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

Retention of bimanual performance following hand arm bimanual intensive therapy in children with unilateral cerebral palsy: A six-month longitudinal study

Hand-arm bimanual intensive therapy (HABIT) enhances upper extremity (UE) function and bimanual coordination in children with unilateral cerebral palsy (UCP). Previous studies assessed immediate improvements in UE function using clinical and self-reported measures, which may not accurately reflect real-world UE performance and their long-term retention effects. Therefore, this study aims to investigate the retention of real-world bimanual performance gains over time following HABIT in children with UCP. Thirty children with UCP, age 6-16 years underwent HABIT (6 hours/day for 5 days). Bimanual performance was assessed using GT9X Link accelerometers, worn on bilateral wrists for 3 days pre-, post-, 3-, and 6-month of HABIT. Accelerometer-derived variables-use ratio (UR), magnitude ratio (MR), bilateral magnitude (BM), median acceleration (MA), and acceleration variability (AV)-quantified bimanual performance during real-world activities. UE function was measured with standardized assessments. A mixed model analysis with repeated measures and paired t-tests analyzed the differences real-world bimanual performance and UE function respectively. There was a significant main effect of time in UR (F = 2.72, p = 0.05), BM (F = 4.36, p = 0.007), and MA (F = 3.68, p = 0.016). Post-hoc analysis (mean differences, 95% confidence interval [CI]) revealed improvements immediately post- compared to pre-HABIT in BM (14.99, 4.35-25.63) and MA (7.46, 2.55-12.36). However, subsequent assessments at 3- and 6-months displayed a regression in these gains, suggesting a lack of retention. A decline was observed at 3 months) and 6 months (BM; 16.94, 6.3-27.4, MA; 6.51, 1.61-11.41) in BM and MA compared to post-HABIT. UE capacity measures also showed improvements (p < 0.05) post-HABIT. Although HABIT initially may enhance performance of real-world bimanual tasks, its benefits diminish within six months, suggesting a need for repeating HABIT every 3-6 months to retain long-term improvements.

Reaching the cognitive-motor interface: effects of cognitive load on arm choice and motor performance after stroke

A vexing characteristic of motor disability after stroke is that many individuals fail to use their affected arm effectively despite having the capacity to do so, a phenomenon termed arm nonuse. Based on the hypothesis that nonuse is influenced by the competing cognitive demands of many daily activities, we examined the effects of cognitive load on arm choice and motor performance in individuals with stroke using a novel virtual reality paradigm that mimics the demands of real-life visual search, object selection, and reaching to targets. Twenty individuals with single left or right hemispheric chronic stroke (11 left cerebrovascular accident; 9 right cerebrovascular accident) and 10 age-matched neurotypical participants completed the Virtual Reality Arm Choice task, in which they reached for target objects in an array under varied cognitive demand. To manipulate cognitive demand, we varied the semantic similarity of objects in the reaching space and the presence or absence of a secondary task. The results showed reduced use of the paretic arm under increased demand. Under cognitive load, participants with stroke also showed slower reach initiation, slower movements, increased reach curvature, and increased performance differences between the paretic and non-paretic arms. The arm choice of neurotypical individuals was also modulated under cognitive load. These data indicate that cognitive factors influence arm choice and motor performance in naturalistic reaching tasks in individuals with chronic stroke. Performance decrements under cognitive load may in turn influence reduced paretic arm use during daily activities.

Factors Influencing Real-World Use of the More-Affected Upper Limb After Stroke: A Scoping Review

IMPORTANCE

Current interventions are limited in improving use of the more-affected upper limb in real-world daily occupations and functional independence poststroke. A comprehensive understanding of the factors influencing real-world upper limb use is required to develop interventions to improve functional independence poststroke.

OBJECTIVE

To systematically review the factors that influence real-world use of the more-affected upper limb poststroke.

DATA SOURCES

We searched MEDLINE, Embase, PsycINFO, and the Physiotherapy Evidence Database for English-language articles from 2012 to 2023.

STUDY SELECTION AND DATA COLLECTION

Of 774 studies, we included 33 studies that had participants at least age 18 yr who exhibited upper limb impairments poststroke, objectively measured real-world upper limb use using a movement sensor, and measured factors affecting upper limb use. Two reviewers independently screened the abstracts.

FINDINGS

The results were categorized by International Classification of Functioning, Disability and Health domains. Prominent factors were upper limb impairment; motor ability; functional independence; task type; hand dominance; stroke-related factors, including time since stroke; and perception of use of the more-affected upper limb.

CONCLUSIONS AND RELEVANCE

Existing interventions primarily focus on upper limb impairments and motor ability. Our findings suggest that interventions should also incorporate other factors: task type (unilateral vs. bilateral), hand dominance, self-efficacy, and perception of more-affected limb use as active ingredients in improving real-world use of the more-affected upper limb poststroke. We also provide recommendations to use behavioral activation theory in designing an occupation-focused intervention to augment self-efficacy and confidence in use of the more-affected upper limb in daily occupations. Plain-Language Summary: In order to develop interventions to improve functional independence poststroke, occupational therapy practitioners must have a comprehensive understanding of the factors that influence real-world more-affected upper limb use. The study findings provide a set of distinct factors that practitioners can target separately or in combination to improve real-world use of the more-affected upper limb poststroke.

