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

Gamified devices for stroke rehabilitation: A systematic review

BACKGROUND AND OBJECTIVE

Rehabilitation after stroke is essential to minimize permanent disability. Gamification, the integration of game elements into non-game environments, has emerged as a promising strategy for increasing motivation and rehabilitation effectiveness. This article systematically reviews the gamified devices used in stroke rehabilitation and evaluates their impact on emotional, social, and personal effects on patients, providing a comprehensive view of gamified rehabilitation.

METHODS

A comprehensive search using the PRISMA 2020 guidelines was conducted using the IEEE Xplore, PubMed, Springer Link, APA PsycInfo, and ScienceDirect databases. Empirical studies published between January 2019 and December 2023 that quantified the effects of gamification in terms of usability, motivation, engagement, and other qualitative patient responses were selected.

RESULTS

In total, 169 studies involving 6404 patients were included. Gamified devices are categorized into four types: robotic/motorized, non-motorized, virtual reality, and neuromuscular electrical stimulation. The results showed that gamified devices not only improved motor and cognitive function but also had a significant positive impact on patients' emotional, social and personal levels. Most studies have reported high levels of patient satisfaction and motivation, highlighting the effectiveness of gamification in stroke rehabilitation.

CONCLUSIONS

Gamification in stroke rehabilitation offers significant benefits beyond motor and cognitive recovery by improving patients' emotional and social well-being. This systematic review provides a comprehensive overview of the most effective gamified technologies and highlights the need for future multidisciplinary research to optimize the design and implementation of gamified solutions in stroke rehabilitation.

Effects of wearable device training on upper limb motor function in patients with stroke: a systematic review and meta-analysis

OBJECTIVE

To evaluate the effect of wearable device training on improving upper limb motor function in patients who experienced strokes.

METHODS

The PubMed, Embase, Cochrane Library, Web of Science, MEDLINE, SCOPUS, China National Knowledge Infrastructure, WanFang, and VIP databases were searched for randomized controlled trials (RCTs) that assessed the effectiveness of wearable device training in improving upper limb motor function in patients with stroke. Two investigators independently screened studies by their titles and abstracts and cross-checked, downloaded, and evaluated the results. Disagreements were resolved by a third highly experienced researcher. Risk of bias was evaluated using the Cochrane risk-of-bias tool. This meta-analysis was registered in PROSPERO (registration No. CRD42023421633).

RESULTS

This study comprised 508 patients from 14 RCTs. The experimental group assessed various wearable devices, including 3D-printed dynamic orthoses, inertial measurement unit (IMU) sensors, electrical stimulation devices, and virtual reality (VR) devices for virtual interactive training. The control group received traditional rehabilitation therapies, including physical and conventional rehabilitation. The experimental group scored better on the Fugl-Meyer Assessment (FMA-UE) scale (standardized mean difference [SMD] 0.26, 95% confidence interval [CI] 0.07, 0.45) and Box and Block Test (BBT) (SMD 0.43, 95% CI 0.17, 0.69) versus controls. No significant intergroup differences were observed in the Action Research Arm Test (SMD 0.20, 95% CI -0.15, 0.55), motor activity log (mean difference [MD] 0.32, 95% CI -0.54, 0.33), and modified Ashworth scale (MD -0.08, 95% CI -0.81, 0.64). The probability rankings of wearable devices that improved FMA-UE scores in patients with stroke were: orthotic devices, with the highest probability ranking of 0.45, followed by sensor devices at 0.23, electrical stimulation devices at 0.21, and VR devices at 0.11.

CONCLUSIONS

Wearable device training was found to significantly improve upper limb motor function in patients with stroke, particularly for large-range movements. Improvements in FMA-UE and BBT scores reflected reduced impairment and enhanced manual dexterity, respectively. However, the training had no significant effect on hand movement frequency, fine motor skills, or spasticity. Among the different wearable devices tested, orthoses produced the most effective results.

Effects of a Wearable-Based Intervention on the Hemiparetic Upper Limb in Persons With Stroke: A Randomized Controlled Trial

INTRODUCTION

Wearables have emerged as a transformative rehabilitation tool to provide self-directed training in the home. Objective. In this study, we examined the efficacy of a novel wearable device, "Smart Reminder" (SR), to provide home-based telerehabilitation for hemiparetic upper limb (UL) training in persons with stroke.

METHODS

Forty stroke survivors from community support groups were randomized (stratified by the period after stroke onset and impairment severity) to either the SR group or the sham device group. Participants received either 20 hours of telerehabilitation using the SR device or training with pictorial handouts and a sham device over 4 weeks. In addition, all participants wore a standard accelerometer for 3 hours each day, 5 times a week, outside the prescribed training. Participants were assessed by a masked assessor at baseline, post-intervention (week 4), and follow-up (week 8). The outcome measures included Fugl-Meyer Assessment for Upper Extremity (FMA-UE), Action Research Arm Test, Motor Activity Log, muscle strength, active range of motion and amount of movement of the UL, and compliance rate of training.

