Challenges and opportunities in sensor-based fall prevention for older adults: a bibliometric review

Abstract

Purpose

This bibliometric review examines the recent literature on sensor-based fall prevention for older adults. It analyzes publication trends, key researchers and institutions, major research themes, as well as gaps and opportunities in this field.

Design/methodology/approach

A comprehensive search was conducted in Scopus and Web of Science (WoS) databases for publications from 1990 to 2024. Bibliometric indicators including publication output, citation analysis and co-occurrence of keywords were used to map the research landscape. Network visualizations were employed to identify key thematic clusters.

Findings

The research on sensor-based fall prevention has grown rapidly, peaking in 2019. The USA, Australia and Canada lead this work, with universities and hospitals collaborating globally. Key themes include fall epidemiology, wearable sensors and AI for fall detection. Opportunities exist to better implement these sensor systems through large trials, user-centered design, hybrid sensors and advanced analytics.

Research limitations/implications

While comprehensive, the analysis focused primarily on publications indexed in Scopus and WoS, which may not capture all relevant literature. Future studies could expand the search to include other databases and conduct deeper analyses of highly influential studies.

Practical implications

The review provides an evidence-informed roadmap to accelerate the translation of sensor innovations into scalable and sustainable fall prevention practices for vulnerable older adult populations.

Originality/value

This is the first comprehensive bibliometric analysis to map the research landscape of sensor-based fall prevention, identifying key trends, themes and opportunities to advance this critical domain addressing a major global public health challenge.

Citation

Azizan, A. (2024), "Challenges and opportunities in sensor-based fall prevention for older adults: a bibliometric review", Journal of Enabling Technologies, Vol. 18 No. 4, pp. 306-318. https://doi.org/10.1108/JET-02-2024-0011