Global trends in wearable sensors for stroke motor rehabilitation: A bibliometric analysis

Background: Stroke is a leading cause of long-term disability, and wearable technologies have emerged as promising tools in motor rehabilitation. This study presents a bibliometric and visual analysis of global research on wearable devices for stroke motor recovery, aiming to map knowledge structures, identify research hotspots, and reveal emerging trends. Methods: A total of 564 English-language publications from 2005 to June 2025 were retrieved from the Web of Science Core Collection, with trend and burst analyses conducted through 2024. Using CiteSpace, VOSviewer, RStudio, and OriginPro, we analyzed publication trends, country and institutional contributions, author collaboration, co-citation networks, keyword co-occurrence, clustering, and burst terms. Results: Over the past two decades, the number of publications has increased steadily, with the United States and China being the most productive. Core themes include gait analysis, upper-limb recovery, and sensor-based monitoring, while recent bursts highlight the growing exploration of data-driven and AI-assisted approaches to personalized rehabilitation. Conclusion: This study provides a comprehensive overview of research development in this domain and offers insight for future interdisciplinary and data-driven rehabilitation innovations.