RESULTS

The SR group improved substantially in their FMA-UE scores after treatment (mean difference = 2.05, P = .036) compared to the sham group. Also, adherence to the training using the SR device was significantly higher, 97%, than the sham group, 82.3% (P = .038).

CONCLUSION

The 4-week telerehabilitation program using a "SR" device demonstrated potential efficacy in improving FMA-UE scores of the hemiparetic upper limb. However, it did not significantly enhance the performance of the affected limb in daily activities. The trial was registered on ClinicalTrial.gov (URL: http://www.clinicaltrials.gov) with the identifier NCT05877183.

Addressing Data Absenteeism and Technology Chauvinism in the Use of Gamified Wearable Gloves Among Older Adults: Moderated Usability Study

BACKGROUND

Digital health technologies have the potential to improve health outcomes for older adults, especially for those recovering from stroke. However, there are challenges to developing these technologies, such as data absenteeism (where older adults' views are often underrepresented in research and development) and technology chauvinism (the belief that sophisticated technology alone is the panacea to addressing health problems), which hinder their effectiveness.

OBJECTIVE

In this study, we aimed to address these challenges by developing a wearable glove integrated with culturally relevant exergames to motivate older adults to exercise and, for those recovering from stroke, to adhere to rehabilitation.

METHODS

We conducted a moderated usability study with 19 older adults, of which 11 (58%) had a history of stroke. Our participants engaged in a 30-minute gameplay session with the wearable glove integrated with exergames, followed by a quantitative survey and an in-depth interview. We used descriptive analysis to compare responses to the System Usability Scale between those who had a history of stroke and those who did not. In addition, we analyzed the qualitative interviews using a bottom-up thematic analysis to identify key themes related to the motivations and barriers regarding the use of wearable gloves for rehabilitation and exercise.

RESULTS

Our study generated several key insights. First, making the exergames exciting and challenging could improve exercise and rehabilitation motivation, but it could also have a boomerang effect, where participants may become demotivated if the games were very challenging. Second, the comfort and ease of use of the wearable gloves were important for older adults, regardless of their stroke history. Third, for older adults with a history of stroke, the functionality and purpose of the wearable glove were important in helping them with specific exercise movements.

CONCLUSIONS

Our findings highlight the importance of providing contextual support for the effective use of digital technologies, particularly for older adults recovering from stroke. In addition to technology and usability factors, other contextual factors such as gamification and social support (from occupational therapists or caregivers) should be considered to provide a comprehensive approach to addressing health problems. To overcome data absenteeism and technology chauvinism, it is important to develop digital health technologies that are tailored to the needs of underserved communities. Our study provides valuable insights for the development of digital health technologies that can motivate older adults recovering from stroke to exercise and adhere to rehabilitation.

Use of the Capability, Opportunity and Motivation Behaviour model (COM-B) to Understand Interventions to Support Physical Activity Behaviour in People with Stroke: An Overview of Reviews

OBJECTIVE

Physical activity in people with stroke remains low despite considerable research. This overview aimed to provide high-level synthesis and aid clinical decision-making. The Capability, Opportunity, Motivation-Behaviour (COM-B) model was used to classify interventions to understand which components improve physical activity behaviour in people with stroke.

DATA SOURCES

CINAHL, Cochrane Database, MEDLINE, PEDro, PsychINFO, SPORTDiscus.

REVIEW METHODS

A systematic search was conducted (November 2023) to identify reviews of interventions to improve physical activity in people with stroke. Results were screened and assessed for eligibility. Participant characteristics, intervention classification using COM-B, and effect of intervention were extracted. Quality was assessed using AMSTAR2, and Corrected Cover Analysis for study overlap. Narrative synthesis was used to understand components of interventions to improve physical activity behaviour.

RESULTS

1801 references were screened and 29 full-text references assessed for eligibility. Twenty reviews were included. Quality ranged from critically low (n = 3) to high (n = 10). Study overlap calculated using corrected cover area indicated slight overlap (0.028) and minimal reporting bias.The majority of participants were mobile with mild stroke and community dwelling. Twenty-three interventions were classified using COM-B. Three of twelve interventions classified to one aspect of the COM-B were effective. Fourteen of sixteen effective interventions combined at least two COM-B elements, ten of these combined capability and motivation.

CONCLUSION

Interventions including at least two elements of the COM-B are most likely to improve physical activity in mobile stroke survivors. Further research is needed to understand physical activity behaviour in those with moderate to severe stroke.

Multicentre pilot randomised control trial of a self-directed exergaming intervention for poststroke upper limb rehabilitation: research protocol

INTRODUCTION

Technology-facilitated, self-directed upper limb (UL) rehabilitation, as an adjunct to conventional care, could enhance poststroke UL recovery compared with conventional care alone, without imposing additional resource burden. The proposed pilot randomised controlled trial (RCT) aims to assess whether stroke survivors will engage in self-directed UL training, explore factors associated with intervention adherence and evaluate the study design for an RCT testing the efficacy of a self-directed exer-gaming intervention for UL recovery after stroke.

