Quantitative evaluation of motor functional recovery process in chronic stroke patients during robot-assisted wrist training

The effects of respiratory muscle training on respiratory function and functional capacity in patients with early stroke: a meta-analysis

BACKGROUND

Respiratory muscle training is a continuous and standardized training of respiratory muscles, but the evidence of the effects on early stroke patients is not clear. This meta-analysis aimed to investigate the effects of respiratory muscle training on respiratory function and functional capacity in patients with early stroke.

METHODS

PubMed, Embase, PEDro, ScienceDirect, AMED, CINAHL, and China National Knowledge Infrastructure databases were searched from inception to December 8, 2023 for articles about studies that 1) stroke patients with age ≥ 18 years old. Early stroke < 3 months at the time of diagnosis, 2) respiratory muscle training, including inspiratory and expiratory muscle training, 3) the following measurements are the outcomes: respiratory muscle strength, respiratory muscle endurance, pulmonary function testing, dyspnea fatigue score, and functional capacity, 4) randomized controlled trials. Studies that met the inclusion criteria were extracted data and appraised the methodological quality and risk of bias using the Physiotherapy Evidence Database scale and the Cochrane Risk of Bias tool by two independent reviewers. RevMan 5.4 with a random effect model was used for data synthesis and analysis. Mean differences (MD) or standard mean differences (SMD), and 95% confidence interval were calculated (95%CI).

RESULTS

Nine studies met inclusion criteria, recruiting 526 participants (mean age 61.6 years). Respiratory muscle training produced a statistically significant effect on improving maximal inspiratory pressure (MD = 10.93, 95%CI: 8.51-13.36), maximal expiratory pressure (MD = 9.01, 95%CI: 5.34-12.69), forced vital capacity (MD = 0.82, 95%CI: 0.54-1.10), peak expiratory flow (MD = 1.28, 95%CI: 0.94-1.63), forced expiratory volume in 1 s (MD = 1.36, 95%CI: 1.13-1.59), functional capacity (SMD = 0.51, 95%CI: 0.05-0.98) in patients with early stroke. Subgroup analysis showed that inspiratory muscle training combined with expiratory muscle training was beneficial to the recovery of maximal inspiratory pressure (MD = 9.78, 95%CI: 5.96-13.60), maximal expiratory pressure (MD = 11.62, 95%CI: 3.80-19.43), forced vital capacity (MD = 0.87, 95%CI: 0.47-1.27), peak expiratory flow (MD = 1.51, 95%CI: 1.22-1.80), forced expiratory volume in 1 s (MD = 0.76, 95%CI: 0.41-1.11), functional capacity (SMD = 0.61, 95%CI: 0.08-1.13), while inspiratory muscle training could improve maximal inspiratory pressure (MD = 11.60, 95%CI: 8.15-15.05), maximal expiratory pressure (MD = 7.06, 95%CI: 3.50-10.62), forced vital capacity (MD = 0.71, 95%CI: 0.21-1.21), peak expiratory flow (MD = 0.84, 95%CI: 0.37-1.31), forced expiratory volume in 1 s (MD = 0.40, 95%CI: 0.08-0.72).

CONCLUSIONS

This study provides good-quality evidence that respiratory muscle training is effective in improving respiratory muscle strength, pulmonary function, and functional capacity for patients with early stroke. Inspiratory muscle training combined with expiratory muscle training seems to promote functional recovery in patients with early stroke more than inspiratory muscle training alone.

TRIAL REGISTRATION

Prospero registration number: CRD42021291918.

Myoelectric, Myo-Oxygenation, and Myotonometry Changes during Robot-Assisted Bilateral Arm Exercises with Varying Resistances

Robot-assisted bilateral arm training has demonstrated its effectiveness in improving motor function in individuals post-stroke, showing significant enhancements with increased repetitions. However, prolonged training sessions may lead to both mental and muscle fatigue. We conducted two types of robot-assisted bimanual wrist exercises on 16 healthy adults, separated by one week: long-duration, low-resistance workouts and short-duration, high-resistance exercises. Various measures, including surface electromyograms, near-infrared spectroscopy, heart rate, and the Borg Rating of Perceived Exertion scale, were employed to assess fatigue levels and the impacts of exercise intensity. High-resistance exercise resulted in a more pronounced decline in electromyogram median frequency and recruited a greater amount of hemoglobin, indicating increased muscle fatigue and a higher metabolic demand to cope with the intensified workload. Additionally, high-resistance exercise led to increased sympathetic activation and a greater sense of exertion. Conversely, engaging in low-resistance exercises proved beneficial for reducing post-exercise muscle stiffness and enhancing muscle elasticity. Choosing a low-resistance setting for robot-assisted wrist movements offers advantages by alleviating mental and physiological loads. The reduced training intensity can be further optimized by enabling extended exercise periods while maintaining an approximate dosage compared to high-resistance exercises.

Hybrid Functional Electrical Stimulation and Robotic Assistance for Wrist Motion Training After Stroke: Preliminary Results

This work presents preliminary results of a clinical study with sub-acute stroke patients using a hybrid system for wrist rehabilitation. The patients trained their wrist flexion/extension motion through a target tracking task, where electrical stimulation and robotic torque assisted them proportionally to their tracking error. Five sub-acute stroke patients have completed the training for 3 sessions on separate days. The preliminary results show hybrid assistance improves tracking performance and motion smoothness in most participants. In each session, patients' tracking performances before and after training were evaluated in unassisted tracking trials, without assistance. Their unassisted performance was compared across sessions and the results suggest that moderately to severely impaired patients might benefit more from hybrid training with our system than mildly impaired patients. Subjective assessments from all sessions show that the patients found the use of the device very comfortable and the training enjoyable. More data is being collected and future work will aim at verifying these trends.

The Translation of Mobile-Exoneuromusculoskeleton-Assisted Wrist-Hand Poststroke Telerehabilitation from Laboratory to Clinical Service

Rehabilitation robots are helpful in poststroke telerehabilitation; however, their feasibility and rehabilitation effectiveness in clinical settings have not been sufficiently investigated. A non-randomized controlled trial was conducted to investigate the feasibility of translating a telerehabilitation program assisted by a mobile wrist/hand exoneuromusculoskeleton (WH-ENMS) into routine clinical services and to compare the rehabilitative effects achieved in the hospital-service-based group (n = 12, clinic group) with the laboratory-research-based group (n = 12, lab group). Both groups showed significant improvements (p ≤ 0.05) in clinical assessments of behavioral motor functions and in muscular coordination and kinematic evaluations after the training and at the 3-month follow-up, with the lab group demonstrating better motor gains than the clinic group (p ≤ 0.05). The results indicated that the WH-ENMS-assisted tele-program was feasible and effective for upper limb rehabilitation when integrated into routine practice, and the quality of patient-operator interactions physically and remotely affected the rehabilitative outcomes.

Will Your Next Therapist Be a Robot?-A Review of the Advancements in Robotic Upper Extremity Rehabilitation

Several recent studies have indicated that upper extremity injuries are classified as a top common workplace injury. Therefore, upper extremity rehabilitation has become a leading research area in the last few decades. However, this high number of upper extremity injuries is viewed as a challenging problem due to the insufficient number of physiotherapists. With the recent advancements in technology, robots have been widely involved in upper extremity rehabilitation exercises. Although robotic technology and its involvement in the rehabilitation field are rapidly evolving, the literature lacks a recent review that addresses the updates in the robotic upper extremity rehabilitation field. Thus, this paper presents a comprehensive review of state-of-the-art robotic upper extremity rehabilitation solutions, with a detailed classification of various rehabilitative robots. The paper also reports some experimental robotic trials and their outcomes in clinics.

