Sensor-based arm skill training in chronic stroke patients: results on treatment outcome, patient motivation, and system usability

Supporting patients' workload through wearable devices and mobile health applications, a systematic literature review

Patients face a challenging workload in their course of care. In this study, we investigate the impact of using mobile health technologies in supporting this workload and identify the system challenges of its application through a systematic review of the literature published in the last two decades following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Reviews and Meta-Analysis guidelines PRISMA guidelines. Twenty-two studies that satisfied the inclusion criteria were included. The review revealed various mobile health and wearable devices used to support mental demand, physical demand, frustration, and performance. Better outcomes were related to mobile health use in healthcare for patients in different settings. There were no applications of health that supported the temporal demand of patients. Some populations, such as cancer patients, need more than only physical demand. Mhealth devices are important in supporting the patients' workload in their daily activities and clinical settings.Practitioner summary: This review study shows the importance of mHealth and wearables in supporting patients' workload (physical, mental, emotional) but not the temporal load.

Modulated effectiveness of rehabilitation motivation by reward strategies combined with tDCS in stroke: study protocol for a randomized controlled trial

Background

Stroke survivors often exhibit low motivation for rehabilitation, hindering their ability to effectively complete rehabilitation training task effectively and participate in daily activities actively. Reward strategies have been identified as an effective method for boosting rehabilitation motivation, but their long-term efficacy remains uncertain. Transcranial direct current stimulation (tDCS) has been recognized as a technique that facilitates plastic changes and functional reorganization of cortical areas. Particularly, tDCS can improve the functional connectivity between brain regions associated with goal-directed behavior when applied to the left dorsolateral prefrontal cortex (dlPFC). Combing reward strategies with tDCS (RStDCS) has been shown to motivate healthy individuals to exert more effort in task performance. However, research exploring the combined and sustained effects of these strategies on rehabilitation motivation in stroke survivors is lacking.

Methods and design

Eighty-seven stroke survivors with low motivation and upper extremity dysfunction will be randomized to receive either conventional treatment, RS treatment, or RStDCS treatment. The RStDCS group will receive reward strategies combined with anodal tDCS stimulation of the left dlPFC. The RS group will receive reward strategies combined with sham stimulation. The conventional group will receive conventional treatment combined with sham stimulation. tDCS stimulation is performed over 3 weeks of hospitalization, 20 min/time, five times a week. Reward strategies refers to personalized active exercise programs for patients during hospitalization and at home. Patients can voluntarily choose tasks for active exercise and self-report to the therapist so as to punch a card for points and exchange gifts. The conventional group will receive home rehabilitation instructions prior to discharge. Rehabilitation motivation, measured using RMS. RMS, FMA, FIM, and ICF activity and social engagement scale will be compared at baseline, 3 weeks, 6 weeks, and 3 months post-enrollment to evaluate patients' multifaceted health condition based on the ICF framework.

Discussion

This study integrates knowledge from social cognitive science, economic behavioral science, and other relevant fields. We utilize straightforward and feasible reward strategies, combined with neuromodulation technology, to jointly improve patients' rehabilitation motivation. Behavioral observations and various assessment tools will be used to monitor patients' rehabilitation motivation and multifaceted health condition according to the ICF framework. The aim is to provide a preliminary exploration path for professionals to develop comprehensive strategies for improving patient rehabilitation motivation and facilitating a complete "hospital-home-society" rehabilitation process.

Clinical trial registration

https://www.chictr.org.cn/showproj.aspx?proj=182589, ChiCTR2300069068.

Effects of a remote-handling-concept-based task-oriented arm training (ReHab-TOAT) on arm-hand skill performance in chronic stroke: a study protocol for a two-armed randomized controlled trial

BACKGROUND

Improving arm-hand skill performance is a major therapeutic target in stroke rehabilitation and needs intensive and varied training. However, guided treatment time is limited. Technology can assist in the training of patients, offering a higher intensity and more variety in content. A new task-oriented arm training approach was developed, using a 'Remote Handling concept based' device to provide haptic feedback during the performance of daily living activities (ReHab-TOAT). This study aims to investigate the effects of ReHab-TOAT on patients' arm-hand function and arm-hand skill performance, quality of life of both patients in the chronic phase after stroke and their caregivers and the patients' perception regarding the usability of the intervention.

METHODS

A randomized clinical trial was designed. Adult chronic stroke patients suffering from hemiparesis and arm-hand problems, with an Utrechtse Arm-hand Test score of 1-3, will be invited to participate. Participants in the experimental group receive ReHab-TOAT additional to care as usual. ReHab-TOAT contains task-oriented arm training for stroke patients in combination with haptic feedback, generated by a remote handling device. They will train for 4 weeks, 3× per week, 1.5h per day. Participants in the control group will receive no additional therapy apart from care as usual. The Fugl-Meyer Assessment (FMA), measuring participants' motor performance of the affected arm, is used as the primary outcome measure. Secondary outcome measures are arm-hand capacity of the patient (ARAT), perceived arm-hand skill performance (MAL), actual arm-hand skill performance (accelerometry), patients' quality of life (EuoQol-5D) and caregivers' quality of life (CarerQoL). Participants' perception regarding the usability of the intervention, including both the developed approach and technology used, will be evaluated by the System Usability Scale and a questionnaire on the user experience of technology. Measurements will be performed at 1, 2, 3 and 4 weeks pre-intervention (baseline); immediately post-intervention; and 3, 6 and 9 months post-intervention. Statistical analysis includes linear mixed model analysis.

DISCUSSION

This study is designed to investigate the evidence regarding the effects of ReHab-TOAT on patients' performance at different levels of the International Classification of Functioning, disability and health (ICF) model, i.e. a framework measuring functioning and disability in relation to a health condition, and to provide insights on a successful development and research process regarding technology-assisted training in co-creation.

TRIAL REGISTRATION

Netherlands Trial Register NL9541. Registered on June 22, 2021.

