ArticleGames for health journal2023
Usage of RePlay as a Take-Home System to Support High-Repetition Motor Rehabilitation After Neurological Injury.
Article in Games for health journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 7 citations in OpenAlex.
- Trial
- Trial
- Vagus nerve stimulation for chronic pain management: Mechanisms and clinical advances.Journal of biological methods · 2025Review
- Characterization of an Algorithm for Autonomous, Closed-Loop Neuromodulation During Motor Rehabilitation.Neurorehabilitation and neural repair · 2024Article
- NeurostimML: a machine learning model for predicting neurostimulation-induced tissue damage.Journal of neural engineering · 2024Article
- NeurostimML: A machine learning model for predicting neurostimulation-induced tissue damage.bioRxiv : the preprint server for biology · 2023Article
- How to fail with paired VNS therapy.Brain stimulationReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Stroke is a leading cause of chronic motor disability. While physical rehabilitation can promote functional recovery, several barriers prevent patients from receiving optimal rehabilitative care. Easy access to at-home rehabilitative tools could increase patients' ability to participate in rehabilitative exercises, which may lead to improved outcomes. Toward achieving this goal, we developed RePlay: a novel system that facilitates unsupervised rehabilitative exercises at home. RePlay leverages available consumer technology to provide a simple tool that allows users to perform common rehabilitative exercises in a gameplay environment. RePlay collects quantitative time series force and movement data from handheld devices, which provide therapists the ability to quantify gains and individualize rehabilitative regimens. RePlay was developed in C# using Visual Studio. In this feasibility study, we assessed whether participants with neurological injury are capable of using the RePlay system in both a supervised in-office setting and an unsupervised at-home setting, and we assessed their adherence to the unsupervised at-home rehabilitation assignment. All participants were assigned a set of 18 games and exercises to play each day. Participants produced on average 698 ± 36 discrete movements during the initial 1 hour in-office visit. A subset of participants who used the system at home produced 1593 ± 197 discrete movements per day. Participants demonstrated a high degree of engagement while using the system at home, typically completing nearly double the number of assigned exercises per day. These findings indicate that the open-source RePlay system may be a feasible tool to facilitate access to rehabilitative exercises and potentially improve overall patient outcomes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.