Effects of electromyography-driven robot-aided hand training with neuromuscular electrical stimulation on hand control performance after chronic stroke

Comparative efficacy of robot-assisted therapy associated with other different interventions on upper limb rehabilitation after stroke: A protocol for a network meta-analysis

INTRODUCTION

Post-stroke movement disorders are common, especially upper limb dysfunction, which seriously affects the physical and mental health of stroke patients. With the continuous development of intelligent technology, robot-assisted therapy has become a research hotspot in the upper limb rehabilitation of stroke patients in recent years. Many scholars have also integrated robot-assisted therapy with other interventions to improve rehabilitation outcomes. However, there is a lack of research to determine which auxiliary intervention is the best. Therefore, this protocol aims to guide the development of a network meta-analysis, which helps determine the most suitable auxiliary interventions for robot-assisted therapy.

METHODS AND ANALYSIS

Published randomized controlled trials will be included if robot-assisted therapy or robot-assisted therapy associated with other different interventions was applied in stroke patients with upper limb dysfunction in the experimental group and usual rehabilitation treatment and care was applied in the control group. CINAHL, PubMed, Web of Science, MEDLINE, Embase, CNKI, and Wanfang electronic databases will be searched. Studies should be published between January 1, 2013, and December 31, 2023. Two reviewers will independently select studies and extra data, and assess the quality of the included studies. The risk of bias will be evaluated based on the Cochrane Collaboration's risk of bias tool. The evidence quality will be measured according to the Grading of Recommendations Assessment, Development and Evaluation. A network meta-analysis will be conducted by using STATA version 15.0 and R version 4.1.3. The probabilities of rehabilitation interventions will be ranked according to the surface under the cumulative ranking curve.

ETHICS AND DISSEMINATION

Ethical approval is not needed for reviewing published studies. The results will be submitted to a journal.

TRIAL REGISTRATION

PROSPERO registration number: CRD42023486570.

Effects of robot-assisted upper limb training combined with functional electrical stimulation in stroke patients: study protocol for a randomized controlled trial

INTRODUCTION

About 17-80% stroke survivors experience the deficit of upper limb function, which strongly influences their independence and quality of life. Robot-assisted training and functional electrical stimulation are commonly used interventions in the rehabilitation of hemiplegia upper extremities, while the effect of their combination remains unclear. The aim of this trial is to explore the effect of robot-assisted upper limb training combined with functional electrical stimulation, in terms of neuromuscular rehabilitation, compared with robot-assisted upper limb training alone.

METHODS

Individuals (n = 60) with the first onset of stroke (more than 1 week and less than 1 year after stroke onset) will be considered in the recruitment of this single-blinded, three-arm randomized controlled trial. Participants will be allocated into three groups (robot-assisted training combined with functional electrical stimulation group, robot-assisted training group, and conventional rehabilitation therapies group) with a ratio of 1:1:1. All interventions will be executed for 45 min per session, one session per day, 5 sessions per week for 6 weeks. The neuromuscular function of the upper limb (Fugl-Meyer Assessment of upper extremity), ability of daily life (modified Barthel Index), pain (visual analogue scale), and quality of life (EQ-5D-5L) will be assessed at the baseline, at the end of this trial and after 3 months follow-up. Two-way repeated measures analysis of variance will be used to compare the outcomes if the data are normally distributed. Simple effects tests will be used for the further exploration of interaction effects by time and group. Scheirer-Ray-Hare test will be used if the data are not satisfied with normal distribution.

DISCUSSION

We expect this three-arm randomized controlled trial to explore the effectiveness of robot-assisted training combined with functional electrical stimulation in improving post-stroke upper limb function compared with robot-assisted training alone.

TRIAL REGISTRATION

Effect of upper limb robot on improving upper limb function after stroke, identifier: ChiCTR2300073279. Registered on 5 July 2023.

