Radar Based Real-Time Fall Detection System with Low Power Consumption

被引:6
作者
Lu, Jincheng [1 ]
Ou, Zixuan [1 ]
Liu, Ziyu [1 ]
Han, Cheng [1 ]
Ye, Wenbin [1 ]
机构
[1] Shenzhen Univ, Microscale Optoelect Informat & Elect Engn, Shenzhen, Peoples R China
来源
18TH INTERNATIONAL SOC DESIGN CONFERENCE 2021 (ISOCC 2021) | 2021年
关键词
fall detection; radar; real-time; deep learning;
D O I
10.1109/ISOCC53507.2021.9613989
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Fall detection plays a critical role in the elder people home caring. In this work, we propose a low-power fall detection system based on Doppler radar sensor. To lower the power consumption which is of great importance in practical applications, the system is designed to be multistage including event detection, fall-like event detection and fall detection parts. By adopting the proposed multi-stage system, the most power consumption part, deep neural network operation, will not be activated in most cases. The experiment results show that the proposed model can not only achieve high accuracy of fall detection, but also have great potential for deployment in a low power mode.
引用
收藏
页码:266 / 267
页数:2
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