METHODS AND ANALYSIS

This is a multicentre, internal pilot RCT; parallel design, with nested qualitative methods. The sample will consist of stroke survivors with UL paresis, presenting within the previous 30 days. Participants randomised to the intervention group will be trained to use an exergaming device and will be supported to adopt this as part of their self-directed rehabilitation (ie, without formal support/supervision) for a 3-month period. The primary outcome will be the Fugl Meyer Upper Extremity Assessment (FM-UE) at 6 months poststroke. Secondary outcomes are the Action Research Arm Test (ARAT), the Barthel Index and the Modified Rankin Scale. Assessment time points will be prior to randomisation (0-1 month poststroke), 3 months and 6 months poststroke. A power calculation to inform sample size required for a definitive RCT will be conducted using FM-UE data from the sample across 0-6 months time points. Semistructured qualitative interviews will examine factors associated with intervention adoption. Reflexive thematic analysis will be used to code qualitative interview data and generate key themes associated with intervention adoption.

ETHICS AND DISSEMINATION

The study protocol (V.1.9) was granted ethical approval by the Health Research Authority, Health and Care Research Wales, and the London- Harrow Research Ethics Committee (ref. 21/LO/0054) on 19 May 2021. Trial results will be submitted for publication in peer-reviewed journals, presented at national and international stroke meetings and conferences and disseminated among stakeholder communities.

TRIAL REGISTRATION NUMBER

NCT04475692.

'Smart reminder': A feasibility pilot study on the effects of a wearable device treatment on the hemiplegic upper limb in persons with stroke

INTRODUCTION

Emerging literature suggests that wearable devices offer a promising option for self-directed home-based upper limb training for persons with stroke. However, little research is available to explore integrating smartphone applications with wearable devices to provide upper limb telerehabilitation to stroke survivors at home. This study examined the feasibility and potential therapeutic effects of a wearable device integrated with a smartphone-based telerehabilitation system to provide upper limb rehabilitation to stroke survivors at home.

METHODS

Twelve stroke survivors from community support groups participated in a treatment consisting of 4-week telerehabilitation using a wearable device and 4-week conventional therapy successively in a single-blind, randomised crossover study. A 3-week washout period was administered between the two 4-week treatments. The primary outcome measures were the Fugl Meyer Assessment, the Action Research Arm Test, and the active range of motion (ROM) of the upper limb. Secondary outcome measures included the Motor Activity Log and exercise adherence.

RESULTS

Results showed that the active ROM of participants' hemiplegic shoulder improved more significantly after 4 weeks of telerehabilitation with the wearable device than with conventional therapy. No significant differences were found in other outcome measures.

CONCLUSIONS

A 4-week telerehabilitation programme using a wearable device improves the hemiplegic upper limb in community-dwelling stroke survivors and may be feasible as an effective intervention for self-directed upper limb rehabilitation at home.

Wearable devices for gait and posture monitoring via telemedicine in people with movement disorders and multiple sclerosis: a systematic review

INTRODUCTION

Wearable devices and telemedicine are increasingly used to track health-related parameters across patient populations. Since gait and postural control deficits contribute to mobility deficits in persons with movement disorders and multiple sclerosis, we thought it interesting to evaluate devices in telemedicine for gait and posture monitoring in such patients.

METHODS

For this systematic review, we searched the electronic databases MEDLINE (PubMed), SCOPUS, Cochrane Library, and SPORTDiscus. Of the 452 records retrieved, 12 met the inclusion/exclusion criteria. Data about (1) study characteristics and clinical aspects, (2) technical, and (3) telemonitoring and teleconsulting were retrieved, The studies were quality assessed.

RESULTS

All studies involved patients with Parkinson's disease; most used triaxial accelerometers for general assessment (n = 4), assessment of motor fluctuation (n = 3), falls (n = 2), and turning (n = 3). Sensor placement and count varied widely across studies. Nine used lab-validated algorithms for data analysis. Only one discussed synchronous patient feedback and asynchronous teleconsultation.

CONCLUSIONS

Wearable devices enable real-world patient monitoring and suggest biomarkers for symptoms and behaviors related to underlying gait disorders. thus enriching clinical assessment and personalized treatment plans. As digital healthcare evolves, further research is needed to enhance device accuracy, assess user acceptability, and integrate these tools into telemedicine infrastructure.

PROSPERO REGISTRATION

CRD42022355460.

Upper limb assessment with inertial measurement units according to the international classification of functioning in stroke: a systematic review and correlation meta-analysis

OBJECTIVE

To investigate the usefulness of inertial measurement units (IMUs) in the assessment of motor function of the upper limb (UL) in accordance with the international classification of functioning (ICF).

DATA SOURCES

PubMed; Scopus; Embase; WoS and PEDro databases were searched from inception to 1 February 2022.

METHODS

The current systematic review follows PRISMA recommendations. Articles including IMU assessment of UL in stroke individuals have been included and divided into four ICF categories (b710, b735, b760, d445). We used correlation meta-analysis to pool the Fisher Z-score of each correlation between kinematics and clinical assessment.

