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

Recent applications of EEG-based brain-computer-interface in the medical field

Brain-computer interfaces (BCIs) represent an emerging technology that facilitates direct communication between the brain and external devices. In recent years, numerous review articles have explored various aspects of BCIs, including their fundamental principles, technical advancements, and applications in specific domains. However, these reviews often focus on signal processing, hardware development, or limited applications such as motor rehabilitation or communication. This paper aims to offer a comprehensive review of recent electroencephalogram (EEG)-based BCI applications in the medical field across 8 critical areas, encompassing rehabilitation, daily communication, epilepsy, cerebral resuscitation, sleep, neurodegenerative diseases, anesthesiology, and emotion recognition. Moreover, the current challenges and future trends of BCIs were also discussed, including personal privacy and ethical concerns, network security vulnerabilities, safety issues, and biocompatibility.

How Can Robotic Devices Help Clinicians Determine the Treatment Dose for Post-Stroke Arm Paresis?

Upper limb training dose after stroke is usually quantified by time and repetitions. This study analyzed upper limb motor training dose in stroke participants (N = 36) using a more comprehensive approach. Participants, classified by initial motor severity (severe/moderate/mild) and recovery trajectory (good/poor), received daily robotic and occupational therapy. Treatment dose was reported using a multidimensional framework. Fugl-Meyer Assessment (FMA) score and robot-derived kinematic parameters (reach distance (cm), velocity (cm/s), accuracy (cm) and smoothness (number of velocity peaks)) were analyzed pre- and post-intervention. FMA scores (mean (SD)) improved significantly post-intervention in severe (+11 (12) pts; p < 0.001) and moderate (+13 (6) pts; p ≤ 0.01) impairment groups. In the severe group, good recoverers showed greater improvement (+18 (12) pts) than poor recoverers (+4 (4) pts). Despite similar robotic therapy duration (34 min/session) and number of movements (600-900/session) between good and poor recoverers, both groups experienced very different therapeutic plans in the use of physical modalities: good recoverers gradually moved from assisted to the unassisted then resisted modality. Kinematic analysis showed distinct patterns of motor improvement across severity levels, ranging from quantitative (reach distance/velocity) to qualitative (accuracy/smoothness) changes. This approach provides a more accurate description of the therapeutic dose by characterizing the movements actually performed and can help personalize rehabilitation strategies.

An interactive soft robotic hand-task training system with wireless task boards and daily objects on post-stroke rehabilitation

We have developed an interactive system comprising a soft wearable robot hand and a wireless task board, facilitating the interaction between the hand and regular daily objects for task-oriented training in stroke rehabilitation. A ring-reinforced soft actuator (RSA) to accommodate different hand sizes and enable flexion and extension movements was introduced in this paper. Individually controlled finger actuators assist stroke patients during various grasping tasks. A wireless task board was developed to support the training, allowing for the placement of training objects and seamless interaction with the soft robotic hand. Evaluation with seven stroke subjects shows significant improvements in upper limb functions (FMA), hand-motor abilities (ARAT, BBT), and maximum grip strengths after 20 sessions of this task-oriented training. These improvements were observed to persist for at least 3 months post-training. The results demonstrate its potential to enhance stroke rehabilitation and promote hand-motor recovery. This lightweight, user-friendly interactive system facilitates frequent hand practice and easily integrates into regular rehabilitation therapy routines.

Clinical validation of an individualized auto-adaptative serious game for combined cognitive and upper limb motor robotic rehabilitation after stroke

BACKGROUND

Intensive rehabilitation through challenging and individualized tasks are recommended to enhance upper limb recovery after stroke. Robot-assisted therapy (RAT) and serious games could be used to enhance functional recovery by providing simultaneous motor and cognitive rehabilitation.

OBJECTIVE

The aim of this study is to clinically validate the dynamic difficulty adjustment (DDA) mechanism of ROBiGAME, a robot serious game designed for simultaneous rehabilitation of motor impairments and hemispatial neglect.

METHODS

A proof of concept, with 24 participants in subacute and chronic stroke, was conducted using a 5-day protocol (two days were dedicated to assessment and three days to consecutive training sessions). Participants performed three consecutive ROBiGAME sessions during which overall task difficulty was determined through simultaneous DDA of motor and attentional parameters. Relationships between clinical and robotic assessment scores with respective task-difficulty parameters were analyzed using a multivariate regression model and a principal component analysis.

RESULTS

Game difficulty rapidly (within approximately thirty minutes) auto-adapted to match individual impairment levels. The relationship between task-difficulty parameters with motor (Fugl Meyer Assessment: r = 0.84 p < 0.05) and with attentional impairments (Bells test total omissions: r = 0.617 p < 0.05) showed that task-difficulty during RAT adapted to each participant's degree of impairment. Principal component analysis identified two data subsets determining overall task-difficulty, one subset for motor and the other for cognitive functional evaluation scores with respective task-difficulty parameters.

CONCLUSIONS

This proof of concept clinically validated a DDA mechanism and showed how task-difficulty adequately adapted to match individual degrees of impairment during RAT after stroke. ROBiGAME provided simultaneous motor and attentional exercises with parameters determining task-difficulty strongly related with respective clinical and robotic evaluation scores. Individualized levels of game difficulty and rapid adjustment of the system suggest implementation in clinical practice. Registry number This study was registered at ClinicalTrials.gov (NCT02543424).

Control Method of Upper Limb Rehabilitation Exoskeleton for Better Assistance: A Comprehensive Review

The upper limb rehabilitation exoskeleton is a robotic‐arm‐like device that fits the human upper limb and assists in movement, having the potential to be widely used in medical practice. The control method of the upper limb rehabilitation exoskeleton system is an important factor that affects the effectiveness of its rehabilitation training assistance and is also the focus of research in this field. In this article, we divide the control method of the upper limb rehabilitation exoskeleton into two levels, the high‐level control mode (including passive mode, active mode, and ANN, etc.) and the low‐level controller. The design of the controller aims to meet the requirements of the control mode but faces difficulties such as complex dynamic models of the system, unknown external disturbances, and motion intention recognition to achieve accurate motion trajectory tracking and flexible human–robot interaction. Based on relevant literature in the field of upper limb rehabilitation exoskeleton control methods in recent years, we analyze the rehabilitation training control modes that researchers aim to achieve, as well as the work they have done in controller design to achieve these control modes. We also propose potential research directions for achieving better exoskeleton‐assisted training effects.

Robotics in Physical Rehabilitation: Systematic Review

As the global prevalence of motor disabilities continues to rise, there is a pressing need for advanced solutions in physical rehabilitation. This systematic review examines the progress and challenges of implementing robotic technologies in the motor rehabilitation of patients with physical disabilities. The integration of robotic technologies such as exoskeletons, assistive training devices, and brain-computer interface systems holds significant promise for enhancing functional recovery and patient autonomy. The review synthesizes findings from the most important studies, focusing on the clinical effectiveness of robotic interventions in comparison to traditional rehabilitation methods. The analysis reveals that robotic therapies can significantly improve motor function, strength, co-ordination, and dexterity. Robotic systems also support neuroplasticity, enabling patients to relearn lost motor skills through precise, controlled, and repetitive exercises. However, the adoption of these technologies is hindered by high costs, the need for specialized training, and limited accessibility. Key insights from the review highlight the necessity of personalizing robotic therapies to meet individual patient needs, alongside addressing technical, economic, social, and cultural barriers. The review also underscores the importance of continued research to optimize these technologies and develop effective implementation strategies. By overcoming these challenges, robotic technologies can revolutionize motor rehabilitation, improving quality of life and social integration for individuals with motor disabilities.

Robotic task specific training for upper limb neurorehabilitation: a mixed methods feasibility trial reporting achievable dose

PURPOSE

Robotic devices for upper-limb neurorehabilitation allow an increase in intensity of practice, often relying on video game-based training strategies with limited capacity to individualise training and integrate functional training. This study shows the development of a robotic Task Specific Training (TST) protocol and evaluate the achieved dose.