High-Tech Home-Based Rehabilitation after Stroke: A Systematic Review and Meta-Analysis

(1) Background: To improve existing rehabilitation technologies, we conducted a systematic review and meta-analysis to identify the effect size of home-based rehabilitation using robotic, virtual reality, and game devices on physical function for stroke survivors. (2) Methods: Embase, PubMed, Cochrane Library, ProQuest, and CINAHL were used to search the randomized controlled trials that applied technologies via home-based rehabilitation, such as virtual reality, robot-assisted devices, and games. The effect size (Hedges's g) of technology type and affected limb on physical function were calculated. (3) Results: Ten studies were included. The effect size of home-based rehabilitation in virtual reality had the greatest value (Hedges's g, 0.850; 95% CI, 0.314-1.385), followed by robot-assisted devices (Hedges's g, 0.120; 95% CI, 0.003-0.017) and games (Hedges's g, -0.162; 95% CI, -0.036 to -0.534). The effect size was larger in the upper limbs (Hedges's g, 0.287; 95% CI, 0.128-0.447) than in the lower limbs (Hedges's g, -0.113; 95% CI, -0.547 to 0.321). (4) Conclusions: Virtual reality home rehabilitation was highly effective for physical function compared to other rehabilitation technologies. Interventions that consisted of a pre-structured and tailored program applied to the upper limbs were effective for physical function and psychological outcomes.

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.

Poststroke Grasp Ability Assessment using an Intelligent Data Glove based on Action Research Arm Test: Development, Algorithms, and Experiments

Growing impact of poststroke upper extremity (UE) functional limitations entails newer dimensions in assessment methodologies. This has compelled researchers to think way beyond traditional stroke assessment scales during the out-patient rehabilitation phase. In concurrence with this, sensor-driven quantitative evaluation of poststroke UE functional limitations has become a fertile field of research. Here, we have emphasized an instrumented wearable for systematic monitoring of stroke patients with right-hemiparesis for evaluating their grasp abilities deploying intelligent algorithms. An instrumented glove housing 6 flex sensors, 3 force sensors, and a motion processing unit was developed to administer 19 activities of Action Research Arm Test (ARAT) while experimenting on 20 voluntarily participating subjects. After necessary signal conditioning, meaningful features were extracted, and subsequently the most appropriate ones were selected using the ReliefF algorithm. An optimally tuned support vector classifier was employed to classify patients with different degrees of disability and an accuracy of 92% was achieved supported by a high area under the receiver operating characteristic score. Furthermore, selected features could provide additional information that revealed the causes of grasp limitations. This would assist physicians in planning more effective poststroke rehabilitation strategies. Results of the one-way ANOVA test conducted on actual and predicted ARAT scores of the subjects indicated remarkable prospects of the proposed glove-based method in poststroke grasp ability assessment and rehabilitation.

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.

Towards a Platform for Robot-Assisted Minimally-Supervised Therapy of Hand Function: Design and Pilot Usability Evaluation

BACKGROUND

Robot-assisted therapy can increase therapy dose after stroke, which is often considered insufficient in clinical practice and after discharge, especially with respect to hand function. Thus far, there has been a focus on rather complex systems that require therapist supervision. To better exploit the potential of robot-assisted therapy, we propose a platform designed for minimal therapist supervision, and present the preliminary evaluation of its immediate usability, one of the main and frequently neglected challenges for real-world application. Such an approach could help increase therapy dose by allowing the training of multiple patients in parallel by a single therapist, as well as independent training in the clinic or at home.

METHODS

We implemented design changes on a hand rehabilitation robot, considering aspects relevant to enabling minimally-supervised therapy, such as new physical/graphical user interfaces and two functional therapy exercises to train hand motor coordination, somatosensation and memory. Ten participants with chronic stroke assessed the usability of the platform and reported the perceived workload during a single therapy session with minimal supervision. The ability to independently use the platform was evaluated with a checklist.

RESULTS

Participants were able to independently perform the therapy session after a short familiarization period, requiring assistance in only 13.46 (7.69-19.23)% of the tasks. They assigned good-to-excellent scores on the System Usability Scale to the user-interface and the exercises [85.00 (75.63-86.88) and 73.75 (63.13-83.75) out of 100, respectively]. Nine participants stated that they would use the platform frequently. Perceived workloads lay within desired workload bands. Object grasping with simultaneous control of forearm pronosupination and stiffness discrimination were identified as the most difficult tasks.

DISCUSSION

Our findings demonstrate that a robot-assisted therapy device can be rendered safely and intuitively usable upon first exposure with minimal supervision through compliance with usability and perceived workload requirements. The preliminary usability evaluation identified usability challenges that should be solved to allow real-world minimally-supervised use. Such a platform could complement conventional therapy, allowing to provide increased dose with the available resources, and establish a continuum of care that progressively increases therapy lead of the patient from the clinic to the home.

Capturing hand use of individuals with spinal cord injury at home using egocentric video: a feasibility study

STUDY DESIGN

Feasibility study.

OBJECTIVE

The objective of this study is to explore the feasibility of capturing egocentric (first person) video recordings in the home of individuals with cervical spinal cord injury (SCI) for hand function evaluation.

SETTING

Community-based study in Toronto, Ontario, Canada.

METHODS

Three participants with SCI recorded activities of daily living (ADLs) at home without the presence of a researcher. Information regarding recording characteristics and compliance was obtained as well as structured and semi-structured interviews involving privacy, usefulness, and usability. A video processing algorithm capable of detecting interactions between the hand and objects was applied to the home recordings.

RESULTS

In all, 98.58 ± 1.05% of the obtained footage was usable and included four to eight unique activities over a span of 3-7 days. The interaction detection algorithm yielded an F1 score of 0.75 ± 0.15.

