Validating mm-Wave Radar System for Fall Detection and Recovery in Washrooms

Falls are a leading cause of death among individuals over 65, making timely detection crucial for preventing fatalities and improving recovery. Washrooms, despite being high-risk areas for falls, are underrepresented in fall detection research. This study aims to validate a non-contact fall-detection system capable of continuous and reliable monitoring in cluttered washroom environments, including scenarios involving common walking aids. The system uses Single Input Multiple Output Frequency-Modulated Continuous Wave (SIMO FMCW) radar to detect falls from both sitting and standing positions. Four participants simulated falls and fall recoveries in various scenarios, such as sitting on a toilet or wheelchair, standing with a walker, and standing freely. The system's ability to differentiate between falls and recoveries was also tested, as recovered falls are significant for fall history and injury risk. The radar system demonstrated an average fall detection accuracy of 100 % and a recovery detection accuracy of 92.5%. The findings support the use of SIMO FMCW radar as an effective, non-contact emergency alert system for washroom falls. This affordable and convenient system offers a life-saving solution for fall monitoring in personal spaces, ensuring safety while respecting privacy. Clinical Relevance-Our non-contact, autonomous fall detection system demonstrates 100 accuracy in detecting falls within washrooms and 92.5 % accuracy in detecting fall recoveries.

Authors

Publication Details

Published
2024-09-19
DOI
https://doi.org/10.1109/hi-poct64255.2024.10876204
Primary Topic
Postharvest Quality and Shelf Life Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Validating mm-Wave Radar System for Fall Detection and Recovery in Washrooms

Jun Ho Bae, Joshua Visser, George Shaker, Hajar Abedi et al.
Postharvest Quality and Shelf Life Management
article

Validating mm-Wave Radar System for Fall Detection and Recovery in Washrooms

Jun Ho Bae, Joshua Visser, George Shaker, Hajar Abedi, Senior Member, J Hall
article en

Abstract

Falls are a leading cause of death among individuals over 65, making timely detection crucial for preventing fatalities and improving recovery. Washrooms, despite being high-risk areas for falls, are underrepresented in fall detection research. This study aims to validate a non-contact fall-detection system capable of continuous and reliable monitoring in cluttered washroom environments, including scenarios involving common walking aids. The system uses Single Input Multiple Output Frequency-Modulated Continuous Wave (SIMO FMCW) radar to detect falls from both sitting and standing positions. Four participants simulated falls and fall recoveries in various scenarios, such as sitting on a toilet or wheelchair, standing with a walker, and standing freely. The system's ability to differentiate between falls and recoveries was also tested, as recovered falls are significant for fall history and injury risk. The radar system demonstrated an average fall detection accuracy of 100 % and a recovery detection accuracy of 92.5%. The findings support the use of SIMO FMCW radar as an effective, non-contact emergency alert system for washroom falls. This affordable and convenient system offers a life-saving solution for fall monitoring in personal spaces, ensuring safety while respecting privacy. Clinical Relevance-Our non-contact, autonomous fall detection system demonstrates 100 accuracy in detecting falls within washrooms and 92.5 % accuracy in detecting fall recoveries.

Openalex Percentile: Top 85%
Postharvest Quality and Shelf Life Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Validating mm-Wave Radar System for Fall Detection and Recovery in Washrooms — Jun Ho Bae, Joshua Visser, et al. · (2024) | TGRS Research Map | TGRS