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Multi-Sensor Fusion for Fall Detection and Early Warning: Overcoming Camera Blind Spots

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成果类型:
会议论文
作者:
Yehong Zhao;Junwen Deng;Mingyue Zhang;Huan Liu;Mingtao Liu;...
作者机构:
[Yehong Zhao; Jinmei Li] College of Electrical and Information Engineering, Hunan Institute of Traffic Engineering, Hengyang, Hunan, China [email protected]
[Junwen Deng; Mingyue Zhang; Huan Liu; Mingtao Liu] School of Computing / Software, University of South China, Hengyang, Hunan, China [email protected]
语种:
英文
年:
2025
页码:
1288-1298
会议名称:
EITCE '24: Proceedings of the 2024 8th International Conference on Electronic Information Technology and Computer Engineering
会议论文集名称:
Electronic Information Technology and Computer Engineering
出版地:
New York, NY, United States
出版者:
Association for Computing Machinery
ISBN:
9798400710094
机构署名:
本校为其他机构
摘要:
The aging population has led to an increased need for reliable fall detection systems that can provide timely assistance to individuals who have fallen. This paper presents a multi-sensor fusion system designed to detect falls and issue early warnings, overcoming the limitations of camera-based systems, particularly in areas where camera surveillance is not feasible. We utilize a combination of an MPU6050 six-axis pose sensor and a MAX30102 heart rate and blood oxygen sensor to achieve high accuracy in fall detection. The system is designed to differentiate between falling and normal physical ...

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