RESULTS

A total of 35 articles, involving 475 patients, met the inclusion criteria. In the included studies, IMUs have been employed to assess the mobility of joint functions (n = 6), muscle tone functions (n = 4), control of voluntary movement functions (n = 15), and hand and arm use (n = 15). A significant correlation was found in overall meta-analysis based on 10 studies, involving 213 subjects: (r = 0.69) (95% CI: 0.69/0.98; p < 0.001) as in the d445 (r = 0.71) and b760 (r = 0.64) ICF domains, with no heterogeneity across the studies.

CONCLUSION

The literature supports the integration of IMUs and conventional clinical assessment in functional evaluation of the UL after a stroke. The use of a limited number of wearable sensors can provide additional kinematic features of UL in all investigated ICF domains, especially in the ADL tasks when a strong correlation with clinical evaluation was found.

Do digital health interventions hold promise for stroke prevention and care in Black and Latinx populations in the United States? A scoping review

BACKGROUND

Black and Latinx populations are disproportionately affected by stroke and are likely to experience gaps in health care. Within fragmented care systems, remote digital solutions hold promise in reversing this pattern. However, there is a digital divide that follows historical disparities in health. Without deliberate attempts to address this digital divide, rapid advances in digital health will only perpetuate systemic biases. This study aimed to characterize the range of digital health interventions for stroke care, summarize their efficacy, and examine the inclusion of Black and Latinx populations in the evidence base.

METHODS

We searched PubMed, the Web of Science, and EMBASE for publications between 2015 and 2021. Inclusion criteria include peer-reviewed systematic reviews or meta-analyses of experimental studies focusing on the impact of digital health interventions on stroke risk factors and outcomes in adults. Detailed information was extracted on intervention modality and functionality, clinical/behavioral outcome, study location, sample demographics, and intervention results.

RESULTS

Thirty-eight systematic reviews met inclusion criteria and yielded 519 individual studies. We identified six functional categories and eight digital health modalities. Case management (63%) and health monitoring (50%) were the most common intervention functionalities. Mobile apps and web-based interventions were the two most commonly studied modalities. Evidence of efficacy was strongest for web-based, text-messaging, and phone-based approaches. Although mobile applications have been widely studied, the evidence on efficacy is mixed. Blood pressure and medication adherence were the most commonly studied outcomes. However, evidence on the efficacy of the various intervention modalities on these outcomes was variable. Among all individual studies, only 38.0% were conducted in the United States (n = 197). Of these U.S. studies, 54.8% adequately reported racial or ethnic group distribution. On average, samples were 27.0% Black, 17.1% Latinx, and 63.4% White.

CONCLUSION

While evidence of the efficacy of selected digital health interventions, particularly those designed to improve blood pressure management and medication adherence, show promise, evidence of how these interventions can be generalized to historically underrepresented groups is insufficient. Including these underrepresented populations in both digital health experimental and feasibility studies is critical to advancing digital health science and achieving health equity.

B-Spline Modeling of Inertial Measurements for Evaluating Stroke Rehabilitation Effectiveness

Patients who experience upper-limb paralysis after stroke require continual rehabilitation. Rehabilitation must be evaluated for appropriate treatment adjustment; such evaluation can be performed using inertial measurement units (IMUs) instead of standard scales or subjective evaluations. However, IMUs produce large quantities of discretized data, and using these data directly is challenging. In this study, B-splines were used to estimate IMU trajectory data for objective evaluations of hand function and stability by using machine learning classifiers and mathematical indices. IMU trajectory data from a 2018 study on upper-limb rehabilitation were used to validate the proposed method. Features extracted from B -spline trajectories could be used to classify individuals in the 2018 study with high accuracy, and the proposed indices revealed differences between these groups. Compared with conventional rehabilitation evaluation methods, the proposed method is more objective and effective.

Clinical applications of smart wearable sensors

Smart wearable sensors are electronic devices worn on the body that collect, process, and transmit various physiological data. Compared to traditional devices, their advantages in terms of portability and comfort have made them increasingly important in the medical field. This review takes a unique clinical physician's standpoint, diverging from conventional sensor-type-based classifications, and provides a comprehensive overview of the diverse clinical applications of wearable sensors in recent years. In this review, we categorize these applications according to different diseases, encompassing skin diseases and injuries, cardiovascular diseases, abnormal human motion, as well as endocrine and metabolic disorders. Additionally, we discuss the challenges and perspectives hindering the development of sensors for clinical use, emphasizing the critical need for interdisciplinary collaboration between medical and engineering professionals. Overall, this review would serve as an important reference for the future direction of sensor devices in clinical use.

A Sensor-Based Feedback Device Stimulating Daily Life Upper Extremity Activity in Stroke Patients: A Feasibility Study

This study aims to evaluate the feasibility and explore the efficacy of the Arm Activity Tracker (AAT). The AAT is a device based on wrist-worn accelerometers that provides visual and tactile feedback to stimulate daily life upper extremity (UE) activity in stroke patients.