Effects of EMG-based robot for upper extremity rehabilitation on post-stroke patients: a systematic review and meta-analysis

Objective: A growing body of research shows the promise and efficacy of EMG-based robot interventions in improving the motor function in stroke survivors. However, it is still controversial whether the effect of EMG-based robot is more effective than conventional therapies. This study focused on the effects of EMG-based robot on upper limb motor control, spasticity and activity limitation in stroke survivors compared with conventional rehabilitation techniques. Methods: We searched electronic databases for relevant randomized controlled trials. Outcomes included Fugl-Meyer assessment scale (FMA), Modified Ashworth Scale (MAS), and activity level. Result: Thirteen studies with 330 subjects were included. The results showed that the outcomes post intervention was significantly improved in the EMG-based robot group. Results from subgroup analyses further revealed that the efficacy of the treatment was better in patients in the subacute stage, those who received a total treatment time of less than 1000 min, and those who received EMG-based robotic therapy combined with electrical stimulation (ES). Conclusion: The effect of EMG-based robot is superior to conventional therapies in terms of improving upper extremity motor control, spasticity and activity limitation. Further research should explore optimal parameters of EMG-based robot therapy and its long-term effects on upper limb function in post-stroke patients. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/; Identifier: 387070.

Surface EMG analysis of weakness distribution in upper limb muscles post-stroke

Weakness is a common symptom after a stroke. This study aims to depict weakness distribution among forearm muscles given that joints in the upper limb are usually driven by a group of muscles. Multi-channel electromyography (EMG) was applied to assess the muscle group, and an EMG-based index was proposed to quantify the weakness of individual muscles. By using this method, four weakness distribution patterns were observed in extensor muscles from five out of eight subjects after stroke. Complex weakness distribution patterns were observed in flexor muscles from seven out of the eight subjects when they performed grasp, tripod pinch, and hook grip. The findings can help determine the weak muscles in a clinic and facilitate the development of appropriate interventions in stroke rehabilitation targeting specific muscle weakness.

Upper Limbs Muscle Co-contraction Changes Correlated With the Impairment of the Corticospinal Tract in Stroke Survivors: Preliminary Evidence From Electromyography and Motor-Evoked Potential

Objective

Increased muscle co-contraction of the agonist and antagonist muscles during voluntary movement is commonly observed in the upper limbs of stroke survivors. Much remain to be understood about the underlying mechanism. The aim of the study is to investigate the correlation between increased muscle co-contraction and the function of the corticospinal tract (CST).

Methods

Nine stroke survivors and nine age-matched healthy individuals were recruited. All the participants were instructed to perform isometric maximal voluntary contraction (MVC) and horizontal task which consist of sponge grasp, horizontal transportation, and sponge release. We recorded electromyography (EMG) activities from four muscle groups during the MVC test and horizontal task in the upper limbs of stroke survivors. The muscle groups consist of extensor digitorum (ED), flexor digitorum (FD), triceps brachii (TRI), and biceps brachii (BIC). The root mean square (RMS) of EMG was applied to assess the muscle activation during horizontal task. We adopted a co-contraction index (CI) to evaluate the degree of muscle co-contraction. CST function was evaluated by the motor-evoked potential (MEP) parameters, including resting motor threshold, amplitude, latency, and central motor conduction time. We employed correlation analysis to probe the association between CI and MEP parameters.

Results

The RMS, CI, and MEP parameters on the affected side showed significant difference compared with the unaffected side of stroke survivors and the healthy group. The result of correlation analysis showed that CI was significantly correlated with MEP parameters in stroke survivors.

Conclusion

There existed increased muscle co-contraction and impairment in CST functionality on the affected side of stroke survivors. The increased muscle co-contraction was correlated with the impairment of the CST. Intervention that could improve the excitability of the CST may contribute to the recovery of muscle discoordination in the upper limbs of stroke survivors.

Does the Score on the MRC Strength Scale Reflect Instrumented Measures of Maximal Torque and Muscle Activity in Post-Stroke Survivors?

It remains unknown whether variation of scores on the Medical Research Council (MRC) scale for muscle strength is associated with operator-independent techniques: dynamometry and surface electromyography (sEMG). This study aimed to evaluate whether the scores of the MRC strength scale are associated with instrumented measures of torque and muscle activity in post-stroke survivors with severe hemiparesis both before and after an intervention. Patients affected by a first ischemic or hemorrhagic stroke within 6 months before enrollment and with complete paresis were included in the study. The pre- and post-treatment assessments included the MRC strength scale, sEMG, and dynamometry assessment of the triceps brachii (TB) and biceps brachii (BB) as measures of maximal elbow extension and flexion torque, respectively. Proprioceptive-based training was used as a treatment model, which consisted of multidirectional exercises with verbal feedback. Each treatment session lasted 1 h/day, 5 days a week for a total 15 sessions. Nineteen individuals with stroke participated in the study. A significant correlation between outcome measures for the BB (MRC and sEMG p = 0.0177, ρ = 0.601; MRC and torque p = 0.0001, ρ = 0.867) and TB (MRC and sEMG p = 0.0026, ρ = 0.717; MRC and torque p = 0.0001, ρ = 0.873) were observed post intervention. Regression models revealed a relationship between the MRC score and sEMG and torque measures for both the TB and BB. The results confirmed that variation on the MRC strength scale is associated with variation in sEMG and torque measures, especially post intervention. The regression model showed a causal relationship between MRC scale scores, sEMG, and torque assessments.