MATERIALS AND METHODS

Mixed-method study. A 3D robotic device for the upper limb, was made available to therapists for use during neurorehabilitation sessions. A first phase allowed clinicians to define a dedicated session protocol for TST. In a second phase the protocol was applied and the achieved dose was measured.

RESULTS

First phase (N = 5): a specific protocol, using deweighting for assessment, followed by customised passive movements and then active movement practice was developed. Second phase: the protocol was successfully applied with all participants (N = 10). Intervention duration: 4.5 ± 0.8 weeks, session frequency: 1.4 ± 0.2sessions/week, session length: 42 ± 9mins, session density: 39 ± 13%, intensity: 214 ± 84 movements/session, difficulty: dn = 0.77 ± 0.1 (normalised reaching distance) and Ɵ = 6.3 ± 23° (transverse reaching angle). Sessions' density and intensity were consistent across participants but clear differences of difficulty were observed. No changes in metrics were observed over the intervention.

CONCLUSIONS

Robotic systems can support TST with high therapy intensity by modulating the practice difficulty to participants' needs and capabilities.

Advanced rehabilitation in ischaemic stroke research

At present, due to the rapid progress of treatment technology in the acute phase of ischaemic stroke, the mortality of patients has been greatly reduced but the number of disabled survivors is increasing, and most of them are elderly patients. Physicians and rehabilitation therapists pay attention to develop all kinds of therapist techniques including physical therapy techniques, robot-assisted technology and artificial intelligence technology, and study the molecular, cellular or synergistic mechanisms of rehabilitation therapies to promote the effect of rehabilitation therapy. Here, we discussed different animal and in vitro models of ischaemic stroke for rehabilitation studies; the compound concept and technology of neurological rehabilitation; all kinds of biological mechanisms of physical therapy; the significance, assessment and efficacy of neurological rehabilitation; the application of brain-computer interface, rehabilitation robotic and non-invasive brain stimulation technology in stroke rehabilitation.

Task-Oriented Training by a Personalized Electromyography-Driven Soft Robotic Hand in Chronic Stroke: A Randomized Controlled Trial

BACKGROUND

Intensive task-oriented training has shown promise in enhancing distal motor function among patients with chronic stroke. A personalized electromyography (EMG)-driven soft robotic hand was developed to assist task-oriented object-manipulation training effectively. Objective. To compare the effectiveness of task-oriented training using the EMG-driven soft robotic hand.

METHODS

A single-blinded, randomized controlled trial was conducted with 34 chronic stroke survivors. The subjects were randomly assigned to the Hand Task (HT) group (n = 17) or the control (CON) group (n = 17). The HT group received 45 minutes of task-oriented training by manipulating small objects with the robotic hand for 20 sessions, while the CON group received 45 minutes of hand-functional exercises without objects using the same robot. Fugl-Meyer assessment (FMA-UE), Action Research Arm Test (ARAT), Modified Ashworth Score (MAS), Box and Block test (BBT), Maximum Grip Strength, and active range of motion (AROM) of fingers were assessed at baseline, after intervention, and 3 months follow-up. The muscle co-contraction index (CI) was analyzed to evaluate the session-by-session variation of upper limb EMG patterns.

RESULTS

The HT group showed more significant improvement in FMA-UE (wrist/hand, shoulder/elbow) compared to the CON group (P < .05). At 3-month follow-up, the HT group demonstrated significant improvements in FMA-UE, ARAT, BBT, MAS (finger), and AROMs (P < .05). The HT group exhibited a more significant decrease in muscle co-contractions compared to the CON group (P < .05).

CONCLUSIONS

EMG-driven task-oriented training with the personalized soft robotic hand was a practical approach to improving motor function and muscle coordination.

CLINICAL TRIAL REGISTRY NAME

Soft Robotic Hand System for Stroke Rehabilitation.

CLINICAL TRIAL REGISTRATION-URL

https://clinicaltrials.gov/.

UNIQUE IDENTIFIER

NCT03286309.

Direct Comparisons of Upper-Limb Motor Learning Performance Among Three Types of Haptic Guidance With Non-Assisted Condition in Spiral Drawing Task

In robot-assisted rehabilitation, it is unclear which type of haptic guidance is effective for regaining motor function because of the lack of direct comparisons among multiple types of haptic guidance. The objective of this study was to investigate the effects of different types of haptic guidance on upper limb motor learning in a spiral drawing task. Healthy young participants performed two experiments in which they practiced the drawing movement using a robotic manipulandum with a virtual wall (Path guidance), running direction pushing and virtual wall (Path & Push guidance), restriction to the target movement (Target guidance), or without haptic guidance (Free guidance). Experiment 1 compared the learning effects of the four types of guidance. Experiment 2 investigated the effects of pre-learning with Path, Path & Push, or Target guidance on post-learning with Free guidance. In Experiment 1, Free guidance demonstrated the greatest learning effect, followed by Path guidance, which showed a significantly greater improvement in task performance than the other two types of guidance. In Experiment 2, the type of pre-learning did not influence post-learning with Free guidance. The results suggested that learning with Path guidance showed a slightly slower but comparable effect to Free guidance and was the most effective among the three types of haptic guidance. The superiority of Path guidance over other haptic guidance was interpreted within the framework of error-based learning, in which the intensity of sensory feedback and voluntary motor control play important roles.

Robot-assisted support combined with electrical stimulation for the lower extremity in stroke patients: a systematic review

Objective. The incidence of stroke rising, leading to an increased demand for rehabilitation services. Literature has consistently shown that early and intensive rehabilitation is beneficial for stroke patients. Robot-assisted devices have been extensively studied in this context, as they have the potential to increase the frequency of therapy sessions and thereby the intensity. Robot-assisted systems can be combined with electrical stimulation (ES) to further enhance muscle activation and patient compliance. The objective of this study was to review the effectiveness of ES combined with all types of robot-assisted technology for lower extremity rehabilitation in stroke patients.Approach. A thorough search of peer-reviewed articles was conducted. The quality of the included studies was assessed using a modified version of the Downs and Black checklist. Relevant information regarding the interventions, devices, study populations, and more was extracted from the selected articles.Main results. A total of 26 articles were included in the review, with 23 of them scoring at least fair on the methodological quality. The analyzed devices could be categorized into two main groups: cycling combined with ES and robots combined with ES. Overall, all the studies demonstrated improvements in body function and structure, as well as activity level, as per the International Classification of Functioning, Disability, and Health model. Half of the studies in this review showed superiority of training with the combination of robot and ES over robot training alone or over conventional treatment.Significance. The combination of robot-assisted technology with ES is gaining increasing interest in stroke rehabilitation. However, the studies identified in this review present challenges in terms of comparability due to variations in outcome measures and intervention protocols. Future research should focus on actively involving and engaging patients in executing movements and strive for standardization in outcome values and intervention protocols.

Therapeutic robots for post-stroke rehabilitation

Stroke is a prevalent, severe, and disabling health-care issue on a global scale, inevitably leading to motor and cognitive deficits. It has become one of the most significant challenges in China, resulting in substantial social and economic burdens. In addition to the medication and surgical interventions during the acute phase, rehabilitation treatment plays a crucial role in stroke care. Robotic technology takes distinct advantages over traditional physical therapy, occupational therapy, and speech therapy, and is increasingly gaining popularity in post-stroke rehabilitation. The use of rehabilitation robots not only alleviates the workload of healthcare professionals but also enhances the prognosis for specific stroke patients. This review presents a concise overview of the application of therapeutic robots in post-stroke rehabilitation, with particular emphasis on the recovery of motor and cognitive function.

Personalized robots for long-term telerehabilitation after stroke: a perspective on technological readiness and clinical translation

Stroke rehabilitation, which demands consistent, intensive, and adaptable intervention in the long term, faced significant challenges due to the COVID-19 pandemic. During this time, telerehabilitation emerged as a noteworthy complement to traditional rehabilitation services, offering the convenience of at-home care delivery and overcoming geographical and resource limitations. Self-help rehabilitation robots deliver repetitive and intensive physical assistance, thereby alleviating the labor burden. However, robots have rarely demonstrated long-term readiness for poststroke telerehabilitation services. The transition from research trials to general clinical services presents several challenges that may undermine the rehabilitative gains observed in these studies. This perspective discusses the technological readiness of personal use robots in the context of telerehabilitation and identifies the potential challenges for their clinical translation. The goal is to leverage technology to seamlessly integrate it into standard clinical workflows, ultimately enhancing the outcomes of stroke rehabilitation.