Feasibility and Effect of a Wearable Motion Sensor Device in Facilitating In-Home Rehabilitation Program in Patients after Total Knee Arthroplasty: A Preliminary Study

Postoperative home-based rehabilitation programs are essential for facilitating functional recovery after total knee replacement (TKA). This study aimed to verify the feasibility of applying a wearable motion sensor device (MSD) to assist patients in performing home-based exercises after TKA. The interrater reliability of the measurement for knee mobility and the time spent completing the 5-times sit-to-stand test (5TSST) by two experienced physicians and using the MSD in 12 healthy participants was first assessed. A prospective control trial was then conducted, in which 12 patients following TKA were allocated to two groups: the home-based exercise group and the MSD-assisted rehabilitation group. Changes in knee range of motion, pain, functional score, performance, and exercise completion rates were compared between the groups over two months of follow-up. MSD-measured knee mobility and 5TSST exhibited excellent reliability compared with the physician measurements. Furthermore, patients in the MSD-assisted rehabilitation group reported higher training compliance than participants in the home-based exercise group, which led to better outcomes in the knee extension angle and maximal and average angular velocity in 5TSST. MSD-assisted home-based rehabilitation following TKA is a feasible treatment model for telerehabilitation because it enhances patients’ compliance to training, which improves functional recovery.

A Wearable System Composed of FBG-Based Soft Sensors for Trunk Compensatory Movements Detection in Post-Stroke Hemiplegic Patients

In this study, a novel wearable system for the identification of compensatory trunk movements (CTMs) in post-stroke hemiplegic patients is presented. The device is composed of seven soft sensing elements (SSEs) based on fiber Bragg grating (FBG) technology. Each SSE consists of a single FBG encapsulated into a flexible matrix to enhance the sensor’s robustness and improve its compliance with the human body. The FBG’s small size, light weight, multiplexing capability, and biocompatibility make the proposed wearable system suitable for multi-point measurements without any movement restriction. Firstly, its manufacturing process is presented, together with the SSEs’ mechanical characterization to strain. Results of the metrological characterization showed a linear response of each SSE in the operating range. Then, the feasibility assessment of the proposed system is described. In particular, the device’s capability of detecting CTMs was assessed on 10 healthy volunteers and eight hemiplegic patients while performing three tasks which are representative of typical everyday life actions. The wearable system showed good potential in detecting CTMs. This promising result may foster the use of the proposed device on post-stroke patients, aiming at assessing the proper course of the rehabilitation process both in clinical and domestic settings. Moreover, its use may aid in defining tailored strategies to improve post-stoke patients’ motor recovery and quality of life.

A Systematic Review of Wearable Sensors for Monitoring Physical Activity

This article reviews the use of wearable sensors for the monitoring of physical activity (PA) for different purposes, including assessment of gait and balance, prevention and/or detection of falls, recognition of various PAs, conduction and assessment of rehabilitation exercises and monitoring of neurological disease progression. The article provides in-depth information on the retrieved articles and discusses study shortcomings related to demographic factors, i.e., age, gender, healthy participants vs patients, and study conditions. It is well known that motion patterns change with age and the onset of illnesses, and that the risk of falling increases with age. Yet, studies including older persons are rare. Gender distribution was not even provided in several studies, and others included only, or a majority of, men. Another shortcoming is that none of the studies were conducted in real-life conditions. Hence, there is still important work to be done in order to increase the usefulness of wearable sensors in these areas. The article highlights flaws in how studies based on previously collected datasets report on study samples and the data collected, which makes the validity and generalizability of those studies low. Exceptions exist, such as the promising recently reported open dataset FallAllD, wherein a longitudinal study with older adults is ongoing.

Citation Network Study on the Use of New Technologies in Neurorehabilitation

New technologies in neurorehabilitation is a wide concept that intends to find solutions for individual and collective needs through technical systems. Analysis through citation networks is used to search scientific literature related to a specific topic. On the one hand, the main countries, institutions, and authors researching this topic have been identified, as well as their evolution over time. On the other hand, the links between the authors, the countries, and the topics under research have been analyzed. The publications analysis was performed through the Web of Science database using the search terms "new technolog*," "neurorehabilitation," "physical therapy*," and "occupational therapy*." The selected interval of publication was from 1992 to December 2020. The results were analyzed using CitNetExplorer software. After a Web of Science search, a total of 454 publications and 135 citation networks were found, 1992 being the first year of publication. An exponential increase was detected from the year 2009. The largest number was detected in 2020. The main areas are rehabilitation and neurosciences and neurology. The most cited article was from Perry et al. in 2007, with a citation index of 460. The analysis of the top 20 most cited articles shows that most approach the use of robotic devices and brain-computer interface systems. In conclusion, the main theme was found to be the use of robotic devices to address neuromuscular rehabilitation goals and brain-computer interfaces and their applications in neurorehabilitation.

European evidence-based recommendations for clinical assessment of upper limb in neurorehabilitation (CAULIN): data synthesis from systematic reviews, clinical practice guidelines and expert consensus

BACKGROUND

Technology-supported rehabilitation can help alleviate the increasing need for cost-effective rehabilitation of neurological conditions, but use in clinical practice remains limited. Agreement on a core set of reliable, valid and accessible outcome measures to assess rehabilitation outcomes is needed to generate strong evidence about effectiveness of rehabilitation approaches, including technologies. This paper collates and synthesizes a core set from multiple sources; combining existing evidence, clinical practice guidelines and expert consensus into European recommendations for Clinical Assessment of Upper Limb In Neurorehabilitation (CAULIN).

METHODS

Data from systematic reviews, clinical practice guidelines and expert consensus (Delphi methodology) were systematically extracted and synthesized using strength of evidence rating criteria, in addition to recommendations on assessment procedures. Three sets were defined: a core set: strong evidence for validity, reliability, responsiveness and clinical utility AND recommended by at least two sources; an extended set: strong evidence OR recommended by at least two sources and a supplementary set: some evidence OR recommended by at least one of the sources.

RESULTS

In total, 12 measures (with primary focus on stroke) were included, encompassing body function and activity level of the International Classification of Functioning and Health. The core set recommended for clinical practice and research: Fugl-Meyer Assessment of Upper Extremity (FMA-UE) and Action Research Arm Test (ARAT); the extended set recommended for clinical practice and/or clinical research: kinematic measures, Box and Block Test (BBT), Chedoke Arm Hand Activity Inventory (CAHAI), Wolf Motor Function Test (WMFT), Nine Hole Peg Test (NHPT) and ABILHAND; the supplementary set recommended for research or specific occasions: Motricity Index (MI); Chedoke-McMaster Stroke Assessment (CMSA), Stroke Rehabilitation Assessment Movement (STREAM), Frenchay Arm Test (FAT), Motor Assessment Scale (MAS) and body-worn movement sensors. Assessments should be conducted at pre-defined regular intervals by trained personnel. Global measures should be applied within 24 h of hospital admission and upper limb specific measures within 1 week.

