Bibliometric Analysis-Research Trends in mHealth Applications, Wearable Sensors and Self-Monitoring Devices

This paper presents a comprehensive bibliometric analysis of the scholarly landscape pertaining to mHealth applications, wearable sensors, and self-monitoring devices, situated within the broader domain of intelligent health systems. Utilizing a robust dataset extracted from the Web of Science (WoS) and Scopus databases spanning last five years (2020–2025), this study systematically identifies and interprets key research trends, influential authors, prominent institutions, pivotal journals, and emerging thematic clusters. Through performance analysis (e.g., publication growth, citation patterns) and science mapping (e.g., co-authorship, co-citation, keyword co-occurrence networks), we reveal the intellectual structure, evolutionary trajectories, and critical areas of innovation. The findings offer valuable insights for researchers, practitioners, and policymakers navigating the rapidly advancing juncture of intelligent systems and health informatics, highlighting opportunities for future research and association in personalized digital health.