Effect of the VR-guided grasping task on the brain functional network

Virtual reality (VR) technology has been demonstrated to be effective in rehabilitation training with the assistance of VR games, but its impact on brain functional networks remains unclear. In this study, we used functional near-infrared spectroscopy imaging to examine the brain hemodynamic signals from 18 healthy participants during rest and grasping tasks with and without VR game intervention. We calculated and compared the graph theory-based topological properties of the brain networks using phase locking values (PLV). The results revealed significant differences in the brain network properties when VR games were introduced compared to the resting state. Specifically, for the VR-guided grasping task, the modularity of the brain network was significantly higher than the resting state, and the average clustering coefficient of the motor cortex was significantly lower compared to that of the resting state and the simple grasping task. Correlation analyses showed that a higher clustering coefficient, local efficiency, and modularity were associated with better game performance during VR game participation. This study demonstrates that a VR game task intervention can better modulate the brain functional network compared to simple grasping movements and may be more beneficial for the recovery of grasping abilities in post-stroke patients with hand paralysis.

Implementation of a robot-mediated upper limb rehabilitation protocol for a customized treatment after stroke: A retrospective analysis

BACKGROUND

Many authors have emphasized the need for individualized treatments in rehabilitation, but no tailored robotic rehabilitation protocol for stroke patients has been established yet.

OBJECTIVE

To evaluate the effectiveness of a robot-mediated upper limb rehabilitation protocol based on clinical assessment for customized treatment of stroke patients.

METHODS

Clinical data from 81 patients with subacute stroke, undergoing an upper limb robot-mediated rehabilitation, were analyzed retrospectively. 49 patients were treated using a customized robotic protocol (experimental group, EG) based on a clinically guided flowchart, while 32 were treated without it (control group, CG). Fugl-Meyer Assessment for Upper Extremity (FMA-UE), Motricity Index (MI), modified Barthel Index (mBI) and Numerical Rating Scale (NRS) measured before (T0) and after (T1) rehabilitation intervention were used as clinical outcomes.

RESULTS

There was statistically significant improvement in both groups in terms of FMA-UE, MI, and mBI, while no change in NRS. Intergroup analysis showed significantly greater improvement of the FMA-UE (P = 0.002) and MI (P < 0.001) in the EG, compared with the CG.

CONCLUSION

The implementation of our robotic protocol for customized treatment of stroke patients yielded greater recovery in upper limb motor function and strength over robotic treatment without a defined protocol.

Bilateral upper limb robot-assisted rehabilitation improves upper limb motor function in stroke patients: a study based on quantitative EEG

BACKGROUND

Upper limb dysfunction after stroke seriously affects quality of life. Bilateral training has proven helpful in recovery of upper limb motor function in these patients. However, studies evaluating the effectiveness of bilateral upper limb robot-assisted training on improving motor function and quality of life in stroke patients are lacking. Quantitative electroencephalography (EEG) is non-invasive, simple, and monitors cerebral cortical activity, which can be used to evaluate the effectiveness of interventions. In this study, EEG was used to evaluate the effect of end-drive bilateral upper extremity robot-assisted training on upper extremity functional recovery in stroke patients.

METHODS

24 stroke patients with hemiplegia were randomly divided into a conventional training (CT, n = 12) group or a bilateral upper limb robot-assisted training (BRT, n = 12) group. All patients received 60 min of routine rehabilitation treatment including rolling, transferring, sitting, standing, walking, etc., per day, 6 days a week, for three consecutive weeks. The BRT group added 30 min of bilateral upper limb robot-assisted training per day, while the CT group added 30 min of upper limb training (routine occupational therapy) per day, 6 days a week, for 3  weeks. The primary outcome index to evaluate upper limb motor function was the Fugl-Meyer functional score upper limb component (FMA-UE), with the secondary outcome of activities of daily living (ADL), assessed by the modified Barthel index (MBI) score. Quantitative EEG was used to evaluate functional brain connectivity as well as alpha and beta power current source densities of the brain.

RESULTS

Significant (p < 0.05) within-group differences were found in FMA-UE and MBI scores for both groups after treatment. A between-group comparison indicated the MBI score of the BRT group was significantly different from that of the CT group, whereas the FMA-UE score was not significantly different from that of the CT group after treatment. The differences of FMA-UE and MBI scores before and after treatment in the BRT group were significantly different as compared to the CT group. In addition, beta rhythm power spectrum energy was higher in the BRT group than in the CT group after treatment. Functional connectivity in the BRT group, under alpha and beta rhythms, was significantly increased in both the bilateral frontal and limbic lobes as compared to the CT group.

CONCLUSIONS

BRT outperformed CT in improving ADL in stroke patients within three months, and BRT facilitates the recovery of upper limb function by enhancing functional connectivity of the bilateral cerebral hemispheres.

Psychophysiological responses to eye contact with a humanoid robot: Impact of perceived intentionality

Eye contact with a social robot has been shown to elicit similar psychophysiological responses to eye contact with another human. However, it is becoming increasingly clear that the attention- and affect-related psychophysiological responses differentiate between direct (toward the observer) and averted gaze mainly when viewing embodied faces that are capable of social interaction, whereas pictorial or pre-recorded stimuli have no such capability. It has been suggested that genuine eye contact, as indicated by the differential psychophysiological responses to direct and averted gaze, requires a feeling of being watched by another mind. Therefore, we measured event-related potentials (N170 and frontal P300) with EEG, facial electromyography, skin conductance, and heart rate deceleration responses to seeing a humanoid robot's direct versus averted gaze, while manipulating the impression of the robot's intentionality. The results showed that the N170 and the facial zygomatic responses were greater to direct than to averted gaze of the robot, and independent of the robot's intentionality, whereas the frontal P300 responses were more positive to direct than to averted gaze only when the robot appeared intentional. The study provides further evidence that the gaze behavior of a social robot elicits attentional and affective responses and adds that the robot's seemingly autonomous social behavior plays an important role in eliciting higher-level socio-cognitive processing.

The effect of sequential combination of mirror therapy and robot-assisted therapy on motor function, daily function, and self-efficacy after stroke

Robot-assisted therapy and mirror therapy are both effective in promoting upper limb function after stroke and combining these two interventions might yield greater therapeutic effects. We aimed to examine whether using mirror therapy as a priming strategy would augment therapeutic effects of robot-assisted therapy. Thirty-seven chronic stroke survivors (24 male/13 female; age = 49.8 ± 13.7 years) were randomized to receive mirror therapy or sham mirror therapy prior to robot-assisted therapy. All participants received 18 intervention sessions (60 min/session, 3 sessions/week). Outcome measures were evaluated at baseline and after the 18-session intervention. Motor function was assessed using Fugl-Meyer Assessment and Wolf Motor Function Test. Daily function was assessed using Nottingham Extended Activities of Daily Living Scale. Self-efficacy was assessed using Stroke Self-Efficacy Questionnaires and Daily Living Self-Efficacy Scale. Data was analyzed using mixed model analysis of variance. Both groups demonstrated statistically significant improvements in measures of motor function and daily function, but no significant between-group differences were found. Participants who received mirror therapy prior to robot-assisted therapy showed greater improvements in measures of self-efficacy, compared with those who received sham mirror therapy. Our findings suggest that sequentially combined mirror therapy with robot-assisted therapy could be advantageous for enhancing self-efficacy post-stroke.Trial registration: ClinicalTrials.gov Identifier: NCT03917511. Registered on 17/04/2019, https://clinicaltrials.gov/ct2/show/ NCT03917511.