CONCLUSIONS

The CAULIN recommendations for outcome measures and assessment procedures provide a clear, simple, evidence-based three-level structure for upper limb assessment in neurological rehabilitation. Widespread adoption and sustained use will improve quality of clinical practice and facilitate meta-analysis, critical for the advancement of technology-supported neurorehabilitation.

Evidence for the Effectiveness of Feedback from Wearable Inertial Sensors during Work-Related Activities: A Scoping Review

Background: Wearable inertial sensor technology (WIST) systems provide feedback, aiming to modify aberrant postures and movements. The literature on the effects of feedback from WIST during work or work-related activities has not been previously summarised. This review examines the effectiveness of feedback on upper body kinematics during work or work-related activities, along with the wearability and a quantification of the kinematics of the related device. Methods: The Cinahl, Cochrane, Embase, Medline, Scopus, Sportdiscus and Google Scholar databases were searched, including reports from January 2005 to July 2021. The included studies were summarised descriptively and the evidence was assessed. Results: Fourteen included studies demonstrated a 'limited' level of evidence supporting posture and/or movement behaviour improvements using WIST feedback, with no improvements in pain. One study assessed wearability and another two investigated comfort. Studies used tri-axial accelerometers or IMU integration (n = 5 studies). Visual and/or vibrotactile feedback was mostly used. Most studies had a risk of bias, lacked detail for methodological reproducibility and displayed inconsistent reporting of sensor technology, with validation provided only in one study. Thus, we have proposed a minimum 'Technology and Design Checklist' for reporting. Conclusions: Our findings suggest that WIST may improve posture, though not pain; however, the quality of the studies limits the strength of this conclusion. Wearability evaluations are needed for the translation of WIST outcomes. Minimum reporting standards for WIST should be followed to ensure methodological reproducibility.

Developing an intelligent activity-based client-centred training system with a user-centred approach

BACKGROUND

In neurorehabilitation, clinicians and managers are searching for new client-centred task-oriented applications which can be administered without extra costs and effort of therapists, and increase the client's motivation.

OBJECTIVE

To develop and evaluate a prototype of an intelligent activity-based client-centred training (i-ACT) system based on Microsoft Kinect®.

METHODS

Within an iterative user centred process, the i-ACT prototype was developed and necessary features were established for use in neurological settings. After the test trial with a high fidelity prototype, the value, usefulness, and credibility were evaluated.

RESULTS

Seven therapists participated in focus groups and 54 persons with neurological problems participated in test trials. A prototype was established based on the user's experience. Results show that clients and therapists acknowledge the value and usefulness (clients 5.71/7; therapists 4.86/7), and credibility (clients 21.00/27; therapists 14.50/27) of i-ACT.

CONCLUSIONS

Therapists want to be able to record an endless range of movements and activities which enables individualised exercise programs for persons with disabilities. For therapists it is important that the system provides feedback about the quality of movement and not only results. In future work, clinical trials will be performed towards feasibility and effectiveness of i-ACT in neurorehabilitation and other rehabilitation domains.

A robot goes to rehab: a novel gamified system for long-term stroke rehabilitation using a socially assistive robot-methodology and usability testing

Background

Socially assistive robots (SARs) have been proposed as a tool to help individuals who have had a stroke to perform their exercise during their rehabilitation process. Yet, to date, there are no data on the motivating benefit of SARs in a long-term interaction with post-stroke patients.

Methods

Here, we describe a robot-based gamified exercise platform, which we developed for long-term post-stroke rehabilitation. The platform uses the humanoid robot Pepper, and also has a computer-based configuration (with no robot). It includes seven gamified sets of exercises, which are based on functional tasks from the everyday life of the patients. The platform gives the patients instructions, as well as feedback on their performance, and can track their performance over time. We performed a long-term patient-usability study, where 24 post-stroke patients were randomly allocated to exercise with this platform—either with the robot or the computer configuration—over a 5–7 week period, 3 times per week, for a total of 306 sessions.

Results

The participants in both groups reported that this rehabilitation platform addressed their arm rehabilitation needs, and they expressed their desire to continue training with it even after the study ended. We found a trend for higher acceptance of the system by the participants in the robot group on all parameters; however, this difference was not significant. We found that system failures did not affect the long-term trust that users felt towards the system.

Conclusions

We demonstrated the usability of using this platform for a long-term rehabilitation with post-stroke patients in a clinical setting. We found high levels of acceptance of both platform configurations by patients following this interaction, with higher ratings given to the SAR configuration. We show that it is not the mere use of technology that increases the motivation of the person to practice, but rather it is the appreciation of the technology’s effectiveness and its perceived contribution to the rehabilitation process. In addition, we provide a list of guidelines that can be used when designing and implementing other technological tools for rehabilitation.

Trial registration: This trial is registered in the NIH ClinicalTrials.gov database. Registration number NCT03651063, registration date 21.08.2018. https://clinicaltrials.gov/ct2/show/NCT03651063.

iRebot: An Interactive Rehabilitation Robot with Gesture Control

Physical therapy efficacy relies on patient compliance and motivation. However, the monotony, intensity, and expense of most therapy routines do not promote engagement. Technology-based rehabilitation has the potential to provide engaging and cost-effective treatment, leading to better compliance and mobility outcomes. We present an interactive rehabilitation robot (iRebot) as an affordable, gesture-controlled vehicle that can provide a form of entertainment while conducting physical therapy. Healthy participants (n=11) executed a test maze with the iRebot for six repeated trials, three with each hand. Survey scores and quantitative metrics were evaluated to assess system usability and baseline motor performance, respectively. Wrist mobility across participants was evaluated, with an active range of motion of 39.7± 13° and 72.8± 18° for pitch and roll, respectively. In the course of conducting a single trial (time duration=87.2±67 sec), the participants performed on average 30 full wris t motion repetitions (e.g., flexion/extension). Participants rated the system's usability as excellent (survey score: 85 ± 13), and all participants indicated they would prefer iRebot over standard therapy. The iRebot demonstrated potential as an evidence-based rehabilitation tool based on excellent user ratings and the ability to monitor at- home compliance and motor performance.