An Exoneuromusculoskeleton for Self-Help Upper Limb Rehabilitation After Stroke

This article presents a novel electromyography (EMG)-driven exoneuromusculoskeleton that integrates the neuromuscular electrical stimulation (NMES), soft pneumatic muscle, and exoskeleton techniques, for self-help upper limb training after stroke. The developed system can assist the elbow, wrist, and fingers to perform sequential arm reaching and withdrawing tasks under voluntary effort control through EMG, with a lightweight, compact, and low-power requirement design. The pressure/torque transmission properties of the designed musculoskeletons were quantified, and the assistive capability of the developed system was evaluated on patients with chronic stroke (n = 10). The designed musculoskeletons exerted sufficient mechanical torque to support joint extension for stroke survivors. Compared with the limb performance when no assistance was provided, the limb performance (measured as the range of motion in joint extension) significantly improved when mechanical torque and NMES were provided (p < 0.05). A pilot trial was conducted on patients with chronic stroke (n = 15) to investigate the feasibility of using the developed system in self-help training and the rehabilitation effects of the system. All the participants completed the self-help device-assisted training with minimal professional assistance. After a 20-session training, significant improvements were noted in the voluntary motor function and release of muscle spasticity at the elbow, wrist, and fingers, as indicated by the clinical scores (p < 0.05). The EMG parameters (p < 0.05) indicated that the muscular coordination of the entire upper limb improved significantly after training. The results suggested that the developed system can effectively support self-help upper limb rehabilitation after stroke. ClinicalTrials.gov Register Number NCT03752775.

Automated functional electrical stimulation training system for upper-limb function recovery in poststroke patients

BACKGROUND

This paper describes the design and test of an automated functional electrical stimulation (FES) system for poststroke rehabilitation training. The aim of automated FES is to synchronize electrically induced movements to assist residual movements of patients.

METHODS

In the design of the FES system, an accelerometry module detected movement initiation and movement performed by post-stroke patients. The desired movement was displayed in visual game module. Synergy-based FES patterns were formulated using a normal pattern of muscle synergies from a healthy subject. Experiment 1 evaluated how different levels of trigger threshold or timing affected the variability of compound movements for forward reaching (FR) and lateral reaching (LR). Experiment 2 explored the effect of FES duration on compound movements.

RESULTS

Synchronizing FES-assisted movements with residual voluntary movements produced more consistent compound movements. Matching the duration of synergy-based FES to that of patients could assist slower movements of patients with reduced RMS errors.

CONCLUSIONS

Evidence indicated that synchronization and matching duration with residual voluntary movements of patients could improve the consistency of FES assisted movements. Automated FES training can reduce the burden of therapists to monitor the training process, which may encourage patients to complete the training.

A portable assist-as-need upper-extremity hybrid exoskeleton for FES-induced muscle fatigue reduction in stroke rehabilitation

Background

Hybrid exoskeletons are a recent development which combine Functional Electrical Stimulation with actuators to improve both the mental and physical rehabilitation of stroke patients. Hybrid exoskeletons have been shown capable of reducing the weight of the actuator and improving movement precision compared to Functional Electrical Stimulation alone. However little attention has been given towards the ability of hybrid exoskeletons to reduce and manage Functional Electrical Stimulation induced fatigue or towards adapting to user ability. This work details the construction and testing of a novel assist-as-need upper-extremity hybrid exoskeleton which uses model-based Functional Electrical Stimulation control to delay Functional Electrical Stimulation induced muscle fatigue. The hybrid control is compared with Functional Electrical Stimulation only control on a healthy subject.