Effectiveness of task-specific training using assistive devices and task-specific usual care on upper limb performance after stroke: a systematic review and meta-analysis

PURPOSE

Task-specific rehabilitation is a key indicator for successful rehabilitation to improve the upper limb performance after stroke. Assistive robotic and non-robotic devices are emerging to provide rehabilitation therapy; however, the effectiveness of task-specific training programs using assistive training devices compared with task-specific usual care training has not been summarized yet. Therefore, the effectiveness of task-specific training using assistive arm devices (TST-AAD) compared with task-specific usual care (TSUC) on the upper limb performance of patients with a stroke was investigated. To assess task specificity, a set of criteria was proposed: participation, program, relevant, repeated, randomized, reconstruction and reinforced.

MATERIALS AND METHODS

Out of 855 articles, 17 fulfilled the selection criteria. A meta-analysis was performed on the Fugl-Meyer Assessment scores in the subacute and chronic stages after stroke and during follow-up.

RESULTS AND CONCLUSION

Both TST-AAD and TSUC improved the upper limb performance after stroke. In the sub-acute phase after stroke, TST-AAD was more effective than TSUC in reducing the upper limb impairment, although findings were based on only three studies. In the chronic phase, TST-AAD and TSUC showed similar effectiveness. No differences between the two types of training were found at the follow-up measurements. Future studies should describe training, device usage and criteria of task specificity in a standardized way to ease comparison.Implications for rehabilitationArm or hand function is often undertreated in stroke patients, assistive training devices may be able to improve the upper limb performance.Task-specific training using assistive devices is effective in improving the upper limb performance after stroke.Task-specific training using assistive devices seems to be more effective in reducing impairment compared with task specific usual care in the subacute phase after stroke, but they are equally effective in the chronic phase of stroke.

Instrumented Upper Limb Functional Assessment Using a Robotic Exoskeleton: Normative References Intervals

Upper-limb rehabilitation exoskeletons offer a valuable solution to support and enhance the rehabilitation path of neural-injured patients. Such devices are usually equipped with a network of sensors that can be exploited to evaluate and monitor the performances of the users. In this work, we assess the normality ranges of different motor-performance indicators on a group of 15 healthy participants, computed with the benchmark toolbox of AGREE, an upper limb motorized exoskeleton. The toolbox implements a benchmarking scheme for the evaluation of the upper limb, used to test anterior reaching at rest position height and hand-to-mouth motor skills. We selected kinematic and electromyography performance indicators to assess the different motor abilities. We performed a pilot evaluation on three neurological patients, to verify if the AGREE benchmark toolbox was able to distinguish patients from healthy subjects on the basis of the selected performance indicators. Through a comparison between results obtained by the healthy and the small group of motor-impaired users, we successfully calculated the normality ranges for the selected performance indicators, and we pilot-showed how data gathered from AGREE can be used to evaluate the current status of the patients.

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.

Initial Testing of Robotic Exoskeleton Hand Device for Stroke Rehabilitation

The preliminary test results of a novel robotic hand rehabilitation device aimed at treatment for the loss of motor abilities in the fingers and thumb due to stroke are presented. This device has been developed in collaboration with physiotherapists who regularly treat individuals who have suffered from a stroke. The device was tested on healthy adults to ensure comfort, user accessibility, and repeatability for various hand sizes in preparation for obtaining permission from regulatory bodies and implementing the design in a full clinical trial. Trials were conducted with 52 healthy individuals ranging in age from 19 to 93 with an average age of 58. A comfort survey and force data ANOVA were performed to measure hand motions and ensure the repeatability and accessibility of the system. Readings from the force sensor (p < 0.05) showed no significant difference between repetitions for each participant. All subjects considered the device comfortable. The device scored a mean comfort value of 8.5/10 on all comfort surveys and received the approval of all physiotherapists involved. The device has satisfied all design specifications, and the positive results of the participants suggest that it can be considered safe and reliable. It can therefore be moved forward for clinical trials with post-stroke users.

Exoskeleton-Assisted Anthropomorphic Movement Training for the Upper Limb After Stroke: The EAMT Randomized Trial

BACKGROUND

Robot-assisted arm training is generally delivered in the robot-like manner of planar or mechanical 3-dimensional movements. It remains unclear whether integrating upper extremity (UE) natural coordinated patterns into a robotic exoskeleton can improve outcomes. The study aimed to compare conventional therapist-mediated training to the practice of human-like gross movements derived from 5 typical UE functional activities managed with exoskeletal assistance as needed for patients after stroke.

METHODS

In this randomized, single-blind, noninferiority trial, patients with moderate-to-severe UE motor impairment due to subacute stroke were randomly assigned (1:1) to receive 20 sessions of 45-minute exoskeleton-assisted anthropomorphic movement training or conventional therapy. Treatment allocation was masked from independent assessors, but not from patients or investigators. The primary outcome was the change in the Fugl-Meyer Assessment for Upper Extremity from baseline to 4 weeks against a prespecified noninferiority margin of 4 points. Superiority would be tested if noninferiority was demonstrated. Post hoc subgroup analyses of baseline characteristics were performed for the primary outcome.

RESULTS

Between June 2020 and August 2021, totally 80 inpatients (67 [83.8%] males; age, 51.9±9.9 years; days since stroke onset, 54.6±38.0) were enrolled, randomly assigned to the intervention, and included in the intention-to-treat analysis. The mean Fugl-Meyer Assessment for Upper Extremity change in exoskeleton-assisted anthropomorphic movement training (14.73 points; [95% CI, 11.43-18.02]) was higher than that of conventional therapy (9.90 points; [95% CI, 8.15-11.65]) at 4 weeks (adjusted difference, 4.51 points [95% CI, 1.13-7.90]). Moreover, post hoc analysis favored the patient subgroup (Fugl-Meyer Assessment for Upper Extremity score, 23-38 points) with moderately severe motor impairment.

CONCLUSIONS

Exoskeleton-assisted anthropomorphic movement training appears to be effective for patients with subacute stroke through repetitive practice of human-like movements. Although the results indicate a positive sign for exoskeleton-assisted anthropomorphic movement training, further investigations into the long-term effects and paradigm optimization are warranted.

REGISTRATION

URL: https://www.chictr.org.cn; Unique identifier: ChiCTR2100044078.

Effects of a wearable sensor-based virtual reality game on upper-extremity function in patients with stroke

BACKGROUND

PABLO is a virtual reality game where a motion sensor system is used. Few studies have investigated the effects of the PABLO system in stroke rehabilitation. We investigated the effects of upper-extremity virtual reality training with the PABLO system in patients with stroke.

METHODS

Stroke patients were randomly assigned to the virtual reality (n = 19) or standard rehabilitation groups (n = 18). Total of 18 sessions were conducted twice per week. The primary outcome measure was the Fugl-Meyer Assessment-Upper Extremity subscale. Secondary outcome measures included the active ranges of motion of the shoulder and elbow, the box and block test, hand grip strength, and the Stroke Impact Scale. Enjoyment of activities and side effects were also recorded.

FINDINGS

No difference was observed between two groups in primary outcome. Virtual reality group exhibited greater improvements in the hand dexterity between groups (p = .05). In active motion, virtual reality group showed greater improvement in shoulder flexion between groups (p = .03). Virtual reality group also showed greater improvements in elbow pronation between groups (p = .03). The groups differed in their assessments of how enjoyment the rehabilitation activities were found (p = .01). No significant differences between groups were observed in any other tests.

INTERPRETATION

Interventions based on the PABLO virtual reality system improved upper extremity hand function, shoulder and elbow movements, and elicited a higher degree of enjoyment from study participants, than did traditional treatment.

TRIALS REGISTRATION

The study protocol was registered at ClinicalTrials.gov PRS (No.NCT04296032).

Control strategies used in lower limb exoskeletons for gait rehabilitation after brain injury: a systematic review and analysis of clinical effectiveness

BACKGROUND

In the past decade, there has been substantial progress in the development of robotic controllers that specify how lower-limb exoskeletons should interact with brain-injured patients. However, it is still an open question which exoskeleton control strategies can more effectively stimulate motor function recovery. In this review, we aim to complement previous literature surveys on the topic of exoskeleton control for gait rehabilitation by: (1) providing an updated structured framework of current control strategies, (2) analyzing the methodology of clinical validations used in the robotic interventions, and (3) reporting the potential relation between control strategies and clinical outcomes.