A Gesture-Controlled Rehabilitation Robot to Improve Engagement and Quantify Movement Performance

Rehabilitation requires repetitive and coordinated movements for effective treatment, which are contingent on patient compliance and motivation. However, the monotony, intensity, and expense of most therapy routines do not promote engagement. Gesture-controlled rehabilitation has the potential to quantify performance and provide engaging, cost-effective treatment, leading to better compliance and mobility. We present the design and testing of a gesture-controlled rehabilitation robot (GC-Rebot) to assess its potential for monitoring user performance and providing entertainment while conducting physical therapy. Healthy participants (n = 11) completed a maze with GC-Rebot for six trials. User performance was evaluated through quantitative metrics of movement quality and quantity, and participants rated the system usability with a validated survey. For participants with self-reported video-game experience (n = 10), wrist active range of motion across trials (mean ± standard deviation) was 41.6 ± 13° and 76.8 ± 16° for pitch and roll, respectively. In the course of conducting a single trial with a time duration of 68.3 ± 19 s, these participants performed 27 ± 8 full wrist motion repetitions (i.e., flexion/extension), with a dose-rate of 24.2 ± 5 reps/min. These participants also rated system usability as excellent (score: 86.3 ± 12). Gesture-controlled therapy using the GC-Rebot demonstrated the potential to be an evidence-based rehabilitation tool based on excellent user ratings and the ability to monitor at-home compliance and performance.

Wearable Motion Sensor Device to Facilitate Rehabilitation in Patients With Shoulder Adhesive Capsulitis: Pilot Study to Assess Feasibility

BACKGROUND

Adhesive capsulitis (AC) of the shoulder is a common disorder that painfully reduces the shoulder range of motion (ROM) among middle-aged individuals. Although physical therapy with home-based exercises is widely advised to restore ROM in the treatment of AC, clinical results vary owing to inconsistent patient compliance.

OBJECTIVE

In this study, we aimed to verify the feasibility of a treatment model that involves applying a wearable motion sensor device to assist patients conduct home-based exercises to improve training compliance and the accuracy of exercises, with the ultimate goal of improving the functional recovery of patients with AC.

METHODS

The motion sensor device was comprised of inertial measurement unit-based sensors and mobile apps for patients and physicians, offering shoulder mobility tracing, home-based exercise support, and progress monitoring. The interrater reliability of shoulder mobility measurement using the motion sensor device on 10 healthy participants and 15 patients with AC was obtained using an intraclass correlation coefficient analysis and compared with the assessments performed by two highly experienced physicians. A pilot prospective control trial was then carried out to allocate the 15 patients with AC to two groups: home-based exercise group and motion sensor-assisted rehabilitation group. Changes in active and passive shoulder ROM, pain and functional scores, and exercise completion rates were compared between the groups during a treatment period of 3 months.

RESULTS

Shoulder ROM, as measured using the motion sensor device, exhibited good to excellent reliability based on the comparison with the measurements of two physicians (intraclass correlation coefficient range, 0.771 to 0.979). Compared with patients with AC in the home-based exercise group, those in the motion sensor-assisted rehabilitation group exhibited better shoulder mobility and functional recovery and a higher exercise completion rate during and after 3 months of rehabilitation.

CONCLUSIONS

Motion sensor device-assisted home-based rehabilitation for the treatment of AC is a useful treatment model for telerehabilitation that enhances the compliance of patients through training, thus improving functional recovery. This helps overcome important obstacles in physiotherapy at home by providing comprehensible and easily accessible exercise instructions, enhancing compliance, ensuring the correctness of exercise, and monitoring the progress of patients.

A Systematic Review on the Use of Wearable Body Sensors for Health Monitoring: A Qualitative Synthesis

The use of wearable body sensors for health monitoring is a quickly growing field with the potential of offering a reliable means for clinical and remote health management. This includes both real-time monitoring and health trend monitoring with the aim to detect/predict health deterioration and also to act as a prevention tool. The aim of this systematic review was to provide a qualitative synthesis of studies using wearable body sensors for health monitoring. The synthesis and analysis have pointed out a number of shortcomings in prior research. Major shortcomings are demonstrated by the majority of the studies adopting an observational research design, too small sample sizes, poorly presented, and/or non-representative participant demographics (i.e., age, gender, patient/healthy). These aspects need to be considered in future research work.

Real-Time Detection of Compensatory Patterns in Patients With Stroke to Reduce Compensation During Robotic Rehabilitation Therapy

OBJECTIVES

Compensations are commonly employed by patients with stroke during rehabilitation without therapist supervision, leading to suboptimal recovery outcomes. This study investigated the feasibility of the real-time monitoring of compensation in patients with stroke by using pressure distribution data and machine learning algorithms. Whether trunk compensation can be reduced by combining the online detection of compensation and haptic feedback of a rehabilitation robot was also investigated.

METHODS

Six patients with stroke did three forms of reaching movements while pressure distribution data were recorded as Dataset1. A support vector machine (SVM) classifier was trained with features extracted from Dataset1. Then, two other patients with stroke performed reaching tasks, and the SVM classifier trained by Dataset1 was employed to classify the compensatory patterns online. Based on the real-time monitoring of compensation, a rehabilitation robot provided an assistive force to patients with stroke to reduce compensations.

RESULTS

Good classification performance (F1 score > 0.95) was obtained in both offline and online compensation analysis using the SVM classifier and pressure distribution data of patients with stroke. Based on the real-time detection of compensatory patterns, the angles of trunk rotation, trunk lean-forward and trunk-scapula elevation decreased by 46.95%, 32.35% and 23.75%, respectively.

CONCLUSION

High classification accuracies verified the feasibility of detecting compensation in patients with stroke based on pressure distribution data. Since the validity and reliability of the online detection of compensation has been verified, this classifier can be incorporated into a rehabilitation robot to reduce trunk compensations in patients with stroke.

Development of a Post-stroke Upper Limb Rehabilitation Wearable Sensor for Use in Sub-Saharan Africa: A Pilot Validation Study

The development of context-appropriate sensor technologies could alleviate the significant burden of stroke in Sub-Saharan African rehabilitation clinicians and health care facilities. However, many commercially available wearable sensors are beyond the financial capabilities of the majority of African persons. In this study, we evaluated the concurrent validity of a low-cost wearable sensor (i.e., the outREACH sensor) to measure upper limb movement kinematics of 31 healthy persons, using an 8-camera Vicon motion capture system as the reference standard. The outREACH sensor showed high correlation (r range: 0.808-0.990) and agreement (mean difference range: -1.60 to 1.10) with the reference system regardless of task or kinematic parameter. Moreover, Bland-Altman analyses indicated that there were no significant systematic errors present. This study indicates that upper limb movement kinematics can be accurately measured using the outREACH sensor, and have the potential to enhance stroke evaluation and rehabilitation in sub-Saharan Africa.