Lightweight Bioinspired Exoskeleton for Wrist Rehabilitation Powered by Twisted and Coiled Artificial Muscles

Stroke, cerebral palsy, and spinal cord injuries represent the most common leading causes of upper limb impairment. In recent years, rehabilitation robotics has progressed toward developing wearable technologies to promote the portability of assistive devices and to enable home rehabilitation of the upper extremities. However, current wearable technologies mainly rely on electric motors and rigid links or soft pneumatic actuators and are usually bulky and cumbersome. To overcome the limitations of existing technologies, in this paper, a first prototype of a lightweight, ungrounded, soft exoskeleton for wrist rehabilitation powered by soft and flexible carbon fibers-based twisted and coiled artificial muscles (TCAMs) is proposed. The device, which weighs only 0.135 kg, emulates the arrangement and working mechanism of skeletal muscles in the upper extremities and is able to perform wrist flexion/extension and ulnar/radial deviation. The range of motion and the force provided by the exoskeleton is designed through simple kinematic and dynamic theoretical models, while a thermal model is used to design a thermal insulation system for TCAMs during actuation. The device’s ability to perform passive and active-resisted wrist rehabilitation exercises and EMG-based actuation is also demonstrated.

Evaluation of Objective Functions for the Optimal Design of an Assistive Robot

The number of individuals with upper or lower extremities dysfunction (ULED) has considerably increased in the past few decades, resulting in a high economic burden for their families and society. Individuals with ULEDs require assistive robots to fulfill all their activities of daily living (ADLs). However, a theory for the optimal design of assistive robots that reduces energy consumption while increasing the workspace is unavailable. Thus, this research presents an algorithm for the optimal link length selection of an assistive robot mounted on a wheelchair to minimize the torque demands of each joint while increasing the workspace coverage. For this purpose, this research developed a workspace to satisfy a list of 18 ADLs. Then, three torque indices from the literature were considered as performance measures to minimize; the three torque measures are the quadratic average torque (QAT), the weighted root square mean (WRMS), and the absolute sum of torques (AST). The proposed algorithm evaluates any of the three torque measures within the workspace, given the robot dimensions. This proposed algorithm acts as an objective function, which is optimized using a genetic algorithm for each torque measure. The results show that all tree torque measures are suitable criteria for assistance robot optimization. However, each torque measures yield different optimal results; in the case of the QAT optimization, it produces the least workspace with the minimum overall torques of all the joints. Contrarily, the WRMS and AST optimization yield similar results generating the maximum workspace coverage but with a greater overall torque of all joints. Thus, the selection between the three methods depends on the designer's criteria. Based on the results, the presented methodology is a reliable tool for the optimal dimensioning of assistive robots.

Control of Newly-Designed Wearable Robotic Hand Exoskeleton Based on Surface Electromyographic Signals

The human hand plays a role in a variety of daily activities. This intricate instrument is vulnerable to trauma or neuromuscular disorders. Wearable robotic exoskeletons are an advanced technology with the potential to remarkably promote the recovery of hand function. However, the still face persistent challenges in mechanical and functional integration, with real-time control of the multiactuators in accordance with the motion intentions of the user being a particular sticking point. In this study, we demonstrated a newly-designed wearable robotic hand exoskeleton with multijoints, more degrees of freedom (DOFs), and a larger range of motion (ROM). The exoskeleton hand comprises six linear actuators (two for the thumb and the other four for the fingers) and can realize both independent movements of each digit and coordinative movement involving multiple fingers for grasp and pinch. The kinematic parameters of the hand exoskeleton were analyzed by a motion capture system. The exoskeleton showed higher ROM of the proximal interphalangeal and distal interphalangeal joints compared with the other exoskeletons. Five classifiers including support vector machine (SVM), K-near neighbor (KNN), decision tree (DT), multilayer perceptron (MLP), and multichannel convolutional neural networks (multichannel CNN) were compared for the offline classification. The SVM and KNN had a higher accuracy than the others, reaching up to 99%. For the online classification, three out of the five subjects showed an accuracy of about 80%, and one subject showed an accuracy over 90%. These results suggest that the new wearable exoskeleton could facilitate hand rehabilitation for a larger ROM and higher dexterity and could be controlled according to the motion intention of the subjects.

Home-based self-help telerehabilitation of the upper limb assisted by an electromyography-driven wrist/hand exoneuromusculoskeleton after stroke

BACKGROUND

Most stroke survivors have sustained upper limb impairment in their distal joints. An electromyography (EMG)-driven wrist/hand exoneuromusculoskeleton (WH-ENMS) was developed previously. The present study investigated the feasibility of a home-based self-help telerehabilitation program assisted by the aforementioned EMG-driven WH-ENMS and its rehabilitation effects after stroke.

METHODS

Persons with chronic stroke (n = 11) were recruited in a single-group trial. The training progress, including the training frequency and duration, was telemonitored. The clinical outcomes were evaluated using the Fugl-Meyer Assessment (FMA), Action Research Arm Test (ARAT), Wolf Motor Function Test (WMFT), Motor Functional Independence Measure (FIM), and Modified Ashworth Scale (MAS). Improvement in muscle coordination was investigated in terms of the EMG activation level and the Co-contraction Index (CI) of the target muscles, including the abductor pollicis brevis (APB), flexor carpi radialis-flexor digitorum (FCR-FD), extensor carpi ulnaris-extensor digitorum (ECU-ED), biceps brachii (BIC), and triceps brachii (TRI). The movement smoothness and compensatory trunk movement were evaluated in terms of the following two kinematic parameters: number of movement units (NMUs) and maximal trunk displacement (MTD). The above evaluations were conducted before and after the training.

RESULTS

All of the participants completed the home-based program with an intensity of 63.0 ± 1.90 (mean ± SD) min/session and 3.73 ± 0.75 (mean ± SD) sessions/week. After the training, motor improvements in the entire upper limb were found, as indicated by the significant improvements (P < 0.05) in the FMA, ARAT, WMFT, and MAS; significant decreases (P < 0.05) in the EMG activation levels of the APB and FCR-FD; significant decreases (P < 0.05) in the CI of the ECU-ED/FCR-FD, ECU-ED/BIC, FCR-FD/APB, FCR-FD/BIC, FCR-FD/TRI, APB/BIC and BIC/TRI muscle pairs; and significant reductions (P < 0.05) in the NMUs and MTD.

CONCLUSIONS

The results suggested that the home-based self-help telerehabilitation program assisted by EMG-driven WH-ENMS is feasible and effective for improving the motor function of the paretic upper limb after stroke. Trial registration ClinicalTrials.gov. NCT03752775; Date of registration: November 20, 2018.

Probabilistic Model-based Learning Control of a Soft Pneumatic Glove for Hand Rehabilitation

OBJECTIVE

Stroke survivors are usually unable to perform activities of daily living (ADL) independently due to loss of hand functions. Soft pneumatic gloves provide a promising assistance approach for stroke survivors to conduct ADL tasks. However, few studies have explored effective control strategies for the 'human-soft robot' integrated system due to challenges in the nonlinearities of soft robots and uncertainties of human intentions. Therefore, this work aims to develop control approaches for the system to improve stroke survivors hand functions.

METHODS

Firstly, a soft pneumatic glove was utilized to aid with stroke-impaired hands. Secondly, a probabilistic model-based learning control approach was proposed to overcome the challenges. Then a task-oriented intention-driven training modality was designed. Finally, the control performance was evaluated on three able-bodied subjects and three stroke survivors who attended 20-session rehabilitation training.