METHODS

Four databases were searched using database-specific search terms from January 2000 to September 2020. We identified 1648 articles, of which 159 were included and evaluated in full-text. We included studies that clinically evaluated the effectiveness of the exoskeleton on impaired participants, and which clearly explained or referenced the implemented control strategy.

RESULTS

(1) We found that assistive control (100% of exoskeletons) that followed rule-based algorithms (72%) based on ground reaction force thresholds (63%) in conjunction with trajectory-tracking control (97%) were the most implemented control strategies. Only 14% of the exoskeletons implemented adaptive control strategies. (2) Regarding the clinical validations used in the robotic interventions, we found high variability on the experimental protocols and outcome metrics selected. (3) With high grade of evidence and a moderate number of participants (N = 19), assistive control strategies that implemented a combination of trajectory-tracking and compliant control showed the highest clinical effectiveness for acute stroke. However, they also required the longest training time. With high grade of evidence and low number of participants (N = 8), assistive control strategies that followed a threshold-based algorithm with EMG as gait detection metric and control signal provided the highest improvements with the lowest training intensities for subacute stroke. Finally, with high grade of evidence and a moderate number of participants (N = 19), assistive control strategies that implemented adaptive oscillator algorithms together with trajectory-tracking control resulted in the highest improvements with reduced training intensities for individuals with chronic stroke.

CONCLUSIONS

Despite the efforts to develop novel and more effective controllers for exoskeleton-based gait neurorehabilitation, the current level of evidence on the effectiveness of the different control strategies on clinical outcomes is still low. There is a clear lack of standardization in the experimental protocols leading to high levels of heterogeneity. Standardized comparisons among control strategies analyzing the relation between control parameters and biomechanical metrics will fill this gap to better guide future technical developments. It is still an open question whether controllers that provide an on-line adaptation of the control parameters based on key biomechanical descriptors associated to the patients' specific pathology outperform current control strategies.

Using Features Extracted From Upper Limb Reaching Tasks to Detect Parkinson's Disease by Means of Machine Learning Models

While in the literature there is much interest in investigating lower limbs gait of patients affected by neurological diseases, such as Parkinson's Disease (PD), fewer publications involving upper limbs movements are available. In previous studies, 24 motion signals (the so-called reaching tasks) of the upper limbs of PD patients and Healthy Controls (HCs) were used to extract several kinematic features through a custom-made software; conversely, the aim of our paper is to investigate the possibility to build models-using these features-for distinguishing PD patients from HCs. First, a binary logistic regression and, then, a Machine Learning (ML) analysis was performed by implementing five algorithms through the Knime Analytics Platform. The ML analysis was performed twice: first, a leave-one out-cross validation was applied; then, a wrapper feature selection method was implemented to identify the best subset of features that could maximize the accuracy. The binary logistic regression achieved an accuracy of 90.5%, demonstrating the importance of the maximum jerk during subjects upper limb motion; the Hosmer-Lemeshow test supported the validity of this model (p-value=0.408). The first ML analysis achieved high evaluation metrics by overcoming 95% of accuracy; the second ML analysis achieved a perfect classification with 100% of both accuracy and area under the curve receiver operating characteristics. The top-five features in terms of importance were the maximum acceleration, smoothness, duration, maximum jerk and kurtosis. The investigation carried out in our work has proved the predictive power of the features, extracted from the reaching tasks involving the upper limbs, to distinguish HCs and PD patients.

[Hand robotic devices in neurorehabilitation: A systematic review on the feasibility and effectiveness of stroke rehabilitation]

Robot-assisted therapy is a relatively new intervention, increasingly used in the rehabilitation treatment of stroke patients. It allows to increase the number of repetitions in the performance of specific tasks movements. For this review, a search was carried out between August and October 2021 in the PubMed, Web of Science, Scopus, Cochrane, PEDro and OTseeker databases, selecting a total of six randomized controlled trials where robot-assisted hand therapy was used in stroke rehabilitation. Studies agree that robot-assisted hand therapy has benefits in all phases of stroke rehabilitation that translate into motor and functional improvements of the upper limb and improvements in hemispatial neglect.

Robot-assisted therapy for upper limb paresis after stroke: Use of robotic algorithms in advanced practice

BACKGROUND

Rehabilitation of stroke-related upper limb paresis is a major public health issue.

OBJECTIVE

Robotic systems have been developed to facilitate neurorehabilitation by providing key elements required to stimulate brain plasticity and motor recovery, namely repetitive, intensive, adaptative training with feedback. Although the positive effect of robot-assisted therapy on motor impairments has been well demonstrated, the effect on functional capacity is less certain.

METHOD

This narrative review outlines the principles of robot-assisted therapy for the rehabilitation of post-stroke upper limb paresis.

RESULTS

A paradigm is proposed to promote not only recovery of impairment but also function.

CONCLUSION

Further studies that would integrate some principles of the paradigm described in this paper are needed.

Combined robot motor assistance with neural circuit-based virtual reality (NeuCir-VR) lower extremity rehabilitation training in patients after stroke: a study protocol for a single-centre randomised controlled trial

INTRODUCTION

Improving lower extremity motor function is the focus and difficulty of post-stroke rehabilitation treatment. More recently, robot-assisted and virtual reality (VR) training are commonly used in post-stroke rehabilitation and are considered feasible treatment methods. Here, we developed a rehabilitation system combining robot motor assistance with neural circuit-based VR (NeuCir-VR) rehabilitation programme involving procedural lower extremity rehabilitation with reward mechanisms, from muscle strength training, posture control and balance training to simple and complex ground walking training. The study aims to explore the effectiveness and neurological mechanisms of combining robot motor assistance and NeuCir-VR lower extremity rehabilitation training in patients after stroke.

METHODS AND ANALYSIS

This is a single-centre, observer-blinded, randomised controlled trial. 40 patients with lower extremity hemiparesis after stroke will be recruited and randomly divided into a control group (combined robot assistance and VR training) and an intervention group (combined robot assistance and NeuCir-VR training) by the ratio of 1:1. Each group will receive five 30 min sessions per week for 4 weeks. The primary outcome will be Fugl-Meyer assessment of the lower extremity. Secondary outcomes will include Berg Balance Scale, Modified Ashworth Scale and functional connectivity measured by resting-state functional MRI. Outcomes will be measured at baseline (T0), post-intervention (T1) and follow-ups (T2-T4).

ETHICS, REGISTRATION AND DISSEMINATION

The trial was approved by the Ethics Committee of Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Chinese Traditional Medicine (Grant No. 2019-014). The results will be submitted to a peer-reviewed journal or at a conference.

TRIAL REGISTRATION NUMBER

ChiCTR2100052133.

Identification of inverse kinematic parameters in redundant systems: Towards quantification of inter-joint coordination in the human upper extremity

Understanding and quantifying inter-joint coordination is valuable in several domains such as neurorehabilitation, robot-assisted therapy, robotic prosthetic arms, and control of supernumerary arms. Inter-joint coordination is often understood as a consistent spatiotemporal relation among kinematically redundant joints performing functional and goal-oriented movements. However, most approaches in the literature to investigate inter-joint coordination are limited to analysis of the end-point trajectory or correlation analysis of the joint rotations without considering the underlying task; e.g., creating a desirable hand movement toward a goal as in reaching motions. This work goes beyond this limitation by taking a model-based approach to quantifying inter-joint coordination. More specifically, we use the weighted pseudo-inverse of the Jacobian matrix and its associated null-space to explain the human kinematics in reaching tasks. We propose a novel algorithm to estimate such Inverse Kinematics weights from observed kinematic data. These estimated weights serve as a quantification for spatial inter-joint coordination; i.e., how costly a redundant joint is in its contribution to creating an end-effector velocity. We apply our estimation algorithm to datasets obtained from two different experiments. In the first experiment, the estimated Inverse Kinematics weights pinpoint how individuals change their Inverse Kinematics strategy when exposed to the viscous field wearing an exoskeleton. The second experiment shows how the resulting Inverse Kinematics weights can quantify a robotic prosthetic arm's contribution (or the level of assistance).