CONCLUSIONS

Capturing ADLs using an egocentric camera in the home environment after SCI is feasible. Considerations regarding privacy, ease of use of the devices, and scheduling of recordings are provided.

Implementation of Wearable Sensing Technology for Movement: Pushing Forward into the Routine Physical Rehabilitation Care Field

While the promise of wearable sensor technology to transform physical rehabilitation has been around for a number of years, the reality is that wearable sensor technology for the measurement of human movement has remained largely confined to rehabilitation research labs with limited ventures into clinical practice. The purposes of this paper are to: (1) discuss the major barriers in clinical practice and available wearable sensing technology; (2) propose benchmarks for wearable device systems that would make it feasible to implement them in clinical practice across the world and (3) evaluate a current wearable device system against the benchmarks as an example. If we can overcome the barriers and achieve the benchmarks collectively, the field of rehabilitation will move forward towards better movement interventions that produce improved function not just in the clinic or lab, but out in peoples' homes and communities.

Equal Opportunities for Stroke Survivors' Rehabilitation: A Study on the Validity of the Upper Extremity Fugl-Meyer Assessment Scale Translated and Adapted into Romanian

Background and objectives: The Upper Extremity Fugl-Meyer Assessment (UEFMA) is one of the most recommended and used methods of clinical evaluation not only for post-stroke motor function disability conditions but also for physiotherapy goal-setting. Up to the present, an official Romanian version has not been officially available. This study aims to carry out a translation, adaptation, and validation of UEFMA in Romanian, thus giving both patients and medical practitioners the equal opportunity of benefiting from its proficiency. Material and methods: The English version of the motor component of UEFMA was back and forth translated in the assent of best practice translation guidelines. The research was performed on a group of 64 post-stroke in-patients regarding psychometric properties for content validation and an exploratory and confirmatory factorial analysis was performed using the Bayesian model. To assess internal consistency and test–retest reliability, we used the Cronbach Alpha index and Intraclass Correlation Coefficient (ICC). We used Pearson correlation with the Functional Independence Measure (FIM) and Modified Rankin Scale (MRS) to determine concurrent validation. Standardized response mean (SRM) was applied to determine the responsiveness of the instrument used. Results: After performing the exploratory factor analysis, a single factor was extracted, with an Eigenvalue of 19.363, which explained 64.543% of the variation. The model was confirmed by Bayesian exploration, with Root Mean Square Residual (RMR) 0.051, Goodness-of-fit Index (GFI) 0.980, Normed-Fit Index (NFI) 0.978 and Relative Fit Index (RFI) 0.977. The Cronbach Alpha value was 0.981, the Intraclass Correlation Coefficient (ICC) index for average measures was 0.992, the Pearson correlation with FIM 0.789, and MRS −0.787, while the SRM was 1.117. Conclusions: The Romanian version of the UEFMA scale is a reliable, responsive and valid tool which can be used as a standardized assessment in post-stroke patients across Romania.

Pragmatic Solutions for Stroke Recovery and Improved Quality of Life in Low- and Middle-Income Countries-A Systematic Review

Background: Given the limited healthcare resources in low and middle income countries (LMICs), effective rehabilitation strategies that can be realistically adopted in such settings are required. Objective: A systematic review of literature was conducted to identify pragmatic solutions and outcomes capable of enhancing stroke recovery and quality of life of stroke survivors for low- and middle- income countries. Methods: PubMed, HINARI, and Directory of Open Access Journals databases were searched for published Randomized Controlled Trials (RCTs) till November 2018. Only completed trials published in English with non-pharmacological interventions on adult stroke survivors were included in the review while published protocols, pilot studies and feasibility analysis of trials were excluded. Obtained data were synthesized thematically and descriptively analyzed. Results: One thousand nine hundred and ninety six studies were identified while 347 (65.22% high quality) RCTs were found to be eligible for the review. The most commonly assessed variables (and outcome measure utility) were activities of daily living [75.79% of the studies, with Barthel Index (37.02%)], motor function [66.57%; with Fugl Meyer scale (71.88%)], and gait [31.12%; with 6 min walk test (38.67%)]. Majority of the innovatively high technology interventions such as robot therapy (95.24%), virtual reality (94.44%), transcranial direct current stimulation (78.95%), transcranial magnetic stimulation (88.0%) and functional electrical stimulation (85.00%) were conducted in high income countries. Several traditional and low-cost interventions such as constraint-induced movement therapy (CIMT), resistant and aerobic exercises (R&AE), task oriented therapy (TOT), body weight supported treadmill training (BWSTT) were reported to significantly contribute to the recovery of motor function, activity, participation, and improvement of quality of life after stroke. Conclusion: Several pragmatic, in terms of affordability, accessibility and utility, stroke rehabilitation solutions, and outcome measures that can be used in resource-limited settings were found to be effective in facilitating and enhancing post-stroke recovery and quality of life.

Low-cost equipment for the evaluation of reach and grasp in post-stroke individuals: a pilot study

Background

Reach–grasp movements are motor components commonly affected after stroke and directly related to the independence of these individuals. Evaluations of these activities can be performed using clinical instruments and assessed by detailed and costly kinematic analyses. The aim of this study was to develop an analysis of reach–grasp movements in post-stroke patients using a simple, inexpensive, and manageable instrument.