METHODS

A randomised, crossover within-subject study was conducted in sub-acute stroke patients admitted to a rehabilitation centre. Feasibility encompassed (1) adherence: the dropout rate and the number of participants with insufficient AAT data collection; (2) acceptance: the technology acceptance model (range: 7-112) and (3) usability: the system usability scale (range: 0-100). A two-way ANOVA was used to estimate the difference between the baseline, intervention and control conditions for (1) paretic UE activity and (2) UE activity ratio.

RESULTS

Seventeen stroke patients were included. A 29% dropout rate was observed, and two participants had insufficient data collection. Participants who adhered to the study reported good acceptance (median (IQR): 94 (77-111)) and usability (median (IQR): 77.5 (75-78.5)-). We found small to medium effect sizes favouring the intervention condition for paretic UE activity (η²G = 0.07, p = 0.04) and ratio (η²G = 0.11, p = 0.22).

CONCLUSION

Participants who adhered to the study showed good acceptance and usability of the AAT and increased paretic UE activity. Dropouts should be further evaluated, and a sufficiently powered trial should be performed to analyse efficacy.

Overview of the role of robots in upper limb disabilities rehabilitation: a scoping review

BACKGROUND

Neuromotor rehabilitation and improvement of upper limb functions are necessary to improve the life quality of patients who have experienced injuries or have pathological outcomes. Modern approaches, such as robotic-assisted rehabilitation can help to improve rehabilitation processes and thus improve upper limb functions. Therefore, the aim of this study was to investigate the role of robots in upper limb disability improvement and rehabilitation.

METHODS

This scoping review was conducted by search in PubMed, Web of Science, Scopus, and IEEE (January 2012- February 2022). Articles related to upper limb rehabilitation robots were selected. The methodological quality of all the included studies will be appraised using the Mixed Methods Appraisal Tool (MMAT). We used an 18-field data extraction form to extract data from articles and extracted the information such as study year, country, type of study, purpose, illness or accident leading to disability, level of disability, assistive technologies, number of participants in the study, sex, age, rehabilitated part of the upper limb using a robot, duration and frequency of treatment, methods of performing rehabilitation exercises, type of evaluation, number of participants in the evaluation process, duration of intervention, study outcomes, and study conclusions. The selection of articles and data extraction was made by three authors based on inclusion and exclusion criteria. Disagreements were resolved through consultation with the fifth author. Inclusion criteria were articles involving upper limb rehabilitation robots, articles about upper limb disability caused by any illness or injury, and articles published in English. Also, articles involving other than upper limb rehabilitation robots, robots related to rehabilitation of diseases other than upper limb, systematic reviews, reviews, and meta-analyses, books, book chapters, letters to the editor, and conference papers were also excluded. Descriptive statistics methods (frequency and percentage) were used to analyses the data.

RESULTS

We finally included 55 relevant articles. Most of the studies were done in Italy (33.82%). Most robots were used to rehabilitate stroke patients (80%). About 60.52% of the studies used games and virtual reality rehabilitate the upper limb disabilities using robots. Among the 14 types of applied evaluation methods, "evaluation and measurement of upper limb function and dexterity" was the most applied evaluation method. "Improvement in musculoskeletal functions", "no adverse effect on patients", and "Safe and reliable treatment" were the most cited outcomes, respectively.

CONCLUSIONS

Our findings show that robots can improve musculoskeletal functions (musculoskeletal strength, sensation, perception, vibration, muscle coordination, less spasticity, flexibility, and range of motion) and empower people by providing a variety of rehabilitation capabilities.

Clinical Features to Predict the Use of a sEMG Wearable Device (REMO®) for Hand Motor Training of Stroke Patients: A Cross-Sectional Cohort Study

After stroke, upper limb motor impairment is one of the most common consequences that compromises the level of the autonomy of patients. In a neurorehabilitation setting, the implementation of wearable sensors provides new possibilities for enhancing hand motor recovery. In our study, we tested an innovative wearable (REMO^®) that detected the residual surface-electromyography of forearm muscles to control a rehabilitative PC interface. The aim of this study was to define the clinical features of stroke survivors able to perform ten, five, or no hand movements for rehabilitation training. 117 stroke patients were tested: 65% of patients were able to control ten movements, 19% of patients could control nine to one movement, and 16% could control no movements. Results indicated that mild upper limb motor impairment (Fugl-Meyer Upper Extremity ≥ 18 points) predicted the control of ten movements and no flexor carpi muscle spasticity predicted the control of five movements. Finally, severe impairment of upper limb motor function (Fugl-Meyer Upper Extremity > 10 points) combined with no pain and no restrictions of upper limb joints predicted the control of at least one movement. In conclusion, the residual motor function, pain and joints restriction, and spasticity at the upper limb are the most important clinical features to use for a wearable REMO^® for hand rehabilitation training.