A Systematic Review of Virtual Reality and Robot Therapy as Recent Rehabilitation Technologies Using EEG-Brain-Computer Interface Based on Movement-Related Cortical Potentials

To enhance the treatment of motor function impairment, patients' brain signals for self-control as an external tool may be an extraordinarily hopeful option. For the past 10 years, researchers and clinicians in the brain-computer interface (BCI) field have been using movement-related cortical potential (MRCP) as a control signal in neurorehabilitation applications to induce plasticity by monitoring the intention of action and feedback. Here, we reviewed the research on robot therapy (RT) and virtual reality (VR)-MRCP-based BCI rehabilitation technologies as recent advancements in human healthcare. A list of 18 full-text studies suitable for qualitative review out of 322 articles published between 2000 and 2022 was identified based on inclusion and exclusion criteria. We used PRISMA guidelines for the systematic review, while the PEDro scale was used for quality evaluation. Bibliometric analysis was conducted using the VOSviewer software to identify the relationship and trends of key items. In this review, 4 studies used VR-MRCP, while 14 used RT-MRCP-based BCI neurorehabilitation approaches. The total number of subjects in all identified studies was 107, whereby 4.375 ± 6.3627 were patient subjects and 6.5455 ± 3.0855 were healthy subjects. The type of electrodes, the epoch, classifiers, and the performance information that are being used in the RT- and VR-MRCP-based BCI rehabilitation application are provided in this review. Furthermore, this review also describes the challenges facing this field, solutions, and future directions of these smart human health rehabilitation technologies. By key items relationship and trends analysis, we found that motor control, rehabilitation, and upper limb are important key items in the MRCP-based BCI field. Despite the potential of these rehabilitation technologies, there is a great scarcity of literature related to RT and VR-MRCP-based BCI. However, the information on these rehabilitation methods can be beneficial in developing RT and VR-MRCP-based BCI rehabilitation devices to induce brain plasticity and restore motor impairment. Therefore, this review will provide the basis and references of the MRCP-based BCI used in rehabilitation applications for further clinical and research development.

Hand Exoskeleton Design and Human-Machine Interaction Strategies for Rehabilitation

Stroke and related complications such as hemiplegia and disability create huge burdens for human society in the 21st century, which leads to a great need for rehabilitation and daily life assistance. To address this issue, continuous efforts are devoted in human-machine interaction (HMI) technology, which aims to capture and recognize users' intentions and fulfil their needs via physical response. Based on the physiological structure of the human hand, a dimension-adjustable linkage-driven hand exoskeleton with 10 active degrees of freedom (DoFs) and 3 passive DoFs is proposed in this study, which grants high-level synergy with the human hand. Considering the weight of the adopted linkage design, the hand exoskeleton can be mounted on the existing up-limb exoskeleton system, which greatly diminishes the burden for users. Three rehabilitation/daily life assistance modes are developed (namely, robot-in-charge, therapist-in-charge, and patient-in-charge modes) to meet specific personal needs. To realize HMI, a thin-film force sensor matrix and Inertial Measurement Units (IMUs) are installed in both the hand exoskeleton and the corresponding controller. Outstanding sensor-machine synergy is confirmed by trigger rate evaluation, Kernel Density Estimation (KDE), and a confusion matrix. To recognize user intention, a genetic algorithm (GA) is applied to search for the optimal hyperparameters of a 1D Convolutional Neural Network (CNN), and the average intention-recognition accuracy for the eight actions/gestures examined reaches 97.1% (based on K-fold cross-validation). The hand exoskeleton system provides the possibility for people with limited exercise ability to conduct self-rehabilitation and complex daily activities.

Effectiveness of combining robotic therapy and modified constraint-induced movement therapy for moderate to severe upper limb paresis after stroke in subacute phase: Case–control study by propensity score analysis

Introduction:

Robotic assisted therapy and modified constraint-induced movement therapy are used evidence-based approach in stroke rehabilitation. However, there is no study showing a combination of robotic assisted therapy and modified constraint-induced movement therapy (combined therapy) in the subacute phase. This study investigated the effectiveness of combined therapy in stroke patients with moderate to severe upper limb paresis compared with conventional occupational therapy at subacute setting.

Methods:

This research used a case–control study. The intervention group ( n = 15) consisting of patients with moderate to severe upper limb paresis (Brunnstrom recovery stage upper extremity III or IV and above hand III) 4–8 weeks since stroke onset received a combined therapy for 3 weeks (total intervention time: 1440 minutes). The control group ( n = 15) extracted by propensity score matching received a conventional occupational therapy for 4 weeks (total intervention time: 1680–2240 minutes). The primary outcome was the Fugl-Meyer assessment upper limb score change before and after the intervention.

Results:

The intervention group exhibited significantly greater improvement on Fugl-Meyer assessment upper lim change ( p = 0.005).

Conclusion:

In the subacute phase, the combined therapy of robotic assisted therapy and modified constraint-induced movement therapy helped improve upper limb motor function more effectively and efficiently than conventional occupational therapy.

A unified scheme for the benchmarking of upper limb functions in neurological disorders

BACKGROUND

In neurorehabilitation, we are witnessing a growing awareness of the importance of standardized quantitative assessment of limb functions. Detailed assessments of the sensorimotor deficits following neurological disorders are crucial. So far, this assessment has relied mainly on clinical scales, which showed several drawbacks. Different technologies could provide more objective and repeatable measurements. However, the current literature lacks practical guidelines for this purpose. Nowadays, the integration of available metrics, protocols, and algorithms into one harmonized benchmarking ecosystem for clinical and research practice is necessary.

METHODS

This work presents a benchmarking framework for upper limb capacity. The scheme resulted from a multidisciplinary and iterative discussion among several partners with previous experience in benchmarking methodology, robotics, and clinical neurorehabilitation. We merged previous knowledge in benchmarking methodologies for human locomotion and direct clinical and engineering experience in upper limb rehabilitation. The scheme was designed to enable an instrumented evaluation of arm capacity and to assess the effectiveness of rehabilitative interventions with high reproducibility and resolution. It includes four elements: (1) a taxonomy for motor skills and abilities, (2) a list of performance indicators, (3) a list of required sensor modalities, and (4) a set of reproducible experimental protocols.

RESULTS

We proposed six motor primitives as building blocks of most upper-limb daily-life activities and combined them into a set of functional motor skills. We identified the main aspects to be considered during clinical evaluation, and grouped them into ten motor abilities categories. For each ability, we proposed a set of performance indicators to quantify the proposed ability on a quantitative and high-resolution scale. Finally, we defined the procedures to be followed to perform the benchmarking assessment in a reproducible and reliable way, including the definition of the kinematic models and the target muscles.

CONCLUSIONS

This work represents the first unified scheme for the benchmarking of upper limb capacity. To reach a consensus, this scheme should be validated with real experiments across clinical conditions and motor skills. This validation phase is expected to create a shared database of human performance, necessary to have realistic comparisons of treatments and drive the development of new personalized technologies.

Application of 5G network combined with AI robots in personalized nursing in China: A literature review

The medical and healthcare industry is currently developing into digitization. Attributed to the rapid development of advanced technologies such as the 5G network, cloud computing, artificial intelligence (AI), and big data, and their wide applications in the medical industry, the medical model is shifting into an intelligent one. By combining the 5G network with cloud healthcare platforms and AI, nursing robots can effectively improve the overall medical efficacy. Meanwhile, patients can enjoy personalized medical services, the supply and the sharing of medical and healthcare services are promoted, and the digital transformation of the healthcare industry is accelerated. In this paper, the application and practice of 5G network technology in the medical industry are introduced, including telecare, 5G first-aid remote medical service, and remote robot applications. Also, by combining application characteristics of AI and development requirements of smart healthcare, the overall planning, intelligence, and personalization of the 5G network in the medical industry, as well as opportunities and challenges of its application in the field of nursing are discussed. This paper provides references to the development and application of 5G network technology in the field of medical service.