RESULTS

The proposed approach could enable the soft pneumatic glove to provide adaptive assistance for all participants to accomplish different tasks. The tracking error and muscle co-contraction index showed decreasing trends while the hand gesture index showed an increasing tendency over training sessions. All stroke survivors showed improved hand functions and better muscle coordination after training.

CONCLUSION

This work developed a learning-based soft robotic glove training system and demonstrated its potential in post-stroke hand rehabilitation.

SIGNIFICANCE

This work promotes the application of soft robotic training systems in stroke rehabilitation.

Degree of muscle-and-tendon tonus effects on kinesthetic illusion in wrist joints toward advanced rehabilitation robotics

Due to increasing demand for rehabilitation and therapy for cerebrovascular diseases, patients require advanced development of medical rehabilitation robots. In our laboratory, we focus on the formation capability of the substitute neural path caused by brain plasticity using the kinesthetic illusion (KI), which is effective for therapies using robots. In KI, people perceive an illusionary limb movement without an actual movement when a vibration stimulus is applied to a limb’s tendons. In previous research, the optimal frequency that induces the maximum KI has a correlation factor of about 0.5 with the tendon’s natural frequency when a human subject is in a state of laxity. However, we do not know whether the above finding can be applied to actual rehabilitation because muscles and tendons are sometimes in tonus during rehabilitation, a state that varies the natural frequency. In this study, we investigate the correlation between the optimal and natural frequencies of tendon by systematically changing their tension to clarify the effects on the illusion induced by the muscle and the tendon when they are in tonus. We identified a negative correlation between the optimal and natural frequencies when they are in tonus, although a positive correlation appeared when they are in laxity. This result suggests that KI’s optimal frequency should be changed based on the degree of the tendon and muscle tonus. Therefore, our present findings provide a suitable vibration frequency that induces KI due to the degree of the tendon and muscle tonus during robot therapies.

Quantitative Assessment of Motor Function by an End-Effector Upper Limb Rehabilitation Robot Based on Admittance Control

Various rehabilitation robots have been developed to assist the movement training of the upper limbs of stroke patients, among which some have been used to evaluate the motor recovery. However, how to understand the recovery of motor function from the quantitative assessment following robot-assisted rehabilitation training is still not clear. The objective of this study is to propose a quantitative assessment method of motor function based on the force and trajectory characteristics during robotic training to reflect motor functional recovery. To assist stroke patients who are not able to move voluntarily, an assistive training mode was developed for the robot-assisted rehabilitation system based on admittance control. Then, to validate the relationship between characteristic information and functional recovery, a clinical experiment was conducted, in which nine stroke patients and nine healthy subjects were recruited. The results showed a significant difference in movement range and movement smoothness during trajectory tracking tasks between stroke patients and healthy subjects. The two parameters above have a correlation with the Fugl-Meyer Assessment for Upper Extremity (FMU) of the involved patients. The multiple linear regression analysis showed FMU was positively correlated with parameters (R2=0.91,p<0.005). This finding indicated that the above-mentioned method can achieve quantitative assessment of motor function for stroke patients during robot-assisted rehabilitation training, which can contribute to promoting rehabilitation robots in clinical practice.

Reliable and valid robot-assisted assessments of hand proprioceptive, motor and sensorimotor impairments after stroke

Background

Neurological injuries such as stroke often differentially impair hand motor and somatosensory function, as well as the interplay between the two, which leads to limitations in performing activities of daily living. However, it is challenging to identify which specific aspects of sensorimotor function are impaired based on conventional clinical assessments that are often insensitive and subjective. In this work we propose and validate a set of robot-assisted assessments aiming at disentangling hand proprioceptive from motor impairments, and capturing their interrelation (sensorimotor impairments).

Methods

A battery of five complementary assessment tasks was implemented on a one degree-of-freedom end-effector robotic platform acting on the index finger metacarpophalangeal joint. Specifically, proprioceptive impairments were assessed using a position matching paradigm. Fast target reaching, range of motion and maximum fingertip force tasks characterized motor function deficits. Finally, sensorimotor impairments were assessed using a dexterous trajectory following task. Clinical feasibility (duration), reliability (intra-class correlation coefficient ICC, smallest real difference SRD) and validity (Kruskal-Wallis test, Spearman correlations \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\rho$$\end{document}ρ with Fugl-Meyer Upper Limb Motor Assessment, kinesthetic Up-Down Test, Box & Block Test) of robotic tasks were evaluated with 36 sub-acute stroke subjects and 31 age-matched neurologically intact controls.

Results

Eighty-three percent of stroke survivors with varied impairment severity (mild to severe) could complete all robotic tasks (duration: <15 min per tested hand). Further, the study demonstrated good to excellent reliability of the robotic tasks in the stroke population (ICC>0.7, SRD<30%), as well as discriminant validity, as indicated by significant differences (p-value<0.001) between stroke and control subjects. Concurrent validity was shown through moderate to strong correlations (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\rho$$\end{document}ρ=0.4-0.8) between robotic outcome measures and clinical scales. Finally, robotic tasks targeting different deficits (motor, sensory) were not strongly correlated with each other (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\rho \le$$\end{document}ρ≤0.32, p-value>0.1), thereby presenting complementary information about a patient’s impairment profile.

Conclusions

The proposed robot-assisted assessments provide a clinically feasible, reliable, and valid approach to distinctly characterize impairments in hand proprioceptive and motor function, along with the interaction between the two. This opens new avenues to help unravel the contributions of unique aspects of sensorimotor function in post-stroke recovery, as well as to contribute to future developments towards personalized, assessment-driven therapies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12984-021-00904-5.

A Data-Driven Investigation on Surface Electromyography Based Clinical Assessment in Chronic Stroke

Background: Surface electromyography (sEMG) based robot-assisted rehabilitation systems have been adopted for chronic stroke survivors to regain upper limb motor function. However, the evaluation of rehabilitation effects during robot-assisted intervention relies on traditional manual assessments. This study aimed to develop a novel sEMG data-driven model for automated assessment. Method: A data-driven model based on a three-layer backpropagation neural network (BPNN) was constructed to map sEMG data to two widely used clinical scales, i.e., the Fugl-Meyer Assessment (FMA) and the Modified Ashworth Scale (MAS). Twenty-nine stroke participants were recruited in a 20-session sEMG-driven robot-assisted upper limb rehabilitation, which consisted of hand reaching and withdrawing tasks. The sEMG signals from four muscles in the paretic upper limbs, i.e., biceps brachii (BIC), triceps brachii (TRI), flexor digitorum (FD), and extensor digitorum (ED), were recorded before and after the intervention. Meanwhile, the corresponding clinical scales of FMA and MAS were measured manually by a blinded assessor. The sEMG features including Mean Absolute Value (MAV), Zero Crossing (ZC), Slope Sign Change (SSC), Root Mean Square (RMS), and Wavelength (WL) were adopted as the inputs to the data-driven model. The mapped clinical scores from the data-driven model were compared with the manual scores by Pearson correlation. Results: The BPNN, with 15 nodes in the hidden layer and sEMG features, i.e., MAV, ZC, SSC, and RMS, as the inputs to the model, was established to achieve the best mapping performance with significant correlations (r > 0.9, P < 0.001), according to the FMA. Significant correlations were also obtained between the mapped and manual FMA subscores, i.e., FMA-wrist/hand and FMA-shoulder/elbow, before and after the intervention (r > 0.9, P < 0.001). Significant correlations (P < 0.001) between the mapped and manual scores of MASs were achieved, with the correlation coefficients r = 0.91 at the fingers, 0.88 at the wrist, and 0.91 at the elbow after the intervention. Conclusion: An sEMG data-driven BPNN model was successfully developed. It could evaluate upper limb motor functions in chronic stroke and have potential application in automated assessment in post-stroke rehabilitation, once validated with large sample sizes. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT02117089.

