Scoping review of AI-driven wearable technologies for rehabilitation and functional assessment in Parkinson's disease: a protocol

人工智能驱动的可穿戴技术在帕金森病康复和功能评估中的应用范围界定综述:一项方案

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Abstract

BACKGROUND: Parkinson's disease (PD) is a common neurodegenerative disorder characterised by high prevalence and disability rates, severely impairing patients' quality of life and imposing a substantial societal burden. Rehabilitation interventions are an essential component of PD management; however, conventional face-to-face rehabilitation is constrained by limited resources and poor adherence. In recent years, the integration of artificial intelligence (AI) with wearable technologies has offered new avenues for rehabilitation, enabling continuous monitoring, objective assessment and personalised feedback. Although relevant studies have emerged, most are limited by small sample sizes, short-term designs and a lack of comprehensive synthesis. This study aims to conduct a scoping review to summarise the current applications of AI-driven wearable technologies in PD rehabilitation and functional assessment, and to identify existing research gaps. METHODS AND ANALYSIS: This review will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines and employ the Joanna Briggs Institute three-step search strategy. After an initial pilot search, a comprehensive search strategy will be developed to systematically search 10 databases (CNKI, Wanfang Data Knowledge Service Platform, SinoMed, the Cochrane Library, PubMed, Web of Science, CINAHL, Scopus, Embase and the IEEE Xplore Digital Library). One researcher will independently perform data extraction, and another will independently verify the extracted data. Eligible studies will include original research articles, dissertations and conference papers published after 2020, involving PD patients and using AI-driven wearable devices for rehabilitation or functional assessment. Data will be synthesised narratively and presented using tables and figures. ETHICS AND DISSEMINATION: This study involves only publicly available published data and therefore does not require ethical approval. Findings will be disseminated through peer-reviewed journal publications and presentations at academic conferences.

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