Prediction of balance function for stroke based on EEG and fNIRS features during ankle dorsiflexion

Balance rehabilitation is exceedingly crucial during stroke rehabilitation and is highly related to the stroke patients’ secondary injuries (caused by falling). Stroke patients focus on walking ability rehabilitation during the early stage. Ankle dorsiflexion can activate the brain areas of stroke patients, similar to walking. The combination of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) was a new method, providing more beneficial information. We extracted the event-related desynchronization (ERD), oxygenated hemoglobin (HBO), and Phase Synchronization Index (PSI) features during ankle dorsiflexion from EEG and fNIRS. Moreover, we established a linear regression model to predict Berg Balance Scale (BBS) values and used an eightfold cross validation to test the model. The results showed that ERD, HBO, PSI, and age were critical biomarkers in predicting BBS. ERD and HBO during ankle dorsiflexion and age were promising biomarkers for stroke motor recovery.

Bimanual motor skill learning after stroke: Combining robotics and anodal tDCS over the undamaged hemisphere: An exploratory study

Background

Since a stroke can impair bimanual activities, enhancing bimanual cooperation through motor skill learning may improve neurorehabilitation. Therefore, robotics and neuromodulation with transcranial direct current stimulation (tDCS) are promising approaches. To date, tDCS has failed to enhance bimanual motor control after stroke possibly because it was not integrating the hypothesis that the undamaged hemisphere becomes the major poststroke hub for bimanual control.

Objective

We tested the following hypotheses: (I) In patients with chronic hemiparetic stroke training on a robotic device, anodal tDCS applied over the primary motor cortex of the undamaged hemisphere enhances bimanual motor skill learning compared to sham tDCS. (II) The severity of impairment correlates with the effect of tDCS on bimanual motor skill learning. (III) Bimanual motor skill learning is less efficient in patients than in healthy individuals (HI).

Methods

A total of 17 patients with chronic hemiparetic stroke and 7 healthy individuals learned a complex bimanual cooperation skill on the REAplan® neurorehabilitation robot. The bimanual speed/accuracy trade-off (biSAT), bimanual coordination (biCo), and bimanual force (biFOP) scores were computed for each performance. In patients, real/sham tDCS was applied in a crossover, randomized, double-blind approach.

Results

Compared to sham, real tDCS did not enhance bimanual motor skill learning, retention, or generalization in patients, and no correlation with impairment was noted. The healthy individuals performed better than patients on bimanual motor skill learning, but generalization was similar in both groups.

Conclusion

A short motor skill learning session with a robotic device resulted in the retention and generalization of a complex skill involving bimanual cooperation. The tDCS strategy that would best enhance bimanual motor skill learning after stroke remains unknown.

Clinical trial registration

https://clinicaltrials.gov/ct2/show/NCT02308852, identifier: NCT02308852.

Effects of robotic rehabilitation on recovery of hand functions in acute stroke: A preliminary randomized controlled study

OBJECTIVE

The aim of this study was to investigate the effects of EMG-driven robotic rehabilitation on hand motor functions and daily living activities of patients with acute ischemic stroke.

MATERIALS & METHOD

A preliminary randomized-controlled, single-blind trial rectuited twenty-four patients with acute ischemic stroke (<1 month after cerebrovascular accident) and randomly allocated to experimental group (EG) and control group (CG). Neurophysiological rehabilitation program was performed to both EG and CG for 5 days a week and totally 15 sessions. The EG also received robotic rehabilitation with the EMG-driven exoskeleton hand robot (Hand of Hope®, Rehab-Robotics Company) 15 sessions over 3 weeks. Hand motor functions (Fugl-Meyer Assessment-Upper Extremity (FMA-UE) and Action Research Arm Test (ARAT)), activities of daily living (Motor Activity Log (MAL)), force and EMG activities of extensor and flexor muscles for the cup test were evaluated before treatment (pretreatment) and after the 15th session (posttreatment).

RESULTS

Eleven patients (59.91 ± 14.20 yr) in the EG and 9 patients (70 ± 14.06 yr) in the CG completed the study. EG did not provide a significant advantage compared with the CG in FMA-UE, ARAT and MAL scores and cup-force and EMG activities (p > .05 for all).

CONCLUSION

In this preliminary study, improvement in motor functions, daily living activities and force were found in both groups. However, addition of the EMG-driven robotic treatment to the neurophysiological rehabilitation program did not provide an additional benefit to the clinical outcomes in 3 weeks in acute stroke patients.

Development of portable robotic orthosis and biomechanical validation in people with limited upper limb function after stroke

Stroke has a considerable incidence in the world population and would cause sequelae in the upper limbs. One way to increase the efficiency in the rehabilitation process of patients with these sequelae is through robot-assisted therapy. The present study developed a portable robotic orthosis called Pinotti Portable Robotic Exoskeleton (PPRE) and validated its functioning in clinical tests. The static and dynamic parts of the device modules are described. Design issues, such as heavyweight and engine positioning, have been optimized. The implementation of control was through a smartphone application that communicates with a microcontroller to perform desired movements. Four individuals with motor impairment of the upper limbs due to stroke performed clinical tests to validate the device. Participants did not mention pain, discomfort, tingling, and paresthesia. The robotic device showed the ability to perform the flexion and extension movements of the fingers and elbow. The PPRE was confirmed to be adequate and functional at different levels of motor impairment assessed. The orthosis presented advantages over the currently existing devices, concerning its biomechanical functioning, portability, comfort, and versatility. Thus, the apparatus has the great innovative potential to become a device for home use, serving as an aid to the therapist and facilitating the rehabilitation of patients after an injury. In a larger sample, future studies are needed to assess the effect of a robotic orthosis on the level of rehabilitation in individuals with upper limb impairment.

Upper Limb Stroke Rehabilitation Using Surface Electromyography: A Systematic Review and Meta-Analysis

Background

Upper limb impairment is common after stroke, and many will not regain full upper limb function. Different technologies based on surface electromyography (sEMG) have been used in stroke rehabilitation, but there is no collated evidence on the different sEMG-driven interventions and their effect on upper limb function in people with stroke.

Aim

Synthesize existing evidence and perform a meta-analysis on the effect of different types of sEMG-driven interventions on upper limb function in people with stroke.

Methods

PubMed, SCOPUS, and PEDro databases were systematically searched for eligible randomized clinical trials that utilize sEMG-driven interventions to improve upper limb function assessed by Fugl-Meyer Assessment (FMA-UE) in stroke. The PEDro scale was used to evaluate the methodological quality and the risk of bias of the included studies. In addition, a meta-analysis utilizing a random effect model was performed for studies comparing sEMG interventions to non-sEMG interventions and for studies comparing different sEMG interventions protocols.

Results

Twenty-four studies comprising 808 participants were included in this review. The methodological quality was good to fair. The meta-analysis showed no differences in the total effect, assessed by total FMA-UE score, comparing sEMG interventions to non-sEMG interventions (14 studies, 509 participants, SMD 0.14, P 0.37, 95% CI –0.18 to 0.46, I² 55%). Similarly, no difference in the overall effect was found for the meta-analysis comparing different types of sEMG interventions (7 studies, 213 participants, SMD 0.42, P 0.23, 95% CI –0.34 to 1.18, I² 73%). Twenty out of the twenty-four studies, including participants with varying impairment levels at all stages of stroke recovery, reported statistically significant improvements in upper limb function at post-sEMG intervention compared to baseline.

Conclusion

This review and meta-analysis could not discern the effect of sEMG in comparison to a non-sEMG intervention or the most effective type of sEMG intervention for improving upper limb function in stroke populations. Current evidence suggests that sEMG is a promising tool to further improve functional recovery, but randomized clinical trials with larger sample sizes are needed to verify whether the effect on upper extremity function of a specific sEMG intervention is superior compared to other non-sEMG or other type of sEMG interventions.