Myoelectric analysis of upper-extremity muscles during robot-assisted bilateral wrist flexion-extension in subjects with poststroke hemiplegia

BACKGROUND

Muscle co-contraction during the execution of motor tasks or training is common in poststroke subjects. EMG-derived muscular activation indexes have been used to evaluate muscle co-contractions during movements. In addition, robot-assisted bilateral arm training provides a repetitive and stable training method to improve arm movements. However, quantitative measures of muscle contractions during this training in poststroke subjects have not been described.

METHODS

Seventeen subjects experiencing spastic hemiplegia after a stroke were recruited to perform robot-assisted bilateral wrist flexion and extension movements. The co-contraction index and two new indexes, temporal correlation and cross mutual information, which are derived from the EMGs of working muscles without the need for envelope normalization, are used to quantify intermuscular activation during wrist movements.

FINDINGS

Higher temporal correlation as well as higher co-contraction index was demonstrated in the affected muscles, implying the recruitment of muscle co-contractions to complete the movement task. On the other hand, a higher value of cross mutual information was exhibited in the unaffected muscles which was attributed to their distinct, rhythmic muscle contractions. The plot of temporal correlation versus cross mutual information further defined affected, unaffected synergistic, and unaffected agonist-antagonist muscular regions. Moreover, with the modified Ashworth scale, multiple regression models based on the co-contraction index and cross mutual information had the highest R-squared value of 0.733.

INTERPRETATION

EMG-derived intermuscular activation parameters demonstrated muscle co-contractions in the affected muscles and different types of intermuscular contractions during robot-assisted bilateral arm training. The modified Ashworth scale estimation based on multiple regression analysis of the activation indexes also demonstrated EMG-derived index a valuable method for assessing muscle spasticity in subjects with poststroke hemiplegia.

A Novel Modified Super-Twisting Control Augmented Feedback Linearization for Wearable Robotic Systems Using Time Delay Estimation

The research presents a novel controller designed for robotic systems subject to nonlinear uncertain dynamics and external disturbances. The control scheme is based on the modified super-twisting method, input/output feedback linearization, and time delay approach. In addition, to minimize the chattering phenomenon and ensure fast convergence to the selected sliding surface, a new reaching law has been integrated with the control law. The control scheme aims to provide high performance and enhanced accuracy via limiting the effects brought by the presence of uncertain dynamics. Stability analysis of the closed-loop system was conducted using a powerful Lyapunov function, showing finite time convergence of the system’s errors. Lastly, experiments shaping rehabilitation tasks, as performed by healthy subjects, demonstrated the controller’s efficiency given its uncertain nonlinear dynamics and the external disturbances involved.

Evidence of neuroplasticity with robotic hand exoskeleton for post-stroke rehabilitation: a randomized controlled trial

Background

A novel electromechanical robotic-exoskeleton was designed in-house for the rehabilitation of wrist joint and Metacarpophalangeal (MCP) joint.

Objective

The objective was to compare the rehabilitation effectiveness (clinical-scales and neurophysiological-measures) of robotic-therapy training sessions with dose-matched conventional therapy in patients with stroke.

Methods

A pilot prospective parallel randomized controlled study at clinical settings was designed for patients with stroke within 2 years of chronicity. Patients were randomly assigned to receive an intervention of 20 sessions of 45 min each, five days a week for four weeks, in Robotic-therapy Group (RG) (n = 12) and conventional upper-limb rehabilitation in Control-Group (CG) (n = 11). We intended to evaluate the effects of a novel exoskeleton based therapy on the functional rehabilitation outcomes of upper-limb and cortical-excitability in patients with stroke as compared to the conventional-rehabilitation. Clinical-scales– Modified Ashworth Scale, Active Range of Motion, Barthel-Index, Brunnstrom-stage and Fugl-Meyer (FM) scale and neurophysiological measures of cortical-excitability (using Transcranial Magnetic Stimulation) –Motor Evoked Potential and Resting Motor threshold, were acquired pre- and post-therapy.

Results

No side effects were noticed in any of the patients. Both RG and CG showed significant (p < 0.05) improvement in all clinical motor-outcomes except Modified Ashworth Scale in CG. RG showed significantly (p < 0.05) higher improvement over CG in Modified Ashworth Scale, Active Range of Motion and Fugl-Meyer scale and FM Wrist-/Hand component. An increase in cortical-excitability in ipsilesional-hemisphere was found to be statistically significant (p < 0.05) in RG over CG, as indexed by a decrease in Resting Motor Threshold and increase in the amplitude of Motor Evoked Potential. No significant changes were shown by the contralesional-hemisphere. Interhemispheric RMT-asymmetry evidenced significant (p < 0.05) changes in RG over CG indicating increased cortical-excitability in ipsilesional-hemisphere along with interhemispheric changes.

Conclusion

Robotic-exoskeleton training showed improvement in motor outcomes and cortical-excitability in patients with stroke. Neurophysiological changes in RG could most likely be a consequence of plastic reorganization and use-dependent plasticity.

Trial registry number: ISRCTN95291802

Supplementary Information

The online version contains supplementary material available at 10.1186/s12984-021-00867-7.

Effects of Robot-Assisted Rehabilitation on Hand Function of People With Stroke: A Randomized, Crossover-Controlled, Assessor-Blinded Study

IMPORTANCE

The effects of robot-assisted task-oriented training with tangible objects among patients with stroke remain unknown.

OBJECTIVE

To investigate the effects of robot-assisted therapy (RT) with a Gloreha device on sensorimotor and hand function and ability to perform activities of daily living (ADLs) among patients with stroke.

DESIGN

Randomized, crossover-controlled, assessor-blinded study.

SETTING

Rehabilitation clinic.

PARTICIPANTS

Patients (N = 24) with moderate motor and sensory deficits.

INTERVENTION

Patients participated in 12 RT sessions and 12 conventional therapy (CT) sessions, with order counterbalanced, for 6 wk, with a 1-mo washout period.

OUTCOMES AND MEASURES

Performance was assessed four times: before and after RT and before and after CT. Outcomes were measured using the Fugl-Meyer Assessment-Upper Extremity (FMA-UE), Box and Block Test, electromyography of the extensor digitorum communis (EDC) and brachioradialis, and a grip dynamometer for motor function; Semmes-Weinstein hand monofilament and the Revised Nottingham Sensory Assessment for sensory function; and the Modified Barthel Index (MBI) for ADL ability.

RESULTS

RT resulted in significantly improved FMA-UE proximal (p = .038) and total (p = .046) and MBI (p = .030) scores. Participants' EDC muscles exhibited higher efficacy during the small-block grasping task of the Box and Block Test after RT than after CT (p = .050).

CONCLUSIONS AND RELEVANCE

RT with the Gloreha device can facilitate whole-limb function, leading to beneficial effects on arm motor function, EDC muscle recruitment efficacy, and ADL ability for people with subacute and chronic stroke.

WHAT THIS ARTICLE ADDS

The evidence suggests that a task-oriented approach combined with the Gloreha device can facilitate engagement in whole-limb active movement and efficiently promote functional recovery.

