# Computer-assisted rehabilitation system in the use of motor function recovery: A protocol for scoping review

## TL;DR

This study outlines a plan to review how computer-assisted systems help recover motor function in neurological disorders like stroke and Parkinson's.

## Contribution

A structured scoping review protocol to map and synthesize the fragmented landscape of computer-assisted rehabilitation systems.

## Key findings

- The review will identify key research themes and knowledge gaps in CARS.
- Publication trends and geographic distributions will be visualized using PRISMA diagrams and heatmaps.
- Findings will guide future research and clinical implementation of CARS.

## Abstract

Motor dysfunction, a prevalent sequela of neurological disorders such as stroke, Parkinson’s disease, and cerebral palsy, profoundly compromises patients’ capacity to perform daily activities and participate in social interactions. To address this challenge, computer-assisted rehabilitation systems (CARS) have emerged as innovative tools for facilitating motor function recovery. However, the rapid proliferation of diverse CARS modalities—encompassing novel technical approaches, interdisciplinary integrations, and heterogeneous clinical applications—has resulted in a fragmented and poorly delineated research landscape. This scoping review protocol aims to systematically map the current evidence, clarify conceptual boundaries, identify key research themes, and highlight critical knowledge gaps within the CARS field.

Following PRISMA-ScR guidelines, a comprehensive search across English (PubMed, Embase, Web of Science) and Chinese (CNKI, Wanfang, VIP, SinoMed) databases (inception to May 2025) will retrieve peer-reviewed studies using controlled vocabulary (MeSH: Rehabilitation/methods) and keywords (“computer-assisted rehabilitation system*”). After deduplication (EndNote X9) and manual verification, two reviewers will independently screen titles/abstracts and full texts, resolving discrepancies via third-party arbitration. Data extraction will categorize studies into study characteristics (design, population), technical specifications (sensors, AI), and clinical contexts (outcome measures, motor domains). Quantitative synthesis will map publication trends, geographic distributions, and methodological profiles using PRISMA diagrams and heatmaps. Thematic analysis will identify dominant research clusters (e.g., robotics, VR) and interdisciplinary linkages. Results will be disseminated via interactive evidence maps and narrative summaries emphasizing clinical translation. Any protocol deviations will be explicitly documented to ensure methodological transparency.

This review will synthesize the heterogeneous CARS field into a structured framework, guiding future research prioritization and clinical implementation. By delineating technical innovations, clinical efficacy, and knowledge gaps, findings aim to optimize rehabilitation strategies for neurological populations.

Detail of this review project can be found in Open Science Framework:
https://doi.org/10.17605/OSF.IO/HXDT8.