Results

A Mann–Whitney test was used to compare paretic and non-paretic limb motor performance. A statistically significant difference was found between the variables of total time (p = 0.02) and speed to reach target 3 (p = 0.04) for task 1, while in task 2 significance was found only in the aspect of speed to reach target 2 (p = 0.04). The correlation between clinical tests and variables of tasks was then performed using Spearman’s rank correlation coefficient. At task 1, when compared with the REACH instrument, the close target sub-item; there was a high positive correlation between the parameters of total time (p = 0.028), target velocity 3 (p = 0.028), and target acceleration 3 (p = 0.028). Another instrument that showed a high positive correlation with the target time 3 (p = 0.01) and target acceleration 3 (p = 0.028) variables was the Box and Block Test. When correlated, the data between the task 2 variables and clinical instruments did not present statistically significant data.

Conclusion

Our instrument—the Temporal Data Acquisition Instrument—TDAI—fulfilled the expected objectives and can be used as an option to evaluate the movements of reach and grasp of upper limb post-stroke, using an easy and fast application, without the need for calibration.

Trial registration Trial Registration: Research Ethics Committee of the Trairi School of Health Sciences—Number 2.625.609, approved on April 13, 2018; Brazilian Registry of Clinical Trials—RBR-4995cr approved on July 4, 2019 retrospectively registered (http://www.ensaiosclinicos.gov.br/rg/RBR-4995cr/)

Effectiveness of Upper Limb Wearable Technology for Improving Activity and Participation in Adult Stroke Survivors: Systematic Review

BACKGROUND

With advances in technology, the adoption of wearable devices has become a viable adjunct in poststroke rehabilitation. Upper limb (UL) impairment affects up to 77% of stroke survivors impacting on their ability to carry out everyday activities. However, despite an increase in research exploring these devices for UL rehabilitation, little is known of their effectiveness.

OBJECTIVE

This review aimed to assess the effectiveness of UL wearable technology for improving activity and participation in adult stroke survivors.

METHODS

Randomized controlled trials (RCTs) and randomized comparable trials of UL wearable technology for poststroke rehabilitation were included. Primary outcome measures were validated measures of activity and participation as defined by the International Classification of Functioning, Disability, and Health. Databases searched were MEDLINE, Web of Science (Core collection), CINAHL, and the Cochrane Library. The Cochrane Risk of Bias Tool was used to assess the methodological quality of the RCTs and the Downs and Black Instrument for the quality of non RCTs.

RESULTS

In the review, we included 11 studies with collectively 354 participants at baseline and 323 participants at final follow-up including control groups and participants poststroke. Participants' stroke type and severity varied. Only 1 study found significant between-group differences for systems functioning and activity (P≤.02). The 11 included studies in this review had small sample sizes ranging from 5 to 99 participants at an average (mean) age of 57 years.

CONCLUSIONS

This review has highlighted a number of reasons for insignificant findings in this area including low sample sizes and the appropriateness of the methodology for complex interventions. However, technology has the potential to measure outcomes, provide feedback, and engage users outside of clinical sessions. This could provide a platform for motivating stroke survivors to carry out more rehabilitation in the absence of a therapist, which could maximize recovery.

TRIAL REGISTRATION

PROSPERO CRD42017057715; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=57715.

Upper Limb Performance in Daily Life Improves Over the First 12 Weeks Poststroke

Background. Upper limb (UL) performance, or use, in daily life is complex and likely influenced by many factors. While the recovery trajectory of UL impairment poststroke is well documented, little is known about the recovery trajectory of sensor-measured UL performance in daily life early after stroke and the potential moderating role of psychosocial factors. Objective. To examine the recovery trajectory of UL performance within the first 12 weeks poststroke and characterize the potential moderating role of belief, confidence, and motivation on UL performance. Methods. This was a longitudinal, prospective cohort study quantifying UL performance and related psychosocial factors early after stroke. UL performance was quantified via bilateral, wrist-worn accelerometers over 5 assessment sessions for 24 hours. Belief, confidence, and motivation to use the paretic UL, and self-perceived barriers to UL recovery were quantified via survey. Change in 4 accelerometer variables and the moderating role of psychosocial factors was tested using hierarchical linear modeling. The relationship between self-perceived barriers and UL performance was tested via Spearman rank-order correlation analysis. Results. UL performance improved over the first 12 weeks after stroke. Belief, confidence, and motivation did not moderate UL performance over time. There was a negative relationship between UL performance and self-perceived barriers to UL recovery at week 2, which declined over time. Conclusions. Sensor-measured UL performance can improve early after stroke. Early after stroke, rehabilitation interventions may not need to directly target belief, confidence, and motivation but may instead focus on reducing self-perceived barriers to UL recovery.

Belief, Confidence, and Motivation to Use the Paretic Upper Limb in Daily Life Over the First 24 Weeks After Stroke

BACKGROUND AND PURPOSE

The recovery patterns of upper limb (UL) impairment after stroke are established. Psychosocial factors such as belief that paretic UL recovery is possible, confidence, and motivation to use the paretic UL in everyday tasks are unexplored early after stroke. The purpose of this exploratory study was to characterize belief, confidence, and motivation to use the paretic UL in daily life, and self-perceived barriers to UL recovery over the first 24 weeks after stroke.

METHODS

This was a longitudinal cohort study (N = 30) with 8 assessment sessions over the first 24 weeks after stroke. Belief, confidence, and motivation to use the paretic UL and self-perceived barriers were quantified via survey and analyzed using descriptive statistics. Change in the number of self-perceived barriers between weeks 2 and 24 was tested using a paired-samples t test. The relationship between UL capacity, depressive symptomatology, cognition, and each psychosocial factor was examined using Spearman rank-order correlation analyses.