Results

The hybrid system produced 24° less average angle error and 13.2° less Root Mean Square Error, than Functional Electrical Stimulation on its own and showed a reduction in Functional Electrical Stimulation induced fatigue.

Conclusion

As far as the authors are aware, this is the study which provides evidence of the advantages of hybrid exoskeletons compared to use of Functional Electrical Stimulation on its own with regards to the delay of Functional Electrical Stimulation induced muscle fatigue.

Effect of an EMG-FES Interface on Ankle Joint Training Combined with Real-Time Feedback on Balance and Gait in Patients with Stroke Hemiparesis

This study evaluated the effects of an electromyography-functional electrical stimulation interface (EMG-FES interface) combined with real-time balance and gait feedback on ankle joint training in patients with stroke hemiplegia. Twenty-six stroke patients participated in this study. All subjects were randomly assigned to either the EMG-FES interface combined with real-time feedback on ankle joint training (RFEF) group (n = 13) or the EMG-FES interface on ankle joint training (EF) group (n = 13). Subjects in both groups were trained for 20 min a day, 5 times a week, for 4 weeks. Similarly, all participants underwent a standard rehabilitation physical therapy for 60 min a day, 5 times a week, for 4 weeks. The RFEF group showed significant increases in weight-bearing lunge test (WBLT), Tardieu Scale (TS), Timed Up and Go Test (TUG), Berg Balance Scale (BBS), velocity, cadence, step length, stride length, stance per, and swing per (p < 0.05). Likewise, the EF group showed significant increases in WBLT, TUG, BBS, velocity, and cadence (p < 0.05). Moreover, the RFEF group showed significantly greater improvements than the EF group in terms of WBLT, Tardieu Scale, TUG, BBS, velocity, step length, stride length, stance per, and swing per (p < 0.05). Ankle joint training using an EMG-FES interface combined with real-time feedback improved ankle range of motion (ROM), muscle tone, balance, and gait in stroke patients. These results suggest that an EMG-FES interface combined with real-time feedback is feasible and suitable for ankle joint training in individuals with stroke.

A Review on Design of Upper Limb Exoskeletons

Exoskeleton robotics has ushered in a new era of modern neuromuscular rehabilitation engineering and assistive technology research. The technology promises to improve the upper-limb functionalities required for performing activities of daily living. The exoskeleton technology is evolving quickly but still needs interdisciplinary research to solve technical challenges, e.g., kinematic compatibility and development of effective human–robot interaction. In this paper, the recent development in upper-limb exoskeletons is reviewed. The key challenges involved in the development of assistive exoskeletons are highlighted by comparing available solutions. This paper provides a general classification, comparisons, and overview of the mechatronic designs of upper-limb exoskeletons. In addition, a brief overview of the control modalities for upper-limb exoskeletons is also presented in this paper. A discussion on the future directions of research is included.

Distal versus proximal - an investigation on different supportive strategies by robots for upper limb rehabilitation after stroke: a randomized controlled trial

Background

Different mechanical supporting strategies to the joints in the upper extremity (UE) may lead to varied rehabilitative effects after stroke. This study compared the rehabilitation effectiveness achieved by electromyography (EMG)-driven neuromuscular electrical stimulation (NMES)-robotic systems when supporting to the distal fingers and to the proximal (wrist-elbow) joints.

Methods

Thirty subjects with chronic stroke were randomly assigned to receive motor trainings with NMES-robotic support to the finger joints (hand group, n = 15) and with support to the wrist-elbow joints (sleeve group, n = 15). The training effects were evaluated by the clinical scores of Fugl-Meyer Assessment (FMA), Action Research Arm Test (ARAT), and Modified Ashworth Scale (MAS) before and after the trainings, as well as 3 months later. The cross-session EMG monitoring of EMG activation level and co-contraction index (CI) were also applied to investigate the recovery progress of muscle activations and muscle coordination patterns through the training sessions.

Results

Significant improvements (P < 0.05) in FMA full score, FMA shoulder/elbow (FMA-SE) and ARAT scores were found in both groups, whereas significant improvements (P < 0.05) in FMA wrist/hand (FMA-WH) and MAS scores were only observed in the hand group. Significant decrease of EMG activation levels (P < 0.05) of UE flexors was observed in both groups. Significant decrease in CI values (P < 0.05) was observed in both groups in the muscle pairs of biceps brachii and triceps brachii (BIC&TRI) and the wrist-finger flexors (flexor carpi radialis-flexor digitorum) and TRI (FCR-FD&TRI). The EMG activation levels and CIs of the hand group exhibited faster reductions across the training sessions than the sleeve group (P < 0.05).