Detecting compensatory movements of stroke survivors using pressure distribution data and machine learning algorithms

BACKGROUND

Compensatory movements are commonly employed by stroke survivors during seated reaching and may have negative effects on their long-term recovery. Detecting compensation is useful for coaching the patient to reduce compensatory trunk movements and improving the motor function of the paretic arm. Sensor-based and camera-based systems have been developed to detect compensatory movements, but they still have some limitations, such as causing object obstructions, requiring complex setups and raising privacy concerns. To overcome these drawbacks, this paper proposes a compensatory movement detection system based on pressure distribution data and is unobtrusive, simple and practical. Machine learning algorithms were applied to classify compensatory movements automatically. Therefore, the purpose of this study was to develop and test a pressure distribution-based system for the automatic detection of compensation movements of stroke survivors using machine learning algorithms.

METHODS

Eight stroke survivors performed three types of reaching tasks (back-and-forth, side-to-side, and up-and-down reaching tasks) with both the healthy side and the affected side. The pressure distribution data were recorded, and five features were extracted for classification. The k-nearest neighbor (k-NN) and support vector machine (SVM) algorithms were applied to detect and categorize the compensatory movements. The surface electromyography (sEMG) signals of nine trunk muscles were acquired to provide a detailed description and explanation of compensatory movements.

RESULTS

Cross-validation yielded high classification accuracies (F1-score>0.95) for both the k-NN and SVM classifiers in detecting compensation movements during all the reaching tasks. In detail, an excellent performance was achieved in discriminating between compensation and noncompensation (NC) movements, with an average F1-score of 0.993. For the multiclass classification of compensatory movement patterns, an average F1-score of 0.981 was achieved in recognizing the NC, trunk lean-forward (TLF), trunk rotation (TR) and shoulder elevation (SE) movements.

CONCLUSIONS

Good classification performance in detecting and categorizing compensatory movements validated the feasibility of the proposed pressure distribution-based system. Reliable classification accuracy achieved by the machine learning algorithms indicated the potential to monitor compensation movements automatically by using the pressure distribution-based system when stroke survivors perform seated reaching tasks.

Stroke Patients' Acceptance of a Smart Garment for Supporting Upper Extremity Rehabilitation

The objective is to evaluate to which extent that Zishi a garment equipped with sensors that can support posture monitoring can be used in upper extremity rehabilitation training of stroke patients. Seventeen stroke survivors (mean age: 55 years old, SD =13.5) were recruited in three hospitals in Shanghai. Patients performed 4 tasks (analytical shoulder flexion, functional shoulder flexion placing a cooking pot, analytical flexion in the scapular plane, and functional flexion in the scapular plane placing a bottle of water) with guided feedback on a tablet that was provided through inertial sensors embedded in the Zishi system at the scapula and the thoracic spine region. After performing the training tasks, patients completed four questionnaires for assessing their motivation, their acceptance of the system, its credibility, and usability. The study participants were highly motivated to train with Zishi and the system was rated high usability, while the subjects had moderate confidence with technology supported training in comparison with the training with therapists. The patients respond positively to using Zishi to support rehabilitation training in a clinical setting. Further developments need to address more on engaging and adaptive feedback. This paper paves the way for larger scale effectiveness studies.

A review of wearable motion tracking systems used in rehabilitation following hip and knee replacement

Clinical teams are under increasing pressure to facilitate early hospital discharge for total hip replacement and total knee replacement patients following surgery. A wide variety of wearable devices are being marketed to assist with rehabilitation following surgery. A review of wearable devices was undertaken to assess the evidence supporting their efficacy in assisting rehabilitation following total hip replacement and total knee replacement. A search was conducted using the electronic databases including Medline, CINAHL, Cochrane, PsycARTICLES, and PubMed of studies from January 2000 to October 2017. Five studies met the eligibility criteria, and all used an accelerometer and a gyroscope for their technology. A review of the studies found very little evidence to support the efficacy of the technology, although they show that the use of the technology is feasible. Future work should establish which wearable technology is most valuable to patients, which ones improve patient outcomes, and the most economical model for deploying the technology.

Smart Rehabilitation Garment for posture monitoring

Posture monitoring and correction technologies can support prevention and treatment of spinal pain or can help detect and avoid compensatory movements during the neurological rehabilitation of upper extremities, which can be very important to ensure their effectiveness. We describe the design and development of Smart Rehabilitation Garment (SRG) a wearable system designed to support posture correction. The SRG combines a number of inertial measurement units (IMUs), controlled by an Arduino processor. It provides feedback with vibration on the garment, audible alarm signals and visual instruction through a Bluetooth connected smartphone. We discuss the placement of sensing modules, the garment design, the feedback design and the integration of smart textiles and wearable electronics which aimed at achieving wearability and ease of use. We report on the system's accuracy as compared to optical tracker method.

Motor Control Training for the Shoulder with Smart Garments

Wearable technologies for posture monitoring and posture correction are emerging as a way to support and enhance physical therapy treatment, e.g., for motor control training in neurological disorders or for treating musculoskeletal disorders, such as shoulder, neck, or lower back pain. Among the various technological options for posture monitoring, wearable systems offer potential advantages regarding mobility, use in different contexts and sustained tracking in daily life. We describe the design of a smart garment named Zishi to monitor compensatory movements and evaluate its applicability for shoulder motor control training in a clinical setting. Five physiotherapists and eight patients with musculoskeletal shoulder pain participated in the study. The attitudes of patients and therapists towards the system were measured using standardized survey instruments. The results indicate that patients and their therapists consider Zishi a credible aid for rehabilitation and patients expect it will help towards their recovery. The system was perceived as highly usable and patients were motivated to train with the system. Future research efforts on the improvement of the customization of feedback location and modality, and on the evaluation of Zishi as support for motor learning in shoulder patients, should be made.

Rehabilitation of hand function after spinal cord injury using a novel handgrip device: a pilot study

Background

Activity-based therapy (ABT) for patients with spinal cord injury (SCI), which consists of repetitive use of muscles above and below the spinal lesion, improves locomotion and arm strength. Less data has been published regarding its effects on hand function. We sought to evaluate the effects of a weekly hand-focused therapy program using a novel handgrip device on grip strength and hand function in a SCI cohort.