RESULTS

Twenty-two participants completed all study assessments. Belief, confidence, and motivation were high across the 24 weeks, with little variation. There was no difference between the average number of barriers from weeks 2 to 24. There was no relationship between the clinical measures and psychosocial factors at week 2, 12, or 24.

DISCUSSION AND CONCLUSIONS

High levels of belief, confidence, and motivation appear consistent over the first 6 months after stroke. The lack of correlations between psychosocial factors and clinical measures suggests belief, confidence, and motivation may not be vulnerable to functional status early after stroke.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1 available at: http://links.lww.com/JNPT/A283).

Egocentric video: a new tool for capturing hand use of individuals with spinal cord injury at home

Background

Current upper extremity outcome measures for persons with cervical spinal cord injury (cSCI) lack the ability to directly collect quantitative information in home and community environments. A wearable first-person (egocentric) camera system is presented that aims to monitor functional hand use outside of clinical settings.

Methods

The system is based on computer vision algorithms that detect the hand, segment the hand outline, distinguish the user’s left or right hand, and detect functional interactions of the hand with objects during activities of daily living. The algorithm was evaluated using egocentric video recordings from 9 participants with cSCI, obtained in a home simulation laboratory. The system produces a binary hand-object interaction decision for each video frame, based on features reflecting motion cues of the hand, hand shape and colour characteristics of the scene.

Results

The output from the algorithm was compared with a manual labelling of the video, yielding F1-scores of 0.74 ± 0.15 for the left hand and 0.73 ± 0.15 for the right hand. From the resulting frame-by-frame binary data, functional hand use measures were extracted: the amount of total interaction as a percentage of testing time, the average duration of interactions in seconds, and the number of interactions per hour. Moderate and significant correlations were found when comparing these output measures to the results of the manual labelling, with ρ = 0.40, 0.54 and 0.55 respectively.

Conclusions

These results demonstrate the potential of a wearable egocentric camera for capturing quantitative measures of hand use at home.

Changes in actual arm-hand use in stroke patients during and after clinical rehabilitation involving a well-defined arm-hand rehabilitation program: A prospective cohort study

Introduction

Improvement of arm-hand function and arm-hand skill performance in stroke patients is reported by many authors. However, therapy content often is poorly described, data on actual arm-hand use are scarce, and, as follow-up time often is very short, little information on patients’ mid- and long-term progression is available. Also, outcome data mainly stem from either a general patient group, unstratified for the severity of arm-hand impairment, or a very specific patient group.

Objectives

To investigate to what extent the rate of improvement or deterioration of actual arm-hand use differs between stroke patients with either a severely, moderately or mildly affected arm-hand, during and after rehabilitation involving a well-defined rehabilitation program.

Methods

Design: single–armed prospective cohort study. Outcome measure: affected arm-hand use during daily tasks (accelerometry), expressed as ‘Intensity-of arm-hand-use’ and ‘Duration-of-arm-hand-use’ during waking hours. Measurement dates: at admission, clinical discharge and 3, 6, 9, and 12 months post-discharge. Statistics: Two-way repeated measures ANOVAs.

Results

Seventy-six patients (63 males); mean age: 57.6 years (sd:10.6); post-stroke time: 29.8 days (sd:20.1) participated. Between baseline and 1-year follow-up, Intensity-of-arm-hand-use on the affected side increased by 51%, 114% and 14% (p < .000) in the mildly, moderately and severely affected patients, respectively. Similarly, Duration-of-arm-hand-use increased by 26%, 220% and 161% (p < .000). Regarding bimanual arm-hand use: Intensity-of-arm-hand-use increased by 44%, 74% and 30% (p < .000), whereas Duration-of-arm-hand-use increased by 10%, 22% and 16% (p < .000).

Conclusion

Stroke survivors with a severely, moderately or mildly affected arm-hand showed different, though (clinically) important, improvements in actual arm-hand use during the rehabilitation phase. Intensity-of-arm-hand-use and Duration-of-arm-hand-use significantly improved in both unimanual and bimanual tasks/skills. These improvements were maintained until at least 1 year post-discharge.

Home-based technologies for stroke rehabilitation: A systematic review

BACKGROUND

Many forms of home-based technology targeting stroke rehabilitation have been devised, and a number of human factors are important to their application, suggesting the need to examine this information in a comprehensive review.

OBJECTIVE

The systematic review aims to synthesize the current knowledge of technologies and human factors in home-based technologies for stroke rehabilitation.

METHODS

We conducted a systematic literature search in three electronic databases (IEEE, ACM, PubMed), including secondary citations from the literature search. We included articles that used technological means to help stroke patients conduct rehabilitation at home, reported empirical studies that evaluated the technologies with patients in the home environment, and were published in English. Three authors independently conducted the content analysis of searched articles using a list of interactively defined factors.

RESULTS

The search yielded 832 potentially relevant articles, leading to 31 articles that were included for in-depth analysis. The types of technology of reviewed articles included games, telerehabilitation, robotic devices, virtual reality devices, sensors, and tablets. We present the merits and limitations of each type of technology. We then derive two main human factors in designing home-based technologies for stroke rehabilitation: designing for engagement (including external and internal motivation) and designing for the home environment (including understanding the social context, practical challenges, and technical proficiency).

CONCLUSION

This systematic review presents an overview of key technologies and human factors for designing home-based technologies for stroke rehabilitation.

