Chenshu WU, PhD | The University of Hong Kong;
Competition Sponsor: Research Grants Council of the Hong Kong Special Administrative Region, China
Award Year: 2024
With the growing global aging population, the issue of elderly fall detection has become increasingly critical. Statistically, there are approximately 70,000 fatal falls among older adults worldwide every year, and over 37,000,000 falls that require medical attention. Moreover, many elderly individuals live alone, leaving them potentially unable to seek help for extended periods after a fall. This pressing issue acutely calls for innovative solutions for practical elderly fall detection, which, however, has been a long-standing challenge. This project seeks to develop a practical solution for accurate and robust fall detection that is privacy-preserving, non-intrusive, and low-cost, allowing large-scale deployment for ubiquitous settings. We propose to explore and exploit a unique opportunity underpinned by emerging modalities for non-contact human sensing, e.g., Thermal Arrays and ToF sensors. The combination of these modalities offers a compelling balance between sensing resolution and privacy, rendering a promising solution to ubiquitous fall detection that is unexplored. The project will shed light on practical solutions to fall detection, improving healthy longevity for our aging society to age well.