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Deep‐Learning‐Assisted Neck Motion Monitoring System Self‐Powered Through Biodegradable Triboelectric Sensors.

Authors :
Sun, Fengxin
Zhu, Yongsheng
Jia, Changjun
Wen, Yuzhang
Zhang, Yanhong
Chu, Liang
Zhao, Tianming
Liu, Bing
Mao, Yupeng
Source :
Advanced Functional Materials. 3/25/2024, Vol. 34 Issue 13, p1-9. 9p.
Publication Year :
2024

Abstract

In the new era of artificial intelligence (AI) and the Internet of Things (IoT), big data collection and analysis for intelligent sports are of great importance in monitoring human health. Herein, naturally, biodegradable triboelectric nanogenerators (NB‐TENGs) are developed based on low‐cost, recyclable, and environmentally friendly corn bracts, which are further applied in neck motion recognition. Three NB‐TENGs are integrated into an elastic collar to create a neck‐condition monitoring triboelectric sensor (NCM‐TS). An intelligent behavioral monitoring system is achieved by combining NCM‐TS with a deep learning model, which allows the recognition of four types of neck motion with an average accuracy of 94%. The developed neck motion monitoring sensor has broad potential applications in sports health monitoring, rehabilitation training, and healthcare. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1616301X
Volume :
34
Issue :
13
Database :
Academic Search Index
Journal :
Advanced Functional Materials
Publication Type :
Academic Journal
Accession number :
176294562
Full Text :
https://doi.org/10.1002/adfm.202310742