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

BACKGROUND

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

OBJECTIVES

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

SEARCH METHODS

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

SELECTION CRITERIA

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

DATA COLLECTION AND ANALYSIS

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

MAIN RESULTS

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

AUTHORS' CONCLUSIONS

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

Assessment of the Efficacy of ReoGo-J Robotic Training Against Other Rehabilitation Therapies for Upper-Limb Hemiplegia After Stroke: Protocol for a Randomized Controlled Trial

Background: Stroke patients experience chronic hemiparesis in their upper extremities leaving negative effects on quality of life. Robotic therapy is one method to recover arm function, but its research is still in its infancy. Research questions of this study is to investigate how to maximize the benefit of robotic therapy using ReoGo-J for arm hemiplegia in chronic stroke patients.

Methods: Design of this study is a multi-center parallel group trial following the prospective, randomized, open-label, blinded endpoint (PROBE) study model. Participants and setting will be 120 chronic stroke patients (over 6 months post-stroke) will be randomly allocated to three different rehabilitation protocols. In this study, the control group will receive 20 min of standard rehabilitation (conventional occupational therapy) and 40 min of self-training (i.e., sanding, placing and stretching). The robotic therapy group will receive 20 min of standard rehabilitation and 40 min of robotic therapy using ReoGo®-J device. The combined therapy group will receive 40 min of robotic therapy and 20 min of constraint-induced movement therapy (protocol to improve upper-limb use in ADL suggests). This study employs the Fugl-Meyer Assessment upper-limb score (primary outcome), other arm function measures and the Stroke Impact Scale score will be measured at baseline, 5 and 10 weeks of the treatment phase. In analysis of this study, we use the mixed effects model for repeated measures to compare changes in outcomes between groups at 5 and 10 Weeks. The registration number of this study is UMIN000022509.

Conclusions: This study is a feasible, multi-site randomized controlled trial to examine our hypothesis that combined training protocol could maximize the benefit of robotic therapy and best effective therapeutic strategy for patients with upper-limb hemiparesis.

Comparison of proximal versus distal upper-limb robotic rehabilitation on motor performance after stroke: a cluster controlled trial

This study examined the treatment efficacy of proximal-emphasized robotic rehabilitation by using the InMotion ARM (P-IMT) versus distal-emphasized robotic rehabilitation by using the InMotion WRIST (D-IMT) in patients with stroke. A total of 40 patients with stroke completed the study. They received P-IMT, D-IMT, or control treatment (CT) for 20 training sessions. Primary outcomes were the Fugl-Meyer Assessment (FMA) and Medical Research Council (MRC) scale. Secondary outcomes were the Motor Activity Log (MAL) and wrist-worn accelerometers. The differences on the distal FMA, total MRC, distal MRC, and MAL quality of movement scores among the 3 groups were statistically significant (P = 0.02 to 0.05). Post hoc comparisons revealed that the D-IMT group significantly improved more than the P-IMT group on the total MRC and distal MRC. Furthermore, the distal FMA and distal MRC improved more in the D-IMT group than in the CT group. Our findings suggest that distal upper-limb robotic rehabilitation using the InMotion WRIST system had superior effects on distal muscle strength. Further research based on a larger sample is needed to confirm long-term treatment effects of proximal versus distal upper-limb robotic rehabilitation.

Exercising daily living activities in robot-mediated therapy

[Purpose] Investigation of the efficacy of robot-mediated therapy of the upper limb in patients with chronic stroke, in task-oriented training activities of daily living in real environment. [Subjects and Methods] 20 patients, each more than one year post-stroke (13-71 months) received 20 sessions of upper limb robot-mediated therapy. No other treatment was given. Each therapy session consisted of a passive motion and an active task therapy. During the active therapy, subjects exercised 5 activities of daily living. Assessments of the subjects were blind, and conducted one month prior to, at the start, at the end, and three months after the therapy course. The following outcome measures were recorded: Fugl-Meyer Scale-upper extremity subsection, Modified Ashworth Scale, Action Research Arm Test, Functional Independence Measure, Barthel Index. [Results] Significant improvements were observed between the start and the end of the therapy, except for Modified Ashworth Scale and Barthel Index. Results still held up at the follow-up visit three months later. [Conclusion] Practicing activities of daily living in real environment with robot-mediated physical therapy can improve the motor and functional ability of patients, even with relatively good initial functions, and even years post-stroke.

A Method for Quantifying Upper Limb Performance in Daily Life Using Accelerometers

A key reason for referral to rehabilitation services after stroke and other neurological conditions is to improve one's ability to function in daily life. It has become important to measure a person's activities in daily life, and not just measure their capacity for activity in the structured environment of a clinic or laboratory. A wearable sensor that is now enabling measurement of daily movement is the accelerometer. Accelerometers are commercially-available devices resembling large wrist watches that can be worn throughout the day. Data from accelerometers can quantify how the limbs are engaged to perform activities in peoples' homes and communities. This report describes a methodology to collect accelerometry data and turn it into clinically-relevant information. First, data are collected by having the participant wear two accelerometers (one on each wrist) for 24 h or longer. The accelerometry data are then downloaded and processed to produce four different variables that describe key aspects of upper limb activity in daily life: hours of use, use ratio, magnitude ratio, and the bilateral magnitude. Density plots can be constructed that visually represent the data from the 24 h wearing period. The variables and their resultant density plots are highly consistent in neurologically-intact, community-dwelling adults. This striking consistency makes them a useful tool for determining if upper limb daily performance is different from normal. This methodology is appropriate for research studies investigating upper limb dysfunction and interventions designed to improve upper limb performance in daily life in people with stroke and other patient populations. Because of its relative simplicity, it may not be long before it is also incorporated in clinical neurorehabilitation practice.