Sequentially applied myoelectrically controlled FES in a task-oriented approach and robotic therapy for the recovery of upper limb in post-stroke patients: A randomized controlled pilot study

BACKGROUND

Functional recovery of the plegic upper limb in post-stroke patients may be enhanced by sequentially applying a myoelectrically controlled FES (MeCFES), which allows the patient to voluntarily control the muscle contraction during a functional movement, and robotic therapy which allows many repetitions of movements.

OBJECTIVE

Evaluate the efficacy of MeCFES followed by robotic therapy compared to standard care arm rehabilitation for post-stroke patients.

METHODS

Eighteen stroke subjects (onset ⩾ 3 months, age 60.1 ± 15.5) were recruited and randomized to receive an experimental combination of MeCFES during task-oriented reaching followed by robot therapy (MRG) or same intensity conventional rehabilitation care (CG) aimed at the recovery of the upper limb (20 sessions/45 minutes). Change was evaluated through Fugl-Meyer upper extremity (FMA-UE), Reaching Performance Scale and Box and Block Test.

RESULTS

The experimental treatment resulted in higher improvement on the FMA-UE compared with CG (P= 0.04), with a 10-point increase following intervention. Effect sizes were moderate in favor of the MRG group on FMA-UE, FMA-UE proximal and RPS (0.37-0.56).

CONCLUSIONS

Preliminary findings indicate that a combination of MeCFES and robotic treatment may be more effective than standard care for recovery of the plegic arm in persons > 3 months after stroke. The mix of motor learning techniques may be important for successful rehabilitation of arm function.

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.

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.

Development of a biological signal-based evaluator for robot-assisted upper-limb rehabilitation: a pilot study

Bio-signal based assessment for upper-limb functions is an attractive technology for rehabilitation. In this work, an upper-limb function evaluator is developed based on biological signals, which could be used for selecting different robotic training protocols. Interaction force (IF) and participation level (PL, processed surface electromyography (sEMG) signals) are used as the key bio-signal inputs for the evaluator. Accordingly, a robot-based standardized performance testing (SPT) is developed to measure these key bio-signal data. Moreover, fuzzy logic is used to regulate biological signals, and a rules-based selector is then developed to select different training protocols. To the authors' knowledge, studies focused on biological signal-based evaluator for selecting robotic training protocols, especially for robot-based bilateral rehabilitation, has not yet been reported in literature. The implementation of SPT and fuzzy logic to measure and process key bio-signal data with a rehabilitation robot system is the first of its kind. Five healthy participants were then recruited to test the performance of the SPT, fuzzy logic and evaluator in three different conditions (tasks). The results show: (1) the developed SPT has an ability to measure precise bio-signal data from participants; (2) the utilized fuzzy logic has an ability to process the measured data with the accuracy of 86.7% and 100% for the IF and PL respectively; and (3) the proposed evaluator has an ability to distinguish the intensity of biological signals and thus to select different robotic training protocols. The results from the proposed evaluator, and biological signals measured from healthy people could also be used to standardize the criteria to assess the results of stroke patients later.

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

NAO robot for cooperative rehabilitation training

INTRODUCTION

The aim of this research is to develop a robot-assistive training approach for the disabled individuals with impaired upper limb functions. People with impaired upper limb function can regain their motor functionality undergoing intense rehabilitation exercises. With increasing number of disabled individuals, we face deficiency in the number of expert therapists. One promising remedy could be the use of robotic assistive devices.

METHOD

To instruct and demonstrate rehabilitation exercise, this research used NAO robot. A library of recommended rehabilitation exercises involving shoulder (i.e., abduction/adduction, vertical flexion/extension, and internal/external rotation), and elbow (i.e., flexion/extension) joint movements was formed in Choregraphe (graphical programming interface). For this purpose, a kinematic model of human upper-extremity was developed based on modified Denavit-Hartenberg notations.

RESULT

In experiments, NAO robot gave voice instruction and was maneuvered to cooperate and demonstrate the exercises from the library. NAO also plays some complex game with the subject that represents a multi-joint movement's exercise, which was also included in the library.

CONCLUSIONS

Experimental results with healthy participants reveal that the NAO robot can successfully instruct and demonstrate upper-extremity rehabilitation exercises for single and multi-joint movements. It implies a technical development of cooperative rehabilitation system for which target group will be individuals with upper limb impairment.

Alterations in muscle activation patterns during robot-assisted bilateral training: A pilot study

Robot-assisted bilateral training is being developed as a new rehabilitation approach for stroke patients. However, there is still a lack of understanding of muscle functions when performing robot-assisted synchronous movements. The aim of this work is to explore the muscle activation patterns and the voluntary effort of participants during different robot-assisted bilateral training protocols. To this end, 10 healthy participants were recruited to take part in a 60-minute experiment. The experiment included two different bilateral exercises, and each exercise contained four different training protocols. Trajectories of the robots, interaction force and surface electromyogram signals were recorded during training. The results show that the robots do affect the muscle activation patterns during different training protocols and exercises rather than the controller. Specifically, the activity of muscles is reduced in robot-assisted training but is increased in active force involved robot-assisted training when compared to robot-unassisted training. Meanwhile, the voluntary effort of participants can be presented by the adjusted trajectories via the controller. In addition, the results also suggest that the activations for the same muscle groups in the left and right arms are highly correlated with each other in both exercises. Furthermore, the training protocols and methods developed in this work could be further extended in future clinical trials to investigate therapeutic outcomes for patients as well as to better understand bilateral recovery processes.

Muscle Synergy for Hand Motions Based on Electromyography Analysis

This study aimed to investigate the muscle synergy for hand motions of both the left and right hands based on surface electromyography (sEMG) signals. Six hand motions, including hand grasp (HG), four fingers flexion (FFF), index finger extension (IFE), thumb internal rotation (TIR), thumb opposition (TO), key pinch (KP), were examined in the experiment. The sEMG signals were recorded from brachioradialis (BRA), flexor carpi ulnaris (FCU), flexor carpi radialis (FCR), extensor digitorum communis (EDC), flexor digitorum superficialis (FDS), abductor pollicis brevis (APB), first dorsal interosseous (FDI) and abductor digiti minimi (ADM) of both the left and right hands. A co-contraction index (CI) followed by a correlation coefficients (CC) was applied to quantify the muscle synergy during the hand motions and to compare the synergistic patterns across hands. Results shown that the left and right hands had similar muscle synergy (CC (CC>0.9) for any of the motions. For both hands, there were strong correlations between the synergistic matrix of different motions (CC (CC>0.85), including the correlations between HG and FFF, between FFF and IFE, and between TO and KP. By contrast, weak correlations between the synergistic matrix for IFE and that for TIR (CC (CC<0.1), suggesting a low similarity of the muscle synergy for the two motions. This study shed light on how the muscles of the left and right hands are involved and co-contracted for the dexterous hand motions.

Design and effectiveness evaluation of mirror myoelectric interfaces: a novel method to restore movement in hemiplegic patients

The motor impairment occurring after a stroke is characterized by pathological muscle activation patterns or synergies. However, while robot-aided myoelectric interfaces have been proposed for stroke rehabilitation, they do not address this issue, which might result in inefficient interventions. Here, we present a novel paradigm that relies on the correction of the pathological muscle activity as a way to elicit rehabilitation, even in patients with complete paralysis. Previous studies demonstrated that there are no substantial inter-limb differences in the muscle synergy organization of healthy individuals. We propose building a subject-specific model of muscle activity from the healthy limb and mirroring it to use it as a learning tool for the patient to reproduce the same healthy myoelectric patterns on the paretic limb during functional task training. Here, we aim at understanding how this myoelectric model, which translates muscle activity into continuous movements of a 7-degree of freedom upper limb exoskeleton, could transfer between sessions, arms and tasks. The experiments with 8 healthy individuals and 2 chronic stroke patients proved the feasibility and effectiveness of such myoelectric interface. We anticipate the proposed method to become an efficient strategy for the correction of maladaptive muscle activity and the rehabilitation of stroke patients.