Conclusions

Robotic supports to either the distal fingers or the proximal elbow-wrist could achieve motor improvements in UE. The robotic support directly to the distal fingers was more effective than to the proximal parts in improving finger motor functions and in releasing muscle spasticity in the whole UE.

Clinical trial registration

ClinicalTrials.gov, identifier NCT02117089; date of registration: April 10, 2014. https://clinicaltrials.gov/ct2/show/NCT02117089

Myoelectric Pattern Recognition for Controlling a Robotic Hand: A Feasibility Study in Stroke

OBJECTIVE

Myoelectric pattern recognition has been successfully applied as a human-machine interface to control robotic devices such as prostheses and exoskeletons, significantly improving the dexterity of myoelectric control. This study investigates the feasibility of applying myoelectric pattern recognition for controlling a robotic hand in stroke patients.

METHODS

Myoelectric pattern recognition of six hand motion patterns was performed using forearm electromyogram signals in paretic side of eight stroke subjects. Both the random cross validation (RCV) and the chronological handout validation (CHV) were applied to assess the offline myoelectric pattern recognition performance. Experiments on real-time myoelectric pattern recognition control of an exoskeleton robotic hand were also performed.

RESULTS

An average classification accuracy of 84.1% (the mean value from two different classifiers) and individual subject differences were observed in the offline myoelectric pattern recognition analysis using the RCV, while the accuracy decreased to 65.7% when the CHV was used. The stroke subjects achieved an average accuracy of 61.3 ± 20.9% for controlling the robotic hand. However, our study did not reveal a clear correlation between the real-time control accuracy and the offline myoelectric pattern recognition performance, or any specific characteristics of the stroke subjects.

CONCLUSION

The findings suggest that it is feasible to apply myoelectric pattern recognition to control the robotic hand in some but not all of the stroke patients. Each stroke subject should be individually online tested for the feasibility of applying myoelectric pattern recognition control for robot-assisted rehabilitation.

The Effects of Upper-Limb Training Assisted with an Electromyography-Driven Neuromuscular Electrical Stimulation Robotic Hand on Chronic Stroke

Background

Impaired hand dexterity is a major disability of the upper limb after stroke. An electromyography (EMG)-driven neuromuscular electrical stimulation (NMES) robotic hand was designed previously, whereas its rehabilitation effects were not investigated.

Objectives

This study aims to investigate the rehabilitation effectiveness of the EMG-driven NMES-robotic hand-assisted upper-limb training on persons with chronic stroke.

Method

A clinical trial with single-group design was conducted on chronic stroke participants (n = 15) who received 20 sessions of EMG-driven NMES-robotic hand-assisted upper-limb training. The training effects were evaluated by pretraining, posttraining, and 3-month follow-up assessments with the clinical scores of the Fugl-Meyer Assessment (FMA), the Action Research Arm Test (ARAT), the Wolf Motor Function Test, the Motor Functional Independence Measure, and the Modified Ashworth Scale (MAS). Improvements in the muscle coordination across the sessions were investigated by EMG parameters, including EMG activation level and Co-contraction Indexes (CIs) of the target muscles in the upper limb.

Results

Significant improvements in the FMA shoulder/elbow and wrist/hand scores (P < 0.05), the ARAT (P < 0.05), and in the MAS (P < 0.05) were observed after the training and sustained 3 months later. The EMG parameters indicated a significant decrease of the muscle activation level in flexor digitorum (FD) and biceps brachii (P < 0.05), as well as a significant reduction of CIs in the muscle pairs of FD and triceps brachii and biceps brachii and triceps brachii (P < 0.05).

Conclusion

The upper-limb training integrated with the assistance from the EMG-driven NMES-robotic hand is effective for the improvements of the voluntary motor functions and the muscle coordination in the proximal and distal joints. Furthermore, the motor improvement after the training could be maintained till 3 months later.

Trial registration

ClinicalTrials.gov. NCT02117089; date of registration: April 10, 2014.