Methods

Patients with SCI were enrolled in a weekly program that involved activities with the MediSens (Los Angeles, CA) handgrip. These included maximum voluntary contraction (MVC) and a tracking task that required each subject to adjust his/her grip strength according to a pattern displayed on a computer screen. For the latter, performance was measured as mean absolute accuracy (MAA). The Spinal Cord Independence Measure (SCIM) was used to measure each subject’s independence prior to and after therapy.

Results

Seventeen patients completed the program with average participation duration of 21.3 weeks. The cohort included patients with American Spinal Injury Association (ASIA) Impairment Scale (AIS) A (n = 12), AIS B (n = 1), AIS C (n = 2), and AIS D (n = 2) injuries. The average MVC for the cohort increased from 4.1 N to 21.2 N over 20 weeks, but did not reach statistical significance. The average MAA for the cohort increased from 9.01 to 21.7% at the end of the study (p = .02). The cohort’s average SCIM at the end of the study was unchanged compared to baseline.

Conclusions

A weekly handgrip-based ABT program is feasible and efficacious at increasing hand task performance in subjects with SCI.

Interactive wearable systems for upper body rehabilitation: a systematic review

Background

The development of interactive rehabilitation technologies which rely on wearable-sensing for upper body rehabilitation is attracting increasing research interest. This paper reviews related research with the aim: 1) To inventory and classify interactive wearable systems for movement and posture monitoring during upper body rehabilitation, regarding the sensing technology, system measurements and feedback conditions; 2) To gauge the wearability of the wearable systems; 3) To inventory the availability of clinical evidence supporting the effectiveness of related technologies.

Method

A systematic literature search was conducted in the following search engines: PubMed, ACM, Scopus and IEEE (January 2010–April 2016).

Results

Forty-five papers were included and discussed in a new cuboid taxonomy which consists of 3 dimensions: sensing technology, feedback modalities and system measurements. Wearable sensor systems were developed for persons in: 1) Neuro-rehabilitation: stroke (n = 21), spinal cord injury (n = 1), cerebral palsy (n = 2), Alzheimer (n = 1); 2) Musculoskeletal impairment: ligament rehabilitation (n = 1), arthritis (n = 1), frozen shoulder (n = 1), bones trauma (n = 1); 3) Others: chronic pulmonary obstructive disease (n = 1), chronic pain rehabilitation (n = 1) and other general rehabilitation (n = 14). Accelerometers and inertial measurement units (IMU) are the most frequently used technologies (84% of the papers). They are mostly used in multiple sensor configurations to measure upper limb kinematics and/or trunk posture. Sensors are placed mostly on the trunk, upper arm, the forearm, the wrist, and the finger. Typically sensors are attachable rather than embedded in wearable devices and garments; although studies that embed and integrate sensors are increasing in the last 4 years. 16 studies applied knowledge of result (KR) feedback, 14 studies applied knowledge of performance (KP) feedback and 15 studies applied both in various modalities. 16 studies have conducted their evaluation with patients and reported usability tests, while only three of them conducted clinical trials including one randomized clinical trial.

Conclusions

This review has shown that wearable systems are used mostly for the monitoring and provision of feedback on posture and upper extremity movements in stroke rehabilitation. The results indicated that accelerometers and IMUs are the most frequently used sensors, in most cases attached to the body through ad hoc contraptions for the purpose of improving range of motion and movement performance during upper body rehabilitation. Systems featuring sensors embedded in wearable appliances or garments are only beginning to emerge. Similarly, clinical evaluations are scarce and are further needed to provide evidence on effectiveness and pave the path towards implementation in clinical settings.

SITAR: a system for independent task-oriented assessment and rehabilitation

INTRODUCTION

Over recent years, task-oriented training has emerged as a dominant approach in neurorehabilitation. This article presents a novel, sensor-based system for independent task-oriented assessment and rehabilitation (SITAR) of the upper limb.

METHODS

The SITAR is an ecosystem of interactive devices including a touch and force-sensitive tabletop and a set of intelligent objects enabling functional interaction. In contrast to most existing sensor-based systems, SITAR provides natural training of visuomotor coordination through collocated visual and haptic workspaces alongside multimodal feedback, facilitating learning and its transfer to real tasks. We illustrate the possibilities offered by the SITAR for sensorimotor assessment and therapy through pilot assessment and usability studies.

RESULTS

The pilot data from the assessment study demonstrates how the system can be used to assess different aspects of upper limb reaching, pick-and-place and sensory tactile resolution tasks. The pilot usability study indicates that patients are able to train arm-reaching movements independently using the SITAR with minimal involvement of the therapist and that they were motivated to pursue the SITAR-based therapy.

CONCLUSION

SITAR is a versatile, non-robotic tool that can be used to implement a range of therapeutic exercises and assessments for different types of patients, which is particularly well-suited for task-oriented training.

The Present and Future of Robotic Technology in Rehabilitation

Robotic technology designed to assist rehabilitation can potentially increase the efficiency of and accessibility to therapy by assisting therapists to provide consistent training for extended periods of time, and collecting data to assess progress. Automatization of therapy may enable many patients to be treated simultaneously and possibly even remotely, in the comfort of their own homes, through telerehabilitation. The data collected can be used to objectively assess performance and document compliance as well as progress. All of these characteristics can make therapists more efficient in treating larger numbers of patients. Most importantly for the patient, it can increase access to therapy which is often in high demand and rationed severely in today's fiscal climate. In recent years, many consumer grade low-cost and off-the-shelf devices have been adopted for use in therapy sessions and methods for increasing motivation and engagement have been integrated with them. This review paper outlines the effort devoted to the development and integration of robotic technology for rehabilitation.

Increasing patient engagement in rehabilitation exercises using computer-based citizen science

Patient motivation is an important factor to consider when developing rehabilitation programs. Here, we explore the effectiveness of active participation in web-based citizen science activities as a means of increasing participant engagement in rehabilitation exercises, through the use of a low-cost haptic joystick interfaced with a laptop computer. Using the joystick, patients navigate a virtual environment representing the site of a citizen science project situated in a polluted canal. Participants are tasked with following a path on a laptop screen representing the canal. The experiment consists of two conditions: in one condition, a citizen science component where participants classify images from the canal is included; and in the other, the citizen science component is absent. Both conditions are tested on a group of young patients undergoing rehabilitation treatments and a group of healthy subjects. A survey administered at the end of both tasks reveals that participants prefer performing the scientific task, and are more likely to choose to repeat it, even at the cost of increasing the time of their rehabilitation exercise. Furthermore, performance indices based on data collected from the joystick indicate significant differences in the trajectories created by patients and healthy subjects, suggesting that the low-cost device can be used in a rehabilitation setting for gauging patient recovery.