Electromechanical and robot-assisted arm training for improving activities of daily living, arm function, and arm muscle strength after stroke

BACKGROUND

Electromechanical and robot-assisted arm training devices are used in rehabilitation, and may help to improve arm function after stroke.

OBJECTIVES

To assess the effectiveness of electromechanical and robot-assisted arm training for improving activities of daily living, arm function, and arm muscle strength in people after stroke. We also assessed the acceptability and safety of the therapy.

SEARCH METHODS

We searched the Cochrane Stroke Group's Trials Register (last searched January 2018), the Cochrane Central Register of Controlled Trials (CENTRAL) (the Cochrane Library 2018, Issue 1), MEDLINE (1950 to January 2018), Embase (1980 to January 2018), CINAHL (1982 to January 2018), AMED (1985 to January 2018), SPORTDiscus (1949 to January 2018), PEDro (searched February 2018), Compendex (1972 to January 2018), and Inspec (1969 to January 2018). We also handsearched relevant conference proceedings, searched trials and research registers, checked reference lists, and contacted trialists, experts, and researchers in our field, as well as manufacturers of commercial devices.

SELECTION CRITERIA

Randomised controlled trials comparing electromechanical and robot-assisted arm training for recovery of arm function with other rehabilitation or placebo interventions, or no treatment, for people after stroke.

DATA COLLECTION AND ANALYSIS

Two review authors independently selected trials for inclusion, assessed trial quality and risk of bias, used the GRADE approach to assess the quality of the body of evidence, and extracted data. We contacted trialists for additional information. We analysed the results as standardised mean differences (SMDs) for continuous variables and risk differences (RDs) for dichotomous variables.

MAIN RESULTS

We included 45 trials (involving 1619 participants) in this update of our review. Electromechanical and robot-assisted arm training improved activities of daily living scores (SMD 0.31, 95% confidence interval (CI) 0.09 to 0.52, P = 0.0005; I² = 59%; 24 studies, 957 participants, high-quality evidence), arm function (SMD 0.32, 95% CI 0.18 to 0.46, P < 0.0001, I² = 36%, 41 studies, 1452 participants, high-quality evidence), and arm muscle strength (SMD 0.46, 95% CI 0.16 to 0.77, P = 0.003, I² = 76%, 23 studies, 826 participants, high-quality evidence). Electromechanical and robot-assisted arm training did not increase the risk of participant dropout (RD 0.00, 95% CI -0.02 to 0.02, P = 0.93, I² = 0%, 45 studies, 1619 participants, high-quality evidence), and adverse events were rare.

AUTHORS' CONCLUSIONS

People who receive electromechanical and robot-assisted arm training after stroke might improve their activities of daily living, arm function, and arm muscle strength. However, the results must be interpreted with caution although the quality of the evidence was high, because there were variations between the trials in: the intensity, duration, and amount of training; type of treatment; participant characteristics; and measurements used.

Wrist Robot-assisted Rehabilitation Treatment in Subacute and Chronic Stroke Patients: from Distal to Proximal Motor Recovery

In this study, the recovery of proximal and distal segments in stroke patients who received distal training alone was investigated. Forty (20 subacute and 20 chronic) stroke patients were recruited to perform wrist robot-assisted rehabilitation training. The upper extremity, shoulder-elbow and wrist subsections of the Fugl-Meyer Assessment Scale were used to assess the motor recovery of distal and proximal segments. In addition, the Modified Ashworth Scale, the Motricity Index and the Box & Block test were used as clinical outcome measures together with kinematic parameters to evaluate the effects of the training. Significant increases in the wrist and shoulder-elbow subsections of the Fugl-Meyer Assessment Scale, Motricity Index and Box & Block test were found in both groups. Average changes in shoulder-elbow and upper extremity subsections of the Fugl-Meyer Assessment Scale in the subacute group (6.10 ± 6.60 and 15.65 ± 14.04) were significantly higher (p < 0.05) than those in the chronic group (2.30 ± 2.76 and 6.60 ± 4.64). In addition, significant increases in the movement velocity, movement smoothness and movement quality were observed in the subacute group. Our findings provide evidence that following a robot-assisted rehabilitation treatment there is a distal-to-proximal generalization in subacute stroke patients.

The eWrist - A wearable wrist exoskeleton with sEMG-based force control for stroke rehabilitation

Chronic wrist impairment is frequent following stroke and negatively impacts everyday life. Rehabilitation of the dysfunctional limb is possible but requires extensive training and motivation. Wearable training devices might offer new opportunities for rehabilitation. However, few devices are available to train wrist extension even though this movement is highly relevant for many upper limb activities of daily living. As a proof of concept, we developed the eWrist, a wearable one degree-of-freedom powered exoskeleton which supports wrist extension training. Conceptually one might think of an electric bike which provides mechanical support only when the rider moves the pedals, i.e. it enhances motor activity but does not replace it. Stroke patients may not have the ability to produce overt movements, but they might still be able to produce weak muscle activation that can be measured via surface electromyography (sEMG). By combining force and sEMG-based control in an assist-as-needed support strategy, we aim at providing a training device which enhances activity of the wrist extensor muscles in the context of daily life activities, thereby, driving cortical reorganization and recovery. Preliminary results show that the integration of sEMG signals in the control strategy allow for adjustable assistance with respect to a proxy measurement of corticomotor drive.

A review: Motor rehabilitation after stroke with control based on human intent

Strokes are a leading cause of acquired disability worldwide, and there is a significant need for novel interventions and further research to facilitate functional motor recovery in stroke patients. This article reviews motor rehabilitation methods for stroke survivors with a focus on rehabilitation controlled by human motor intent. The review begins with the neurodevelopmental principles of motor rehabilitation that provide the neuroscientific basis for intuitively controlled rehabilitation, followed by a review of methods allowing human motor intent detection, biofeedback approaches, and quantitative motor rehabilitation assessment. Challenges for future advances in motor rehabilitation after stroke using intuitively controlled approaches are addressed.

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.

Early Stroke Rehabilitation of the Upper Limb Assisted with an Electromyography-Driven Neuromuscular Electrical Stimulation-Robotic Arm

Background

Effective poststroke motor rehabilitation depends on repeated limb practice with voluntary efforts. An electromyography (EMG)-driven neuromuscular electrical stimulation (NMES)-robot arm was designed for the multi-joint physical training on the elbow, the wrist, and the fingers.

Objectives

To investigate the training effects of the device-assisted approach on subacute stroke patients and to compare the effects with those achieved by the traditional physical treatments.

Method

This study was a pilot randomized controlled trial with a 3-month follow-up. Subacute stroke participants were randomly assigned into two groups, and then received 20-session upper limb training with the EMG-driven NMES-robotic arm (NMES-robot group, n = 14) or the time-matched traditional therapy (the control, n = 10). For the evaluation of the training effects, clinical assessments including Fugl-Meyer Assessment (FMA), Modified Ashworth Score (MAS), Action Research Arm Test (ARAT), and Function Independence Measurement (FIM) were conducted before, after the rehabilitation training, and 3 months later. Session-by-session EMG parameters in the NMES-robot group, including normalized co-contraction Indexes (CI) and EMG activation level of target muscles, were used to monitor the progress in muscular coordination patterns.