Robotic Hand-Assisted Training for Spinal Cord Injury Driven by Myoelectric Pattern Recognition: A Case Report

A 51-year-old man with an incomplete C6 spinal cord injury sustained 26 yrs ago attended twenty 2-hr visits over 10 wks for robot-assisted hand training driven by myoelectric pattern recognition. In each visit, his right hand was assisted to perform motions by an exoskeleton robot, while the robot was triggered by his own motion intentions. The hand robot was designed for this study, which can perform six kinds of motions, including hand closing/opening; thumb, index finger, and middle finger closing/opening; and middle, ring, and little fingers closing/opening. After the training, his grip force increased from 13.5 to 19.6 kg, his pinch force remained the same (5.0 kg), his score of Box and Block test increased from 32 to 39, and his score from the Graded Redefined Assessment of Strength, Sensibility, and Prehension test Part 4.B increased from 22 to 24. He accomplished the tasks in the Graded Redefined Assessment of Strength, Sensibility, and Prehension test Part 4.B 28.8% faster on average. The results demonstrate the feasibility and effectiveness of robot-assisted training driven by myoelectric pattern recognition after spinal cord injury.

Real-Time Control of an Exoskeleton Hand Robot with Myoelectric Pattern Recognition

Robot-assisted training provides an effective approach to neurological injury rehabilitation. To meet the challenge of hand rehabilitation after neurological injuries, this study presents an advanced myoelectric pattern recognition scheme for real-time intention-driven control of a hand exoskeleton. The developed scheme detects and recognizes user’s intention of six different hand motions using four channels of surface electromyography (EMG) signals acquired from the forearm and hand muscles, and then drives the exoskeleton to assist the user accomplish the intended motion. The system was tested with eight neurologically intact subjects and two individuals with spinal cord injury (SCI). The overall control accuracy was [Formula: see text] for the neurologically intact subjects and [Formula: see text] for the SCI subjects. The total lag of the system was approximately 250[Formula: see text]ms including data acquisition, transmission and processing. One SCI subject also participated in training sessions in his second and third visits. Both the control accuracy and efficiency tended to improve. These results show great potential for applying the advanced myoelectric pattern recognition control of the wearable robotic hand system toward improving hand function after neurological injuries.

A Neuromuscular Electrical Stimulation (NMES) and robot hybrid system for multi-joint coordinated upper limb rehabilitation after stroke

Background

It is a challenge to reduce the muscular discoordination in the paretic upper limb after stroke in the traditional rehabilitation programs.

Method

In this study, a neuromuscular electrical stimulation (NMES) and robot hybrid system was developed for multi-joint coordinated upper limb physical training. The system could assist the elbow, wrist and fingers to conduct arm reaching out, hand opening/grasping and arm withdrawing by tracking an indicative moving cursor on the screen of a computer, with the support from the joint motors and electrical stimulations on target muscles, under the voluntary intention control by electromyography (EMG). Subjects with chronic stroke (n = 11) were recruited for the investigation on the assistive capability of the NMES-robot and the evaluation of the rehabilitation effectiveness through a 20-session device assisted upper limb training.

Results

In the evaluation, the movement accuracy measured by the root mean squared error (RMSE) during the tracking was significantly improved with the support from both the robot and NMES, in comparison with those without the assistance from the system (P < 0.05). The intra-joint and inter-joint muscular co-contractions measured by EMG were significantly released when the NMES was applied to the agonist muscles in the different phases of the limb motion (P < 0.05). After the physical training, significant improvements (P < 0.05) were captured by the clinical scores, i.e., Modified Ashworth Score (MAS, the elbow and the wrist), Fugl-Meyer Assessment (FMA), Action Research Arm Test (ARAT), and Wolf Motor Function Test (WMFT).

Conclusions

The EMG-driven NMES-robotic system could improve the muscular coordination at the elbow, wrist and fingers.