Design of Spiral-Cable Forearm Exoskeleton to Assist Supination for Hemiparetic Stroke Subjects

We present the development of a cable-based passive forearm exoskeleton that is designed to assist supination for hemiparetic stroke survivors. Our device uniquely provides torque sufficient for counteracting spasticity within a below-elbow apparatus. The mechanism consists of a spiral single-tendon routing embedded in a rigid forearm brace and terminated at the hand and upper-forearm. A spool with an internal releasable-ratchet mechanism allows the user to manually retract the tendon and rotate the hand to counteract involuntary pronation synergies due to stroke. We characterize the mechanism with benchtop testing and five healthy subjects, and perform a preliminary assessment of the exoskeleton with a single chronic stroke subject having minimal supination ability. The mechanism can be integrated into an existing active hand-opening orthosis to enable supination support during grasping tasks, and also allows for a future actuated supination strategy.

The Application of Technological Intervention for Stroke Rehabilitation in Southeast Asia: A Scoping Review With Stakeholders' Consultation

Background

The technological intervention is considered as an adjunct to the conventional therapies applied in the rehabilitation session. In most high-income countries, technology has been widely used in assisting stroke survivors to undergo their treatments. However, technology use is still lacking in Southeast Asia, especially in middle- and low-income countries. This scoping review identifies and summarizes the technologies and related gaps available in Southeast Asia pertaining to stroke rehabilitation.

Methods

The JBI manual for evidence synthesis was used to conduct a scoping study. Until September 2021, an electronic search was performed using four databases (Medline, CINAHL, Scopus, ASEAN Citation Index). Only the studies that were carried out in Southeast Asia were chosen.

Results

Forty-one articles were chosen in the final review from 6,873 articles found during the initial search. Most of the studies reported the implementation of technological intervention combined with conventional therapies in stroke rehabilitation. Advanced and simple technologies were found such as robotics, virtual reality, telerehabilitation, motion capture, assistive devices, and mobility training from Singapore, Thailand, Malaysia, and Indonesia. The majority of the studies show that technological interventions can enhance the recovery period of stroke survivors. The consultation session suggested that the technological interventions should facilitate the needs of the survivors, caregivers, and practitioners during the rehabilitation.

Conclusions

The integration of technology into conventional therapies has shown a positive outcome and show significant improvement during stroke recovery. Future studies are recommended to investigate the potential of home-based technological intervention and lower extremities.

Upper-Limb Motion Recognition Based on Hybrid Feature Selection: Algorithm Development and Validation

Background

For rehabilitation training systems, it is essential to automatically record and recognize exercises, especially when more than one type of exercise is performed without a predefined sequence. Most motion recognition methods are based on feature engineering and machine learning algorithms. Time-domain and frequency-domain features are extracted from original time series data collected by sensor nodes. For high-dimensional data, feature selection plays an important role in improving the performance of motion recognition. Existing feature selection methods can be categorized into filter and wrapper methods. Wrapper methods usually achieve better performance than filter methods; however, in most cases, they are computationally intensive, and the feature subset obtained is usually optimized only for the specific learning algorithm.

Objective

This study aimed to provide a feature selection method for motion recognition of upper-limb exercises and improve the recognition performance.

Methods

Motion data from 5 types of upper-limb exercises performed by 21 participants were collected by a customized inertial measurement unit (IMU) node. A total of 60 time-domain and frequency-domain features were extracted from the original sensor data. A hybrid feature selection method by combining filter and wrapper methods (FESCOM) was proposed to eliminate irrelevant features for motion recognition of upper-limb exercises. In the filter stage, candidate features were first selected from the original feature set according to the significance for motion recognition. In the wrapper stage, k-nearest neighbors (kNN), Naïve Bayes (NB), and random forest (RF) were evaluated as the wrapping components to further refine the features from the candidate feature set. The performance of the proposed FESCOM method was verified using experiments on motion recognition of upper-limb exercises and compared with the traditional wrapper method.

Results

Using kNN, NB, and RF as the wrapping components, the classification error rates of the proposed FESCOM method were 1.7%, 8.9%, and 7.4%, respectively, and the feature selection time in each iteration was 13 seconds, 71 seconds, and 541 seconds, respectively.

Conclusions

The experimental results demonstrated that, in the case of 5 motion types performed by 21 healthy participants, the proposed FESCOM method using kNN and NB as the wrapping components achieved better recognition performance than the traditional wrapper method. The FESCOM method dramatically reduces the search time in the feature selection process. The results also demonstrated that the optimal number of features depends on the classifier. This approach serves to improve feature selection and classification algorithm selection for upper-limb motion recognition based on wearable sensor data, which can be extended to motion recognition of more motion types and participants.

Quantification of the relative arm use in patients with hemiparesis using inertial measurement units

Introduction

Accelerometry-based activity counting for measuring arm use is prone to overestimation due to non-functional movements. In this paper, we used an inertial measurement unit (IMU)-based gross movement (GM) score to quantify arm use.

Methods

In this two-part study, we first characterized the GM by comparing it to annotated video recordings of 5 hemiparetic patients and 10 control subjects performing a set of activities. In the second part, we tracked the arm use of 5 patients and 5 controls using two wrist-worn IMUs for 7 and 3 days, respectively. The IMU data was used to develop quantitative measures (total and relative arm use) and a visualization method for arm use.

