaskeletal system including the viscoelastic properties of the contractile (muscle) and non-contractile (connective) tissues: neuromechanics; and (2) the closed loop nature of neural controller and biomechanical system in which cause and effect interact and are hence difficult to separate. Properties of the neural controller and the biomechanical system need to be addressed synchronously by the combination of haptic robotics, (closed loop) system identification (SI), and neuro-mechanical modeling. In this paper, we argue that assessment of neuromechanics in response to well defined environmental conditions and tasks may provide for key parameters to understand posture and movement disorders in neurological diseases and for biomarkers to increase accuracy of prediction models for functional outcome and effects of intervention.

Combined Clinic-Home Approach for Upper Limb Robotic Therapy After Stroke: A Pilot Study

OBJECTIVE

To investigate the feasibility of a combined clinic-home intervention using a robotic elbow brace and, secondarily, to collect preliminary data on the efficacy of this clinic-home intervention.

DESIGN

Nonrandomized pre-/postinterventional study.

SETTING

Outpatient clinic and participants' homes.

PARTICIPANTS

Individuals at least 6 months after stroke (N=11; 5 women and 6 men; mean age, 51.7y; mean time since stroke, 7.6y; mean Fugl-Meyer Assessment of the Upper Extremity [FMA-UE] score, 22 of 66) were enrolled from the community.

INTERVENTIONS

Participants received training in an outpatient clinic from an experienced occupational therapist to gain independence with use of the device (3-9 sessions) followed by a 6-week home program using the device at home.

MAIN OUTCOME MEASURES

Five instruments were administered before and after the study intervention: Modified Ashworth Scale, Box and Blocks test, FMA-UE, Arm Motor Ability Test, and Motor Activity Log-Amount of Use and Motor Activity Log-How Well subscales (MAL-AOU, MAL-HW).

RESULTS

Nine participants completed the study. Participants used the device on average 42.9min/d, 5.3d/wk. The FMA-UE (t=3.32; P=.01), MAL-AOU (t=4.40; P=.002), and MAL-HW (t=4.02; P=.004) scores showed statistically significant improvement from baseline to discharge; the MAL-AOU (t=2.61; P=.035) and MAL-HW (t=2.47; P=.043) scores were also significantly improved from baseline to 3-month follow-up.

CONCLUSIONS

This combined clinic-home intervention was feasible and effective. Participants demonstrated improvements in arm impairment and self-reported use of the arm from baseline to discharge; they continued to report significant improvement in actual use of the arm at 3-month follow-up.

Invited commentary on comparison of robotics, functional electrical stimulation, and motor learning methods for treatment of persistent upper extremity dysfunction after stroke: a randomized controlled trial

In this issue of Archives of Physical Medicine and Rehabilitation, Jessica McCabe and colleagues report findings from their methodologically sound, dose-matched clinical trial in 39 patients beyond 6 months poststroke. In this phase II trial, the effects of 60 treatment sessions, each involving 3.5 hours of intensive practice plus either 1.5 hours of functional electrical stimulation (FES) or a shoulder-arm robotic therapy, were compared with 5 hours of intensive daily practice alone. Although no significant between-group differences were found on the primary outcome measure of Arm Motor Ability Test and the secondary outcome measure of Fugl-Meyer Arm motor score, 10% to 15% within-group therapeutic gains were on the Arm Motor Ability Test and Fugl-Meyer Arm. These gains are clinically meaningful for patients with stroke. However, the underlying mechanisms that drive these improvements remain poorly understood. The approximately $1000 cost reduction per patient calculated for the use of motor learning (ML) methods alone or combined with FES, compared with the combination of ML and shoulder-arm robotics, further emphasizes the need for cost considerations when making clinical decisions about selecting the most appropriate therapy for the upper paretic limb in patients with chronic stroke.

A damper driven robotic end-point manipulator for functional rehabilitation exercises after stroke

Stroke survivors may benefit from robotic assistance for relearning of functional movements. Current assistive devices are either passive, limited to only two dimensions or very powerful. However, for reach training, weight compensation and a little assistance with limited power is sufficient. We designed and evaluated a novel three-dimensional robotic manipulator, which is able to support the arm weight and assist functional reaching movements. Key points of the design are a damper-based drive train, giving an inherently safe system and its compact and lightweight design. The system is force actuated with a bandwidth of up to 2.3 Hz, which is sufficient for functional arm movements. Maximal assistive forces are 15 N for the up/down and forward/backward directions and 10 N for the left/right direction. Force tracking errors are smaller than 1.5 N for all axes and the total weight of the robot is 25 kg. Furthermore, the device has shown its benefit for increasing reaching distance in a single-case study with a stroke subject. The newly developed system has the technical ability to assist the arm during movement, which is a prerequisite for successful training of stroke survivors. Therapeutic effects of the applied assistance need to be further evaluated. However, with its inherent safety and ease of use, this newly developed system even has the potential for home-based therapeutic training after stroke.