Trial registration

ClinicalTrials.gov. NCT02117089; date of registration: April 10, 2014

Advanced Myoelectric Control for Robotic Hand-Assisted Training: Outcome from a Stroke Patient

A hand exoskeleton driven by myoelectric pattern recognition was designed for stroke rehabilitation. It detects and recognizes the user’s motion intent based on electromyography (EMG) signals, and then helps the user to accomplish hand motions in real time. The hand exoskeleton can perform six kinds of motions, including the whole hand closing/opening, tripod pinch/opening, and the “gun” sign/opening. A 52-year-old woman, 8 months after stroke, made 20× 2-h visits over 10 weeks to participate in robot-assisted hand training. Though she was unable to move her fingers on her right hand before the training, EMG activities could be detected on her right forearm. In each visit, she took 4× 10-min robot-assisted training sessions, in which she repeated the aforementioned six motion patterns assisted by our intent-driven hand exoskeleton. After the training, her grip force increased from 1.5 to 2.7 kg, her pinch force increased from 1.5 to 2.5 kg, her score of Box and Block test increased from 3 to 7, her score of Fugl–Meyer (Part C) increased from 0 to 7, and her hand function increased from Stage 1 to Stage 2 in Chedoke–McMaster assessment. The results demonstrate the feasibility of robot-assisted training driven by myoelectric pattern recognition after stroke.

Effects of combining robot-assisted therapy with neuromuscular electrical stimulation on motor impairment, motor and daily function, and quality of life in patients with chronic stroke: a double-blinded randomized controlled trial

Background

Robot-assisted therapy (RT) is a widely used intervention approach to enhance motor recovery in patients after stroke, but its effects on functional improvement remained uncertain. Neuromuscular electrical stimulation (NMES) is one potential adjuvant intervention approach to RT that could directly activate the stimulated muscles and improve functional use of the paretic hand.

Methods

This was a randomized, double-blind, sham-controlled study. Thirty-nine individuals with chronic stroke were randomly assigned to the RT combined with NMES (RT + ES) or to RT with sham stimulation (RT + Sham) groups. The participants completed the intervention 90 to 100 minutes/day, 5 days/week for 4 weeks. The outcome measures included the upper extremity Fugl-Meyer Assessment (UE-FMA), modified Ashworth scale (MAS), Wolf Motor Function Test (WMFT), Motor Activity Log (MAL), and Stroke Impact Scale 3.0 (SIS). All outcome measures were assessed before and after intervention, and the UE-FMA, MAL, and SIS were reassessed at 3 months of follow-up.

Results

Compared with the RT + Sham group, the RT + ES group demonstrated greater improvements in wrist flexor MAS score, WMFT quality of movement, and the hand function domain of the SIS. For other outcome measures, both groups improved significantly after the interventions, but no group differences were found.

Conclusion

RT + ES induced significant benefits in reducing wrist flexor spasticity and in hand movement quality in patients with chronic stroke.

Trial registration

ClinicalTrials.gov. NCT01655446

Full-movement neuromuscular electrical stimulation improves plantar flexor spasticity and ankle active dorsiflexion in stroke patients: a randomized controlled study

Objective:

To investigate whether full-movement neuromuscular electrical stimulation, which can generate full range of movement, reduces spasticity and/or improves motor function more effectively than control, sensory threshold—neuromuscular electrical stimulation, and motor threshold—neuromuscular electrical stimulation in sub-acute stroke patients.

Design:

A randomized, single-blind, controlled study.

Setting:

Physical therapy room and functional assessment room.

Participants:

A total of 72 adult patients with sub-acute post-stroke hemiplegia and plantar flexor spasticity.

Method:

Patients received 30-minute sessions of neuromuscular electrical stimulation on the motor points of the extensor hallucis and digitorum longus twice a day, five days per week for four weeks.

Measures:

Composite Spasticity Scale, Ankle Active Dorsiflexion Score, and walking time in the Timed Up and Go Test were assessed at pretreatment, posttreatment, and at two-week follow-up.

Results:

After four weeks of treatment, when comparing interclass pretreatment and posttreatment, only the full-movement neuromuscular electrical stimulation group had a significant reduction in the Composite Spasticity Scale (mean % reduction = 19.91(4.96)%, F = 3.878, p < 0.05) and improvement in the Ankle Active Dorsiflexion Score (mean scores = 3.29(0.91), F = 3.140, p < 0.05). Furthermore, these improvements were maintained two weeks after the treatment ended. However, there were no significant differences in the walking time after four weeks of treatment among the four groups (F = 1.861, p > 0.05).

Conclusions:

Full-movement neuromuscular electrical stimulation with a stimulus intensity capable of generating full movement can significantly reduce plantar flexor spasticity and improve ankle active dorsiflexion, but cannot decrease walking time in the Timed Up and Go Test in sub-acute stroke patients.