Results

From the characterization study, we found that GM detects functional activities with 50–60% accuracy and eliminates non-functional activities with >90% accuracy. Continuous monitoring of arm use showed that the arm use was biased towards the dominant limb and less paretic limb for controls and patients, respectively.

Conclusions

The gross movement score has good specificity but low sensitivity in identifying functional activity. The at-home study showed that it is feasible to use two IMU-watches to monitor relative arm use and provided design considerations for improving the assessment method.

Clinical trial registry number: CTRI/2018/09/015648

Exploring the Use of Mobile and Wearable Technology among University Student Athletes in Lebanon: A Cross-Sectional Study

The markets of commercial wearables and health and fitness apps are constantly growing globally, especially among young adults and athletes, to track physical activity, energy expenditure and health. Despite their wide availability, evidence on use comes predominantly from the United States or Global North, with none targeting college student-athletes in low- and middle-income countries. This study was aimed to explore the use of these technologies among student-athletes at the American University of Beirut (AUB). We conducted a cross-sectional survey of 482 participants (average age 20 years) enrolled in 24 teams during Fall 2018; 230 students successfully completed the web-based survey, and 200 provided valid data. Fifty-three (26.5%) have owned a fitness tracker, mostly for self-monitoring. The most popular were Fitbit, Apple Watch, and Garmin. Similarly, 82 students (40%) used apps, primarily MyFitnessPal, Apple Health, and Samsung Health. Nevertheless, many participants discontinued use due to loss of interest or technical issues (breaking, usability, obsolescence, or lack of engagement). Wearable devices were considered superior to mobile phones alone as physical activity monitors. However, forming regular habits made self-monitoring via technology irrelevant. Further research is needed to better understand what motivates continuous use among student-athletes, who could use trackers to improve athletic performance and overall health.

Utilization of wearable technology to assess gait and mobility post-stroke: a systematic review

Background

Extremity weakness, fatigue, and postural instability often contribute to mobility deficits in persons after stroke. Wearable technologies are increasingly being utilized to track many health-related parameters across different patient populations. The purpose of this systematic review was to identify how wearable technologies have been used over the past decade to assess gait and mobility in persons with stroke.

Methods

We performed a systematic search of Ovid MEDLINE, CINAHL, and Cochrane databases using select keywords. We identified a total of 354 articles, and 13 met inclusion/exclusion criteria. Included studies were quality assessed and data extracted included participant demographics, type of wearable technology utilized, gait parameters assessed, and reliability and validity metrics.

Results

The majority of studies were performed in either hospital-based or inpatient settings. Accelerometers, activity monitors, and pressure sensors were the most commonly used wearable technologies to assess gait and mobility post-stroke. Among these devices, spatiotemporal parameters of gait that were most widely assessed were gait speed and cadence, and the most common mobility measures included step count and duration of activity. Only 4 studies reported on wearable technology validity and reliability metrics, with mixed results.

Conclusion

The use of various wearable technologies has enabled researchers and clinicians to monitor patients’ activity in a multitude of settings post-stroke. Using data from wearables may provide clinicians with insights into their patients’ lived-experiences and enrich their evaluations and plans of care. However, more studies are needed to examine the impact of stroke on community mobility and to improve the accuracy of these devices for gait and mobility assessments amongst persons with altered gait post-stroke.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12984-021-00863-x.

Wearables in der Schlaganfallmedizin

Unter Wearables versteht man in die Kleidung oder in tragbare Geräte integrierte Sensoren, die eine kontinuierliche Langzeitmessung von physiologischen Parametern, wie Herzfrequenz, Blutdruck, Atmung, Bewegung, Hautwiderstand usw. und/oder Bewegungsmustern ermöglichen. In der Schlaganfallmedizin eröffnen Wearables neue Optionen in der Diagnostik, Prävention und Rehabilitation.

Application of the National Institute for Health and Care Excellence Evidence Standards Framework for Digital Health Technologies in Assessing Mobile-Delivered Technologies for the Self-Management of Type 2 Diabetes Mellitus: Scoping Review

BACKGROUND

There is a growing role of digital health technologies (DHTs) in the management of chronic health conditions, specifically type 2 diabetes. It is increasingly important that health technologies meet the evidence standards for health care settings. In 2019, the National Institute for Health and Care Excellence (NICE) published the NICE Evidence Standards Framework for DHTs. This provides guidance for evaluating the effectiveness and economic value of DHTs in health care settings in the United Kingdom.

OBJECTIVE

The aim of this study is to assess whether scientific articles on DHTs for the self-management of type 2 diabetes mellitus report the evidence suggested for implementation in clinical practice, as described in the NICE Evidence Standards Framework for DHTs.

METHODS

We performed a scoping review of published articles and searched 5 databases to identify systematic reviews and primary studies of mobile device-delivered DHTs that provide self-management support for adults with type 2 diabetes mellitus. The evidence reported within articles was assessed against standards described in the NICE framework.

