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Purpose: eHealth-based exercise therapies were developed to increase stroke patients' adherence to home-based motor rehabilitation. However, these eHealth tools face a rapid decrease in use after a couple of weeks. This study investigates stroke patients' motivation for home-based upper extremity rehabilitation with eHealth tools and their relation with Basic Psychological Needs., Materials and Methods: This is a qualitative study using thematic analysis. We conducted semi-structured interviews with stroke patients with upper extremity motor impairments, who were discharged home from a rehabilitation centre, after they interacted with a novel eHealth coach demonstrator in their homes for five consecutive days., Results: We included ten stroke patients. Thematic analysis resulted in eight themes for home-based rehabilitation motivation: Curiosity, Rationale, Choice, Optimal challenge, Reference, Encouragement, Social Support and Trustworthiness. Those themes are embedded into three Basic Psychological Needs: "Autonomy", "Competence", and "Relatedness"., Conclusion: Eight motivational themes related to the three Basic Psychological Needs describe stroke patients' motivation for home-based upper extremity rehabilitation. We recommend considering those themes when developing a home-based eHealth intervention for stroke patients to increase the alignment of eHealth tools to the patient's needs and reduce motivational decreases in home-based rehabilitation.

Purpose: Telerehabilitation systems have the potential to enable therapists to monitor and assist stroke patients in achieving high-intensity upper extremity exercise in the home environment. We adopted an iterative user-centred approach, including multiple data sources and meetings with end-users and stakeholders to define the user requirements for home-based upper extremity rehabilitation using wearable motion sensors for subacute stroke patients., Methods: We performed a requirement analysis consisting of the following steps: 1) context & groundwork; 2) eliciting requirements; 3) modelling & analysis; 4) agreeing requirements. During these steps, a pragmatic literature search, interviews and focus groups with stroke patients, physiotherapists and occupational therapists were performed. The results were systematically analysed and prioritised into "must-haves", "should-haves", and "could-haves"., Results: We formulated 33 functional requirements: eighteen must-have requirements related to blended care (2), exercise principles (7), exercise delivery (3), exercise evaluation (4), and usability (2); ten should-haves; and five could-haves. Six movement components, including twelve exercises and five combination exercises, are required. For each exercise, appropriate exercise measures were defined., Conclusion: This study provides an overview of functional requirements, required exercises, and required exercise measures for home-based upper extremity rehabilitation using wearable motion sensors for stroke patients, which can be used to develop home-based upper extremity rehabilitation interventions. Moreover, the comprehensive and systematic requirement analysis used in this study can be applied by other researchers and developers when extracting requirements for designing a system or intervention in a medical context.

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 (η 2 G = 0.07, p = 0.04) and ratio (η 2 G = 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.

Objective: To externally validate recent prognostic models that predict independent gait following stroke., Study Design and Setting: A systematic search identified recent models (<10 years) that predicted independent gait in adult stroke patients, using easily obtainable predictors. Predictors from the original models were assigned proxies when required, and model performance was evaluated in the validation cohort (n = 957). Models were updated to determine if performance could be improved., Results: Three prognostic models met our criteria, all with high Risk of Bias. Validation data was only available for the Australian model. This model used National Institute of Health Stroke Scale (NIHSS) and age to predict independent gait, using Motor Assessment Scale (MAS) walking item. For validation, Scandinavian Stroke Scale (SSS) was a proxy for NIHSS, and Functional Independence Measure (FIM) locomotion item was a proxy for MAS. The Area Under the Curve was 0.77 (0.74-0.80) and had good calibration in the validation dataset. Adjustment of the intercept and regression coefficients slightly improved discrimination. By adding paretic leg strength, the model further improved (AUC 0.82)., Conclusion: External validation of the Australian model with proxies showed fair discrimination and good calibration. Updating the model by adding paretic leg strength further improved model performance., (Copyright © 2021. Published by Elsevier Inc.)