A Bed-Exit and Bedside Fall Warning System Based on Deep Learning Edge Computing Techniques

被引：0

作者：

Chang, Wan-Jung ^{[1
]}

Chen, Liang-Bi ^{[2
]}

Ou, Yang-Kun ^{[3
]}

See, Aaron Raymond ^{[1
]}

Yang, Tzu-Chin ^{[1
]}

机构：

[1] Southern Taiwan Univ Sci & Technol, Dept Elect Engn, Tainan, Taiwan

[2] Natl Penghu Univ Sci & Technol, Dept Comp Sci & Informat Engn, Magong, Penghu, Taiwan

[3] Southern Taiwan Univ Sci & Technol, Dept Creat Prod Design, Tainan, Taiwan

来源：

2021 IEEE 3RD GLOBAL CONFERENCE ON LIFE SCIENCES AND TECHNOLOGIES (IEEE LIFETECH 2021) | 2021年

关键词：

Artificial intelligence over the Internet of Things (AIoT); deep learning; edge computing; fall detection; fall warning;

D O I：

10.1109/LIFETECH52111.2021.9391874

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

According to the hospital's old adult wards' clinical needs, we propose a deep learning edge computing-based two-stage early bed-exit warning and bedside fall notification system for aged patients with a high risk of falls. The proposed system can effectively help the hospital reduce bed fall incidence and increase bed-exit and bedside fall notification rates. As a result, the rate of injury from falling bed-exit can be reduced.

引用

页码：142 / 143

页数：2

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