Use of Machine Learning Classifiers and Sensor Data to Detect Neurological Deficit in Stroke Patients

Background

The pronator drift test (PDT), a neurological examination, is widely used in clinics to measure motor weakness of stroke patients.

Objective

The aim of this study was to develop a PDT tool with machine learning classifiers to detect stroke symptoms based on quantification of proximal arm weakness using inertial sensors and signal processing.

Methods

We extracted features of drift and pronation from accelerometer signals of wearable devices on the inner wrists of 16 stroke patients and 10 healthy controls. Signal processing and feature selection approach were applied to discriminate PDT features used to classify stroke patients. A series of machine learning techniques, namely support vector machine (SVM), radial basis function network (RBFN), and random forest (RF), were implemented to discriminate stroke patients from controls with leave-one-out cross-validation.

Results

Signal processing by the PDT tool extracted a total of 12 PDT features from sensors. Feature selection abstracted the major attributes from the 12 PDT features to elucidate the dominant characteristics of proximal weakness of stroke patients using machine learning classification. Our proposed PDT classifiers had an area under the receiver operating characteristic curve (AUC) of .806 (SVM), .769 (RBFN), and .900 (RF) without feature selection, and feature selection improves the AUCs to .913 (SVM), .956 (RBFN), and .975 (RF), representing an average performance enhancement of 15.3%.

Conclusions

Sensors and machine learning methods can reliably detect stroke signs and quantify proximal arm weakness. Our proposed solution will facilitate pervasive monitoring of stroke patients.

Does Task-Specific Training Improve Upper Limb Performance in Daily Life Poststroke?

BACKGROUND

A common assumption is that changes in upper limb (UL) capacity, or what an individual is capable of doing, translates to improved UL performance in daily life, or what an individual actually does. This assumption should be explicitly tested for individuals with UL paresis poststroke.

OBJECTIVE

To examine changes in UL performance after an intensive, individualized, progressive, task-specific UL intervention for individuals at least 6 months poststroke.

METHODS

Secondary analysis on 78 individuals with UL paresis who participated in a phase II, single-blind, randomized parallel dose-response trial. Participants were enrolled in a task-specific intervention for 8 weeks. Participants were randomized into 1 of 4 treatment groups with each group completing different amounts of UL movement practice. UL performance was assessed with bilateral, wrist-worn accelerometers once a week for 24 hours throughout the duration of the study. The 6 accelerometer variables were tested for change and the influence of potential modifiers using hierarchical linear modeling.

RESULTS

No changes in UL performance were found on any of the 6 accelerometer variables used to quantify UL performance. Neither changes in UL capacity nor the overall amount of movement practice influenced changes in UL performance. Stroke chronicity, baseline UL capacity, concordance, and ADL status significantly increased the baseline starting points but did not influence the rate of change (slopes) for participants.

CONCLUSIONS

Improved motor capacity resulting from an intensive outpatient UL intervention does not appear to translate to increased UL performance outside the clinic.

Balance evaluation techniques and physical therapy in post-stroke patients: A literature review

A stroke (cerebrovascular accident - CVA) is a significant social-economic issue. Approximately 15-30% of all patients develop life-long disability, 20% require over 3 months of specialized care in healthcare institutions, and the majority of the patients never recover the ability to maintain a proper vertical position. Such CVA sequelae as balance disturbances not only negatively affect patients' daily physical activity, but also result in social isolation. A number of standardized clinical scales, tests, and instrumental examination techniques have been proposed for evaluating not only post-CVA balance function, but also any changes in this function following various interventions. Even though scientific literature lists numerous methods and instruments for the improvement of balance after a CVA, not all of them are equally effective, and there have been rather controversial evaluations of some techniques. Nevertheless, the application of the majority of the techniques as complementary or alternative measures to traditional physical therapy (PT) frequently yields better results.

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

BACKGROUND

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Remote Physical Activity Monitoring in Neurological Disease: A Systematic Review

OBJECTIVE

To perform a systematic review of studies using remote physical activity monitoring in neurological diseases, highlighting advances and determining gaps.

METHODS

Studies were systematically identified in PubMed/MEDLINE, CINAHL and SCOPUS from January 2004 to December 2014 that monitored physical activity for ≥24 hours in adults with neurological diseases. Studies that measured only involuntary motor activity (tremor, seizures), energy expenditure or sleep were excluded. Feasibility, findings, and protocols were examined.

RESULTS

137 studies met inclusion criteria in multiple sclerosis (MS) (61 studies); stroke (41); Parkinson's Disease (PD) (20); dementia (11); traumatic brain injury (2) and ataxia (1). Physical activity levels measured by remote monitoring are consistently low in people with MS, stroke and dementia, and patterns of physical activity are altered in PD. In MS, decreased ambulatory activity assessed via remote monitoring is associated with greater disability and lower quality of life. In stroke, remote measures of upper limb function and ambulation are associated with functional recovery following rehabilitation and goal-directed interventions. In PD, remote monitoring may help to predict falls. In dementia, remote physical activity measures correlate with disease severity and can detect wandering.

CONCLUSIONS

These studies show that remote physical activity monitoring is feasible in neurological diseases, including in people with moderate to severe neurological disability. Remote monitoring can be a psychometrically sound and responsive way to assess physical activity in neurological disease. Further research is needed to ensure these tools provide meaningful information in the context of specific neurological disorders and patterns of neurological disability.