TagTrainer: supporting exercise variability and tailoring in technology supported upper limb training

BACKGROUND

Rehabilitation technology for upper limb training can potentially increase the amount, duration, and quality of therapy offered to patients by targeting the needs of individual patients. Empirical evaluations of such technologies focus on clinical effectiveness; however, little is known regarding the implications of their implementation in daily practice. Tailoring training content to patients requires active participation by therapists, and requires an extension of their role to include authoring and modifying exercises. It is not yet known whether this is feasible, and the socio-technical requirements that will make it successful in practice have not yet been explored. The current study investigates the extent to which therapists can take the role of authoring patient-specific training content and whether effort savings can be achieved by sharing the created content.

METHOD

We present TagTrainer: an interactive tabletop system for rehabilitation that can be operated by manipulating every day physical objects in order to carry out exercises that simulate daily living tasks. TagTrainer supports therapists in creating their own exercises that fit individual patient needs, in adjusting existing exercises, and in putting together personalized exercise programs for and with patients. Four therapists in stroke- and paraplegia-rehabilitation have used TagTrainer for three weeks. Semi-structured interviews were conducted with the therapists, questionnaires were administered to them, and observation notes and usage logs were collected.

RESULTS

A total of 20 exercises were created from scratch, while another three exercises were created as variations of the existing ones. Importantly, all these exercises were created to address specific needs that patients expressed. The patients found the exercises motivating and these exercises were integrated into their regular training.

CONCLUSIONS

TagTrainer can support arm-hand rehabilitation training by increasing therapy variability and tailoring. Therapists consider TagTrainer most suited for group sessions where they supervise many patients at once. Therapists are motivated and are able to, with minimal training, create and tailor exercises for patients fitting individual needs and capabilities. Future research will examine the socio-technical conditions that will encourage therapists to contribute and share training content, and provide the peer support needed for the adoption of a new technology.

A computerized recognition system for the home-based physiotherapy exercises using an RGBD camera

Computerized recognition of the home based physiotherapy exercises has many benefits and it has attracted considerable interest among the computer vision community. However, most methods in the literature view this task as a special case of motion recognition. In contrast, we propose to employ the three main components of a physiotherapy exercise (the motion patterns, the stance knowledge, and the exercise object) as different recognition tasks and embed them separately into the recognition system. The low level information about each component is gathered using machine learning methods. Then, we use a generative Bayesian network to recognize the exercise types by combining the information from these sources at an abstract level, which takes the advantage of domain knowledge for a more robust system. Finally, a novel postprocessing step is employed to estimate the exercise repetitions counts. The performance evaluation of the system is conducted with a new dataset which contains RGB (red, green, and blue) and depth videos of home-based exercise sessions for commonly applied shoulder and knee exercises. The proposed system works without any body-part segmentation, bodypart tracking, joint detection, and temporal segmentation methods. In the end, favorable exercise recognition rates and encouraging results on the estimation of repetition counts are obtained.

Accelerometry measuring the outcome of robot-supported upper limb training in chronic stroke: a randomized controlled trial

PURPOSE

This study aims to assess the extent to which accelerometers can be used to determine the effect of robot-supported task-oriented arm-hand training, relative to task-oriented arm-hand training alone, on the actual amount of arm-hand use of chronic stroke patients in their home situation.

METHODS

This single-blind randomized controlled trial included 16 chronic stroke patients, randomly allocated using blocked randomization (n = 2) to receive task-oriented robot-supported arm-hand training or task-oriented (unsupported) arm-hand training. Training lasted 8 weeks, 4 times/week, 2 × 30 min/day using the (T-)TOAT ((Technology-supported)-Task-Oriented-Arm-Training) method. The actual amount of arm-hand use, was assessed at baseline, after 8 weeks training and 6 months after training cessation. Duration of use and intensity of use of the affected arm-hand during unimanual and bimanual activities were calculated.

RESULTS

Duration and intensity of use of the affected arm-hand did not change significantly during and after training, with or without robot-support (i.e. duration of use of unimanual use of the affected arm-hand: median difference of -0.17% in the robot-group and -0.08% in the control group between baseline and after training cessation; intensity of the affected arm-hand: median difference of 3.95% in the robot-group and 3.32% in the control group between baseline and after training cessation). No significant between-group differences were found.

CONCLUSIONS

Accelerometer data did not show significant changes in actual amount of arm-hand use after task-oriented training, with or without robot-support. Next to the amount of use, discrimination between activities performed and information about quality of use of the affected arm-hand are essential to determine actual arm-hand performance.

TRIAL REGISTRATION

Controlled-trials.com ISRCTN82787126.

Effects of task-oriented robot training on arm function, activity, and quality of life in chronic stroke patients: a randomized controlled trial

Background

Over fifty percent of stroke patients experience chronic arm hand performance problems, compromising independence in daily life activities and quality of life. Task-oriented training may improve arm hand performance after stroke, whereby augmented therapy may lead to a better treatment outcome. Technology-supported training holds opportunities for increasing training intensity. However, the effects of robot-supported task-oriented training with real life objects in stroke patients are not known to date. The aim of the present study was to investigate the effectiveness and added value of the Haptic Master robot combined with task-oriented arm hand training in chronic stroke patients.

Methods

In a single-blind randomized controlled trial, 22 chronic stroke patients were randomly allocated to receive either task-oriented robot-assisted arm-hand training (experimental group) or task-oriented non-robotic arm-hand training (control group). For training, the T-TOAT (Technology-supported Task-Oriented Arm Training) method was applied. Training was provided during 8 weeks, 4 times/week, 2× 30 min/day.

Results

A significant improvement after training on the Action Research Arm Test (ARAT) was demonstrated in the experimental group (p = 0.008). Results were maintained until 6 months after cessation of the training. On the perceived performance measure (Motor Activity Log (MAL)), both, the experimental and control group improved significantly after training (control group p = 0.008; experimental group p = 0.013). The improvements on MAL in both groups were maintained until 6 months after cessation of the training. With regard to quality of life, only in the control group a significant improvement after training was found (EuroQol-5D p = 0.015, SF-36 physical p = 0.01). However, the improvement on SF-36 in the control group was not maintained (p = 0.012). No between-group differences could be demonstrated on any of the outcome measures.