Results

Significant improvements were obtained in FMA (full score and shoulder/elbow), ARAT, and FIM [P < 0.001, effect sizes (EFs) > 0.279] for both groups. Significant improvement in FMA wrist/hand was only observed in the NMES-robot group (P < 0.001, EFs = 0.435) after the treatments. Significant reduction in MAS wrist was observed in the NMES-robot group after the training (P < 0.05, EFs = 0.145) and the effects were maintained for 3 months. MAS scores in the control group were elevated following training (P < 0.05, EFs > 0.24), and remained at an elevated level when assessed 3 months later. The EMG parameters indicated a release of muscle co-contraction in the muscle pairs of biceps brachii and flexor carpi radialis and biceps brachii and triceps brachii, as well as a reduction of muscle activation level in the wrist flexor in the NMES-robot group.

Conclusion

The NMES-robot-assisted training was effective for early stroke upper limb rehabilitation and promoted independence in the daily living comparable to the traditional physical therapy. It could achieve higher motor outcomes at the distal joints and more effective release in muscle tones than the traditional therapy.

Clinical Trial Registration

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

Alterations of Muscle Activation Pattern in Stroke Survivors during Obstacle Crossing

OBJECTIVE

This study investigates changes in the neuromuscular activation pattern of the lower limb muscles in stroke survivors when crossing obstacles of three different heights.

METHODS

Eight stroke survivors and eight age-, height-, and gender-matched healthy controls were recruited and instructed to cross over obstacles with heights of 10, 20, and 30% leg length. Surface electromyography (EMG) signals were recorded from the rectus femoris (RF), biceps femoris (BF), tibialis anterior (TA), and medial gastrocnemius (MG) of both limbs. Muscle activation signals were normalized to maximum voluntary contraction. Differences between groups and heights were compared using the root mean square of EMG, the cocontraction index of agonist and antagonist muscles, and power spectral analysis based on the mean power frequency (MPF). The correlations between the calculated variables and clinical scales such as Berg Balance Scale and Fugl-Meyer assessment (FMA) were also examined.

RESULTS

During the leading limb swing phase, the activation levels of all four muscles were greater in the stroke group than the healthy controls (p < 0.05), and the TA showed increased activation level with increasing obstacle height in both groups (p < 0.05). Cocontraction between the TA and MG was higher in the stroke group during the swing phase of the leading limb and between the RF and BF during the stance phase (p < 0.05). Similarly, for the trailing limb, increased cocontractions between the two pairs of agonist and antagonist muscles were found during the stance phase in the stroke group (p < 0.05). During the crossing stride, the frequency analysis showed significantly smaller MPF values in all four lower limb muscles in the leading limb of stroke survivors compared with healthy controls (p < 0.05). Moreover, significant correlations were found between the FMA scores and the BF and TA activations in the leading limb during the swing phase (p < 0.05).

CONCLUSION

Greater activation levels of the lower limb muscles resulted in higher muscular demands for stroke survivors, which might lead to greater difficulty in maintaining balance. The increased cocontraction during obstacle crossing might be compensation for the affected stability and enable safe crossing for stroke survivors. The reduced MPF in the affected limb of the stroke group might be due to impairments in motor units or other complex neuromuscular alterations.

Wrist Rehabilitation Assisted by an Electromyography-Driven Neuromuscular Electrical Stimulation Robot After Stroke

BACKGROUND

Augmented physical training with assistance from robot and neuromuscular electrical stimulation (NMES) may introduce intensive motor improvement in chronic stroke.

OBJECTIVE

To compare the rehabilitation effectiveness achieved by NMES robot-assisted wrist training and that by robot-assisted training.

METHODS

This study was a single-blinded randomized controlled trial with a 3-month follow-up. Twenty-six hemiplegic subjects with chronic stroke were randomly assigned to receive 20-session wrist training with an electromyography (EMG)-driven NMES robot (NMES robot group, n = 11) and with an EMG-driven robot (robot group, n = 15), completed within 7 consecutive weeks. Clinical scores, Fugl-Meyer Assessment (FMA), Modified Ashworth Score (MAS), and Action Research Arm Test (ARAT) were used to evaluate the training effects before and after the training, as well as 3 months later. An EMG parameter, muscle co-contraction index, was also applied to investigate the session-by-session variation in muscular coordination patterns during the training.

RESULTS

The improvement in FMA (shoulder/elbow, wrist/hand) obtained in the NMES robot group was more significant than the robot group (P < .05). Significant improvement in ARAT was achieved in the NMES robot group (P < .05) but absent in the robot group. NMES robot-assisted training showed better performance in releasing muscle co-contraction than the robot-assisted across the training sessions (P < .05).

CONCLUSIONS

The NMES robot-assisted wrist training was more effective than the pure robot. The additional NMES application in the treatment could bring more improvements in the distal motor functions and faster rehabilitation progress.

Assessment of movement quality in robot- assisted upper limb rehabilitation after stroke: a review

Studies of stroke patients undergoing robot-assisted rehabilitation have revealed various kinematic parameters describing movement quality of the upper limb. However, due to the different level of stroke impairment and different assessment criteria and interventions, the evaluation of the effectiveness of rehabilitation program is undermined. This paper presents a systematic review of kinematic assessments of movement quality of the upper limb and identifies the suitable parameters describing impairments in stroke patients. A total of 41 different clinical and pilot studies on different phases of stroke recovery utilizing kinematic parameters are evaluated. Kinematic parameters describing movement accuracy are mostly reported for chronic patients with statistically significant outcomes and correlate strongly with clinical assessments. Meanwhile, parameters describing feed-forward sensorimotor control are the most frequently reported in studies on sub-acute patients with significant outcomes albeit without correlation to any clinical assessments. However, lack of measures in coordinated movement and proximal component of upper limb enunciate the difficulties to distinguish the exploitation of joint redundancies exhibited by stroke patients in completing the movement. A further study on overall measures of coordinated movement is recommended.

Neural coding for effective rehabilitation

Successful neurological rehabilitation depends on accurate diagnosis, effective treatment, and quantitative evaluation. Neural coding, a technology for interpretation of functional and structural information of the nervous system, has contributed to the advancements in neuroimaging, brain-machine interface (BMI), and design of training devices for rehabilitation purposes. In this review, we summarized the latest breakthroughs in neuroimaging from microscale to macroscale levels with potential diagnostic applications for rehabilitation. We also reviewed the achievements in electrocorticography (ECoG) coding with both animal models and human beings for BMI design, electromyography (EMG) interpretation for interaction with external robotic systems, and robot-assisted quantitative evaluation on the progress of rehabilitation programs. Future rehabilitation would be more home-based, automatic, and self-served by patients. Further investigations and breakthroughs are mainly needed in aspects of improving the computational efficiency in neuroimaging and multichannel ECoG by selection of localized neuroinformatics, validation of the effectiveness in BMI guided rehabilitation programs, and simplification of the system operation in training devices.