Exploring the Role of Accelerometers in the Measurement of Real World Upper-Limb Use After Stroke

The ultimate goal of upper-limb rehabilitation after stroke is to promote real-world use, that is, use of the paretic upper-limb in everyday activities outside the clinic or laboratory. Although real-world use can be collected through self-report questionnaires, an objective indicator is preferred. Accelerometers are a promising tool. The current paper aims to explore the feasibility of accelerometers to measure upper-limb use after stroke and discuss the translation of this measurement tool into clinical practice. Accelerometers are non-invasive, wearable sensors that measure movement in arbitrary units called activity counts. Research to date indicates that activity counts are a reliable and valid index of upper-limb use. While most accelerometers are unable to distinguish between the type and quality of movements performed, recent advancements have used accelerometry data to produce clinically meaningful information for clinicians, patients, family and care givers. Despite this, widespread uptake in research and clinical environments remains limited. If uptake was enhanced, we could build a deeper understanding of how people with stroke use their arm in real-world environments. In order to facilitate greater uptake, however, there is a need for greater consistency in protocol development, accelerometer application and data interpretation.

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

BACKGROUND

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

OBJECTIVES

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

SEARCH METHODS

We searched the Cochrane Stroke Group's Trials Register (last searched February 2015), the Cochrane Central Register of Controlled Trials (CENTRAL) (the Cochrane Library 2015, Issue 3), MEDLINE (1950 to March 2015), EMBASE (1980 to March 2015), CINAHL (1982 to March 2015), AMED (1985 to March 2015), SPORTDiscus (1949 to March 2015), PEDro (searched April 2015), Compendex (1972 to March 2015), and Inspec (1969 to March 2015). We also handsearched relevant conference proceedings, searched trials and research registers, checked reference lists, and contacted trialists, experts, and researchers in our field, as well as manufacturers of commercial devices.

SELECTION CRITERIA

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

DATA COLLECTION AND ANALYSIS

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

MAIN RESULTS

We included 34 trials (involving 1160 participants) in this update of our review. Electromechanical and robot-assisted arm training improved activities of daily living scores (SMD 0.37, 95% confidence interval (CI) 0.11 to 0.64, P = 0.005, I² = 62%), arm function (SMD 0.35, 95% CI 0.18 to 0.51, P < 0.0001, I² = 36%), and arm muscle strength (SMD 0.36, 95% CI 0.01 to 0.70, P = 0.04, I² = 72%), but the quality of the evidence was low to very low. Electromechanical and robot-assisted arm training did not increase the risk of participant drop-out (RD 0.00, 95% CI -0.02 to 0.03, P = 0.84, I² = 0%) with moderate-quality evidence, and adverse events were rare.

AUTHORS' CONCLUSIONS

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

Evaluation of a portable markerless finger position capture device: accuracy of the Leap Motion controller in healthy adults

Although motion analysis is frequently employed in upper limb motor assessment (e.g. visually-guided reaching), they are resource-intensive and limited to laboratory settings. This study evaluated the reliability and accuracy of a new markerless motion capture device, the Leap Motion controller, to measure finger position. Testing conditions that influence reliability and agreement between the Leap and a research-grade motion capture system were examined. Nine healthy young adults pointed to 15 targets on a computer screen under two conditions: (1) touching the target (touch) and (2) 4 cm away from the target (no-touch). Leap data was compared to an Optotrak marker attached to the index finger. Across all trials, root mean square (RMS) error of the Leap system was 17.30  ±  9.56 mm (mean ± SD), sampled at 65.47  ±  21.53 Hz. The % viable trials and mean sampling rate were significantly lower in the touch condition (44% versus 64%, p < 0.001; 52.02  ±  2.93 versus 73.98  ±  4.48 Hz, p = 0.003). While linear correlations were high (horizontal: r(2) = 0.995, vertical r(2) = 0.945), the limits of agreement were large (horizontal: -22.02 to +26.80 mm, vertical: -29.41 to +30.14 mm). While not as precise as more sophisticated optical motion capture systems, the Leap Motion controller is sufficiently reliable for measuring motor performance in pointing tasks that do not require high positional accuracy (e.g. reaction time, Fitt's, trails, bimanual coordination).

Recognizing complex upper extremity activities using body worn sensors

To evaluate arm-hand therapies for neurological patients it is important to be able to assess actual arm-hand performance objectively. Because instruments that measure the actual quality and quantity of specific activities in daily life are lacking, a new measure needs to be developed. The aims of this study are to a) elucidate the techniques used to identify upper extremity activities, b) provide a proof-of-principle of this method using a set of activities tested in a healthy adult and in a stroke patient, and c) provide an example of the method’s applicability in daily life based on readings taken from a healthy adult. Multiple devices, each of which contains a tri-axial accelerometer, a tri-axial gyroscope and a tri-axial magnetometer were attached to the dominant hand, wrist, upper arm and chest of 30 healthy participants and one stroke patient, who all performed the tasks ‘drinking’, ‘eating’ and ‘brushing hair’ in a standardized environment. To establish proof-of-principle, a prolonged daily life recording of 1 participant was used to identify the task ‘drinking’. The activities were identified using multi-array signal feature extraction and pattern recognition algorithms and 2D-convolution. The activities ‘drinking’, ‘eating’ and ‘brushing hair’ were unambiguously recognized in a sequence of recordings of multiple standardized daily activities in a healthy participant and in a stroke patient. It was also possible to identify a specific activity in a daily life recording. The long term aim is to use this method to a) identify arm-hand activities that someone performs during daily life, b) determine the quantity of activity execution, i.e. amount of use, and c) determine the quality of arm-hand skill performance.