Conclusion

Arm hand performance improved in chronic stroke patients, after eight weeks of task oriented training. The use of a Haptic Master robot in support of task-oriented arm training did not show additional value over the video-instructed task-oriented exercises in highly functional stroke patients.

Clinical trial registration information

Current Controlled Trials ISRCTN82787126

A meta-analysis evaluating the effectiveness of two different upper limb hemiparesis interventions on improving health-related quality of life following stroke

PURPOSE

The aim of this article is to quantitatively assess the efficacy of different upper limb interventions on health-related quality of life (QOL) in stroke patients.

METHOD

Two botulinum type A injection (BTX-A) studies and 4 constraint-induced movement therapy (CIMT) studies were separately combined in a meta-analysis using a fixed effects model. QOL mean scores were extracted and transformed into weighted mean differences.

RESULTS

Combined, the BTX-A studies showed no significant improvements in overall health-related QOL. Similarly, a meta-analysis of 4 CIMT studies revealed nonsignificant findings for the domains of activities of daily living, communication, and hand function. A separate meta-analysis of 3 CIMT studies showed a significant increase in strength scores (P = .007); however, sensitivity analysis for this domain due to significant heterogeneity led to a newP value of .078, showing a nonsignificant increase in strength. Further results for memory, mobility, mood, participation, and overall recovery were all nonsignificant.

CONCLUSION

This report did not show these types of upper limb interventions to be effective in improving health-related QOL in the poststroke population.

Effect of mental practice on the improvement of function and daily activity performance of the upper extremity in patients with subacute stroke: a randomized clinical trial

OBJECTIVES

More than 50% of patients with upper limb paresis after stroke face long-term impaired arm function and ensuing disability in daily life. This study aims to evaluate the effectiveness of a task-oriented mental practice (MP) approach as an addition to regular arm-hand therapy in patients with subacute stroke.

METHODS

A multicenter, prospective, single-blind, randomized clinical trial was performed. Patients trained for 6 weeks, at least 3 times per day. In the experimental group, patients performed video-instructed MP. In the control group, patients performed neurodevelopmental therapy-based exercise therapy. The primary outcome measures are Fugl-Meyer test, Frenchay arm test, Wolf motor function test, and accelerometry.

RESULTS

The patients did improve over time on Fugl-Meyer test and Wolf motor function test in both the control and the experimental group. A significant improvement on the Frenchay arm test was found after training (which was maintained at 12-month follow-up) only in the experimental group. However, no difference in training effects between groups was demonstrated.

CONCLUSIONS

Training effects were demonstrated after MP training in patients with subacute stroke. However, the results of this study do not corroborate the hypothesis that the use of MP in addition to therapy as usual in patients with subacute stroke has an additional effect over neurodevelopmental therapy in addition to therapy as usual.

Motor training programs of arm and hand in patients with MS according to different levels of the ICF: a systematic review

BACKGROUND

The upper extremity plays an important role in daily functioning of patients with Multiple Sclerosis (MS) and strongly influences their quality of life. However, an explicit overview of arm-hand training programs is lacking. The present review aims to investigate the training components and the outcome of motor training programs for arm and hand in MS.

METHODS

A computerized systematic literature search in 5 databases (PubMed, CINAHL, EMBASE, PEDro and Cochrane) was performed using the following Mesh terms: Multiple Sclerosis, Rehabilitation, Physical Education and Training, Exercise, Patient-Centered Care, Upper Extremity, Activities of Daily Living, Motor Skills, Motor Activity, Intervention Studies and Clinical Trial. The methodological quality of the selected articles was scored with the Van Tulder Checklist. A descriptive analyses was performed using the PICO principle, including scoring of training components with the calculation of Hedges'g effect sizes.

RESULTS

Eleven studies were eligible (mean Van Tulder-score = 10.82(SD2.96)). Most studies reported a specific improvement in arm hand performance at the ICF level that was trained at. The mean number of training components was 5.5(SD2.8) and a significant correlation (r = 0.67; p < 0.05) between the number of training components and effect sizes was found. The components 'client-centered' and 'functional movement' were most frequently used, whereas 'distribution based practice', 'feedback' and 'random practice' were never used. The component 'exercise progression' was only used in studies with single ICF body function training, with the exception of 1 study with activity level training. Studies including the component 'client-centred' demonstrated moderate to high effect sizes.

CONCLUSION

Motor training programs (both at the ICF body function and activity level) have shown to improve arm and hand performance in MS in which the value of the training specificity was emphasized. To optimize upper extremity training in MS the component 'client-centred' and 'exercise progression' may be important. Furthermore, given the importance attributed to the components 'distribution based practice', 'feedback' and 'random practice' in previous research in stroke patients, the use of these components in arm hand training should be explored in future research.

Us'em: the user-centered design of a device for motivating stroke patients to use their impaired arm-hand in daily life activities

Stroke leaves the majority of its survivors with an impairment of the upper extremity that affects their ability to live independently and their quality of life. Rehabilitation research shows that practice of everyday life activities in a natural context may sustain or even improve arm-hand performance, even during chronic stages after stroke. Based on this insight we designed, developed and evaluated Us'em; this consists of two watch-like accelerometry devices that provide feedback to stroke patients regarding the usage of their impaired versus their non-affected upper extremity. System usability and treatment credibility/expectancy were evaluated positively by therapists and patients.

A comparison of treatment effects after sensor- and robot-based task-oriented arm training in highly functional stroke patients

A large number of rehabilitation technologies for stroke patients has been developed in the last decade. To date it is insufficiently clear what the strengths of these different technologies are in relation to certain patient characteristics, such as the level of muscle strength and/or functional ability. One of the reasons is that research protocols differ so much that comparison of treatment results is impossible. This paper compares, while using the same patient inclusion criteria and training protocol, the effectivity of a sensor-supported versus robot-supported task-oriented arm training for highly functional chronic stroke patients. It appeared that individual improvements over time and Hedges's g effect sizes were twice as large for the sensor-based training compared to the robot-supported training in stroke patients with high functional levels. New research is planned to compare both therapy approaches for stroke patients with low and average functional levels.