Training modalities in robot-mediated upper limb rehabilitation in stroke: a framework for classification based on a systematic review

Robot-mediated post-stroke therapy for the upper-extremity dates back to the 1990s. Since then, a number of robotic devices have become commercially available. There is clear evidence that robotic interventions improve upper limb motor scores and strength, but these improvements are often not transferred to performance of activities of daily living. We wish to better understand why. Our systematic review of 74 papers focuses on the targeted stage of recovery, the part of the limb trained, the different modalities used, and the effectiveness of each. The review shows that most of the studies so far focus on training of the proximal arm for chronic stroke patients. About the training modalities, studies typically refer to active, active-assisted and passive interaction. Robot-therapy in active assisted mode was associated with consistent improvements in arm function. More specifically, the use of HRI features stressing active contribution by the patient, such as EMG-modulated forces or a pushing force in combination with spring-damper guidance, may be beneficial.Our work also highlights that current literature frequently lacks information regarding the mechanism about the physical human-robot interaction (HRI). It is often unclear how the different modalities are implemented by different research groups (using different robots and platforms). In order to have a better and more reliable evidence of usefulness for these technologies, it is recommended that the HRI is better described and documented so that work of various teams can be considered in the same group and categories, allowing to infer for more suitable approaches. We propose a framework for categorisation of HRI modalities and features that will allow comparing their therapeutic benefits.

Somatosensory inputs by application of KinesioTaping: effects on spasticity, balance, and gait in chronic spinal cord injury

INTRODUCTION

Leg paralysis, spasticity, reduced interlimb coordination, and impaired balance are the chief limitations to overground ambulation in subjects with incomplete spinal cord injury (SCI). In recent years, the application of KinesioTaping (KT) has been proposed to enhance sensory inputs, decreasing spasticity by proprioception feedback and relieving abnormal muscle tension. Because no studies have examined KT-based techniques in SCI subjects, our goal was to analyze the effects of ankle joint KT on spasticity, balance, and gait.

MATERIALS AND METHODS

A randomized crossover case control design was used to compare the effects of KT and conventional nonelastic silk tape (ST) in 11 chronic SCI subjects, AIS level D, with soleus/gastrocnemius (S/G) muscle spasticity and balance and gait impairments.

TREATMENT

48 h of treatment with KT or ST was followed by 48 h with the other technique after 1 week. A single Y-strip of Cure(©) tape (KT) and ST was to the S and G muscles with 0% stretch. Before and 48 h after of application of KT and ST, clinical data on the range of motion (ROM), spasticity, clonus, pain, balance, and gait were collected. Stabilometric platform assessment of center of pressure (COP) movements; bidimensional gait analysis; and recording of electromyographic (EMG) activity of the S, G, and tibialis anterior and extensor hallucis lungus muscles were also performed.

RESULTS

Only KT had significant effects on spasticity (p < 0.05), clonus (p < 0.001) and COP movements (p < 0.05), kinematic gait parameters (p < 0.001), and EMG activity (p < 0.001). Comparison between ST and KT improvements pointed out significant differences as concerns ROM (p < 0.001), spasticity (p < 0.001), clonus (p < 0.001), pain (p < 0.001), COP parameters (p < 0.05), and most kinematic gait data (p < 0.05).

DISCUSSION

Short-term application of KT reduces spasticity and pain and improves balance and gait in chronic SCI subjects. Although these data are promising, they require confirmation in a larger cohort of patients.

Several practical issues toward implementing myoelectric pattern recognition for stroke rehabilitation

High density surface electromyogram (sEMG) recording and pattern recognition techniques have demonstrated that substantial motor control information can be extracted from neurologically impaired muscles. In this study, a series of pattern recognition parameters were investigated in classification of 20 different movements involving the affected limb of 12 chronic stroke subjects. The experimental results showed that classification performance could be improved with spatial filtering and be maintained with a limited number of electrodes. It was also found that appropriate adjustment of analysis window length, sampling rate, and high-pass cut-off frequency in sEMG conditioning and processing would be potentially useful in reducing computational cost and meanwhile ensuring classification performance. The quantitative analyses are useful for practical myoelectric control toward improved stroke rehabilitation.

A survey on robotic devices for upper limb rehabilitation

The existing shortage of therapists and caregivers assisting physically disabled individuals at home is expected to increase and become serious problem in the near future. The patient population needing physical rehabilitation of the upper extremity is also constantly increasing. Robotic devices have the potential to address this problem as noted by the results of recent research studies. However, the availability of these devices in clinical settings is limited, leaving plenty of room for improvement. The purpose of this paper is to document a review of robotic devices for upper limb rehabilitation including those in developing phase in order to provide a comprehensive reference about existing solutions and facilitate the development of new and improved devices. In particular the following issues are discussed: application field, target group, type of assistance, mechanical design, control strategy and clinical evaluation. This paper also includes a comprehensive, tabulated comparison of technical solutions implemented in various systems.

Synergy analysis as a tool to design and assess an effective stroke rehabilitation

The poor rehabilitation success rate, including the cases of ineffective and detrimental adaptations, make stroke a leading cause of disability. Thus, it is essential to recognize the mechanisms driving healthy motor recovery to improve such rate. Stroke alters the Synergy Architecture (SA), the modular muscle control system. So SA analysis may constitute a powerful tool to design and assess rehabilitation procedures. However, current impairment scales do not consider the patient's neuromuscular state. To gain insights into this hypothesis, we recorded multiple myoelectric signals from upper-limb muscles, in healthy subjects, while executing a set of common rehabilitation exercises. We found that SA reveals optimized motor control strategies and the positive effects of the use of visual feedback (VF) on motor control. Furthermore we demonstrate that the right and left arm's SA share the basic structure within the same subject, so we propose using the unaffected limb's SA as a reference motion pattern to be reached through rehabilitation.

Complexity analysis of EMG signals for patients after stroke during robot-aided rehabilitation training using fuzzy approximate entropy

The paper presents a novel viewpoint to monitor the motor function improvement during a robot-aided rehabilitation training. Eight chronic poststroke subjects were recruited to attend the 20-session training, and in each session, subjects were asked to perform voluntary movements of elbow flexion and extension together with the robotic system. The robotic system was continuously controlled by the electromyographic (EMG) signal from the affected triceps. Fuzzy approximate entropy (fApEn) was applied to investigate the complexity of the EMG segment, and maximum voluntary contraction (MVC) during elbow flexion and extension was applied to reflect force generating capacity of the affected muscles. The results showed that the group mean fApEn of EMG signals from triceps and biceps increased significantly after the robot-aided rehabilitation training . There was also significant increase in maximum voluntary flexion and extension torques after the robot-aided rehabilitation training . There was significant correlation between fApEn of agonist and MVC , which implied that the increase of motorneuron number is one of factors that may explain the increase in muscle strength. These findings based on fApEn of the EMG signals expand the existing interpretation of training-induced function improvement in patients after stroke, and help us to understand the neurological change induced by the robot-aided rehabilitation training.

The effects of post-stroke upper-limb training with an electromyography (EMG)-driven hand robot

Loss of hand function and finger dexterity are main disabilities in the upper limb after stroke. An electromyography (EMG)-driven hand robot had been developed for post-stroke rehabilitation training. The effectiveness of the hand robot assisted whole upper limb training was investigated on persons with chronic stroke (n=10) in this work. All subjects attended a 20-session training (3-5times/week) by using the hand robot to practice object grasp/release and arm transportation tasks. Significant motor improvements were observed in the Fugl-Meyer hand/wrist and shoulder/elbow scores (p<0.05), and also in the Action Research Arm Test and Wolf Motor Function Test (p<0.05). Significant reduction in spasticity of the fingers as was measured by the Modified Ashworth Score (p<0.05). The training improved the muscle co-ordination between the antagonist muscle pair (flexor digitorum (FD) and extensor digitorum (ED)), associated with a significant reduction in the ED EMG level (p<0.05) and a significant decrease of ED and FD co-contraction during the training (p<0.05); the excessive muscle activities in the biceps brachii were also reduced significantly after the training (p<0.05).