Dual-Modal Hybrid Control for an Upper-Limb Rehabilitation Robot

The recovery treatment of motor dysfunction plays a crucial role in rehabilitation therapy. Rehabilitation robots are partially or fully replacing therapists in assisting patients in exercise by advantage of robot technologies. However, the rehabilitation training system is not yet intelligent enough to provide suitable exercise modes based on the exercise intentions of patients with different motor abilities. In this paper, a dual-modal hybrid self-switching control strategy (DHSS) is proposed to automatically determine the exercise mode of patients, i.e., passive and assistive exercise mode. In this strategy, the potential field method and the ADRC position control are employed to plan trajectories and assist patients’ training. Dual-modal self-switching rules based on the motor and impulse information of patients are presented to identify patients’ motor abilities. Finally, the DHSS assisted five subjects in performing the training with an average deviation error of less than 2 mm in both exercise modes. The experimental results demonstrate that the muscle activation of the subjects differed significantly in different modes. It also verifies that DHSS is reasonable and effective, which helps patients to train independently without therapists.

Error-Related Negativity-Based Robot-Assisted Stroke Rehabilitation System: Design and Proof-of-Concept

Conventional rehabilitation systems typically execute a fixed set of programs that most motor-impaired stroke patients undergo. In these systems, the brain, which is embodied in the body, is often left out. Including the brains of stroke patients in the control loop of a rehabilitation system can be worthwhile as the system can be tailored to each participant and, thus, be more effective. Here, we propose a novel brain-computer interface (BCI)-based robot-assisted stroke rehabilitation system (RASRS), which takes inputs from the patient's intrinsic feedback mechanism to adapt the assistance level of the RASRS. The proposed system will utilize the patients' consciousness about their performance decoded through their error-related negativity signals. As a proof-of-concept, we experimented on 12 healthy people in which we recorded their electroencephalogram (EEG) signals while performing a standard rehabilitation exercise. We set the performance requirements beforehand and observed participants' neural responses when they failed/met the set requirements and found a statistically significant (p < 0.05) difference in their neural responses in the two conditions. The feasibility of the proposed BCI-based RASRS was demonstrated through a use-case description with a timing diagram and meeting the crucial requirements for developing the proposed rehabilitation system. The use of a patient's intrinsic feedback mechanism will have significant implications for the development of human-in-the-loop stroke rehabilitation systems.

Using Robot-Based Variables during Upper Limb Robot-Assisted Training in Subacute Stroke Patients to Quantify Treatment Dose

In post-stroke motor rehabilitation, treatment dose description is estimated approximately. The aim of this retrospective study was to quantify the treatment dose using robot-measured variables during robot-assisted training in patients with subacute stroke. Thirty-six patients performed fifteen 60 min sessions (Session 1−Session 15) of planar, target-directed movements in addition to occupational therapy over 4 (SD 2) weeks. Fugl−Meyer Assessment (FMA) was carried out pre- and post-treatment. The actual time practiced (percentage of a 60 min session), the number of repeated movements, and the total distance traveled were analyzed across sessions for each training modality: assist as needed, unassisted, and against resistance. The FMA score improved post-treatment by 11 (10) points (Session 1 vs. Session 15, p < 0.001). In Session 6, all modalities pooled, the number of repeated movements increased by 129 (252) (vs. Session 1, p = 0.043), the total distance traveled increased by 1743 (3345) cm (vs. Session 1, p = 0.045), and the actual time practiced remained unchanged. In Session 15, the actual time practiced showed changes only in the assist-as-needed modality: −13 (23) % (vs. Session 1, p = 0.013). This description of changes in quantitative-practice-related variables when using different robotic training modalities provides comprehensive information related to the treatment dose in rehabilitation. The treatment dose intensity may be enhanced by increasing both the number of movements and the motor difficulty of performing each movement.

Use of Robotic Devices for Gait Training in Patients Diagnosed with Multiple Sclerosis: Current State of the Art

Multiple sclerosis (MS) is a neurodegenerative disease that produces alterations in balance and gait in most patients. Robot-assisted gait training devices have been proposed as a complementary approach to conventional rehabilitation treatment as a means of improving these alterations. The aim of this study was to investigate the available scientific evidence on the benefits of the use of robotics in the physiotherapy treatment in people with MS. A systematic review of randomized controlled trials was performed. Studies from the last five years on walking in adults with MS were included. The PEDro scale was used to assess the methodological quality of the included studies, and the Jadad scale was used to assess the level of evidence and the degree of recommendation. Seventeen studies met the eligibility criteria. For the improvement of gait speed, robotic devices do not appear to be superior, compared to the rest of the interventions evaluated. The methodological quality of the studies was moderate–low. For this reason, robot-assisted gait training is considered just as effective as conventional rehabilitation training for improving gait in people with MS.

Bimanual motor skill learning with robotics in chronic stroke: comparison between minimally impaired and moderately impaired patients, and healthy individuals

BACKGROUND

Most activities of daily life (ADL) require cooperative bimanual movements. A unilateral stroke may severely impair bimanual ADL. How patients with stroke (re)learn to coordinate their upper limbs (ULs) is largely unknown. The objectives are to determine whether patients with chronic supratentorial stroke could achieve bimanual motor skill learning (bim-MSkL) and to compare bim-MSkL between patients and healthy individuals (HIs).

METHODS

Twenty-four patients and ten HIs trained over 3 consecutive days on an asymmetrical bimanual coordination task (CIRCUIT) implemented as a serious game in the REAplan® robot. With a common cursor controlled by coordinated movements of the ULs through robotic handles, they performed as many laps as possible (speed constraint) on the CIRCUIT while keeping the cursor within the track (accuracy constraint). The primary outcome was a bimanual speed/accuracy trade-off (biSAT), we used a bimanual coordination factor (biCO) and bimanual forces (biFOP) for the secondary outcomes. Several clinical scales were used to evaluate motor and cognitive functions.

RESULTS

Overall, the patients showed improvements on biSAT and biCO. Based on biSAT progression, the HI achieved a larger bim-MSkL than the patients with mild to moderate impairment (Fugl-Meyer Assessment Upper Extremity (FMA-UE): 28-55, n = 15) but not significantly different from those with minimal motor impairment (FMA-UE: 66, n = 9). There was a significant positive correlation between biSAT evolution and the FMA-UE and Stroke Impact Scale.

CONCLUSIONS

Both HI and patients with chronic stroke training on a robotic device achieved bim-MSkL, although the more impaired patients were less efficient. Bim-MSkL with REAplan® may be interesting for neurorehabilitation after stroke.

TRIAL REGISTRATION

ClinicalTrial.gov identifier: NCT03974750. Registered 05 June 2019. https://clinicaltrials.gov/ct2/show/NCT03974750?cond=NCT03974750&draw=2&rank=1.

Robot-assisted distal training improves upper limb dexterity and function after stroke: a systematic review and meta-regression

INTRODUCTION

Stroke is one of the top 10 causes of death worldwide, and more than half of stroke patients face distal upper extremity dysfunction. Considering that robot-assisted training may be effective in improving distal upper extremity function, the review evaluated the effect of robot-assisted distal training on motor function, hand dexterity, and spasticity after stroke.

METHODS

Eleven databases were systematically searched for randomised controlled trials (RCTs) from inception until Aug 28, 2021. Meta-analysis and meta-regression were performed to investigate the overall effect and source of heterogeneity, respectively.

RESULTS

Twenty-two trials involving 758 participants were included in this systematic review. The overall effect of robot-assisted distal training on the motor function of the wrists and hands was significant improvement (MD = 3.92; 95% CI, 3.04-4.80; P < 0.001). The robot-assisted training had a significantly beneficial effect on other motor functions (MD = 2.84; 95% CI, 1.54-4.14; P < 0.001); dexterity (MD = 9.01; 95% CI, -12.07--5.95; P < 0.001), spasticity, upper extremity strength (SMD = 0.42; 95% CI, 0.07-0.78; P = 0.02) and activities of daily living (SMD = 0.70; 95% CI, 0.29-1.23; P < 0.001). A series of subgroup analyses showed preferable design and effective regime of training. Meta-regression indicated the statistically significant effect of the year of trial, country, and duration on the effectiveness of training.

CONCLUSION

Robot-assisted distal training has a significant effect on motor function, dexterity and spasticity of the upper extremity, compared to conventional therapy.