RESULTS

The database search yielded 715 systematic reviews, of which, 45 were relevant and together included 59 eligible primary studies. Within these, there were 39 unique technologies. Using the NICE framework, 13 technologies met best practice standards, 3 met minimum standards only, and 23 technologies did not meet minimum standards.

CONCLUSIONS

On the assessment of peer-reviewed publications, over half of the identified DHTs did not appear to meet the minimum evidence standards recommended by the NICE framework. The most common reasons for studies of DHTs not meeting these evidence standards included the absence of a comparator group, no previous justification of sample size, no measurable improvement in condition-related outcomes, and a lack of statistical data analysis. This report provides information that will enable researchers and digital health developers to address these limitations when designing, delivering, and reporting digital health technology research in the future.

Estimating Movement Smoothness From Inertial Measurement Units

Inertial measurement units (IMUs) are increasingly used to estimate movement quality and quantity to the infer the nature of motor behavior. The current literature contains several attempts to estimate movement smoothness using data from IMUs, many of which assume that the translational and rotational kinematics measured by IMUs can be directly used with the smoothness measures spectral arc length (SPARC) and log dimensionless jerk (LDLJ-V). However, there has been no investigation of the validity of these approaches. In this paper, we systematically evaluate the use of these measures on the kinematics measured by IMUs. We show that: (a) SPARC and LDLJ-V are valid measures of smoothness only when used with velocity; (b) SPARC and LDLJ-V applied on translational velocity reconstructed from IMU is highly error prone due to drift caused by integration of reconstruction errors; (c) SPARC can be applied directly on rotational velocities measured by a gyroscope, but LDLJ-V can be error prone. For discrete translational movements, we propose a modified version of the LDLJ-V measure, which can be applied to acceleration data (LDLJ-A). We evaluate the performance of these measures using simulated and experimental data. We demonstrate that the accuracy of LDLJ-A depends on the time profile of IMU orientation reconstruction error. Finally, we provide recommendations for how to appropriately apply these measures in practice under different scenarios, and highlight various factors to be aware of when performing smoothness analysis using IMU data.

Determining Factors that Influence Adoption of New Post-Stroke Sensorimotor Rehabilitation Devices in the USA

Rehabilitation device efficacy alone does not lead to clinical practice adoption. Previous literature identifies drivers for device adoption by therapists but does not identify the best settings to introduce devices, the roles of different stakeholders including rehabilitation directors, or specific criteria to be met during device development. The objective of this work was to provide insights into these areas to increase clinical adoption of post-stroke restorative rehabilitation devices. We interviewed 107 persons including physical/occupational therapists, rehabilitation directors, and stroke survivors and performed content analysis. Unique to this work, care settings in which therapy goals are best aligned for restorative devices were found to be outpatient rehabilitation, followed by inpatient rehabilitation. Therapists are the major influencers for adoption because they typically introduce new rehabilitation devices to patients for both clinic and home use. We also learned therapists' utilization rate of a rehabilitation device influences a rehabilitation director's decision to acquire the device for facility use. Main drivers for each stakeholder are identified, along with specific criteria to add details to findings from previous literature. In addition, drivers for home adoption of rehabilitation devices by patients are identified. Rehabilitation device development should consider the best settings to first introduce the device, roles of each stakeholder, and drivers that influence each stakeholder, to accelerate successful adoption of the developed device.

An exploratory qualitative study of health professional perspectives on clinical outcomes in UK orthotic practice

Background

Despite potential savings to the National Health Service, the collection of data on outcomes of NHS orthotic services is patchy. Indeed, several reports into orthotic services in the UK have reported a lack of data relating to outcomes of care and highlighted the need to routinely measure outcomes to demonstrate efficacy of services. Whilst a previous study provided an overview of the use of outcome measures in orthotic practice and identified some barriers to their use, further questions emerged. Hence, this qualitative study aimed to explore orthotists’ opinions and personal experiences on the influences on outcomes, how appropriate and relevant outcomes can be measured and also how barriers to the use of outcome measures can be overcome.

Methods

Following a review of the literature, an initial advisory group informed semi-structured questions. These were used to create dialogue in a focus group of 12 orthotists. Data from the focus group was transcribed verbatim and analysed using thematic analysis, creating themes and subthemes for discussion.

Results

The setting of realistic and agreed goals through managing expectations, compromise and patient education/information were seen as factors that could inform and improve outcomes. Barriers to the collection of outcome measures were associated with inadequate technology to manage the data, lack of time to complete them, lack of training in them and difficulties selecting appropriate outcome measures for patients with complex problems managed by different health professionals. The participants discussed ways of addressing these barriers, such as the use of ‘snapshots’ and delegation of data collection.

Conclusions

This study has revealed that measuring outcomes is considered to be an important activity. In order to achieve good outcomes, it is important to address patient expectations, discuss and establish joint goals for care at the outset and inform and include patients in the decision-making process. The identified barriers to measuring outcomes can be overcome with the solutions revealed by these participants. Hence, this study has contributed to current knowledge which has relevance for clinical practice and may provide the theoretical basis for future research.