Self-Powered Wearable Displacement Sensor for Continuous Respiratory Monitoring and Human-Machine Synchronous Control

被引:0
|
作者
Shi, Yan [1 ]
Li, Heran [1 ,2 ]
Yang, Liman [1 ]
Wang, Yixuan [1 ]
Sun, Zhibo [3 ]
Zhang, Chi [2 ,4 ]
Fu, Xianpeng [2 ,4 ]
Niu, Yanxia [3 ]
Han, Chengwei [1 ]
Xie, Fei [5 ]
机构
[1] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China
[2] Chinese Acad Sci, CAS Ctr Excellence Nanosci, Beijing Inst Nanoenergy & Nanosyst, Beijing Key Lab Micronano Energy & Sensor, Beijing 101400, Peoples R China
[3] Beihang Univ, Engn Training Ctr, Beijing 102206, Peoples R China
[4] Univ Chinese Acad Sci, Sch Nanosci & Technol, Beijing 100049, Peoples R China
[5] Chinese Peoples Liberat Army Gen Hosp, Coll Pulm & Crit Care Med, Beijing 100853, Peoples R China
来源
SMALL METHODS | 2024年
基金
中国国家自然科学基金;
关键词
pneumatic servo system; respiratory monitoring; self-powered; triboelectric nanogenerator; wearable electronics; DRIVEN TRIBOELECTRIC NANOGENERATOR; UNCERTAIN NONLINEAR-SYSTEMS;
D O I
10.1002/smtd.202401189
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Flexible wearable electronic devices play a vital role in daily monitoring, medical diagnosis, and human-computer interaction, and such devices have a great demand for portability, integration, comfort, and self-power. In this study, a triboelectric nanogenerator integrated into a flexible chest belt is proposed as a displacement sensor to monitor the displacement and frequency of thoracic expansion. Based on three parallel interpolation electrode structures with phase differences, the Triboelectric Nanogenerators's(TENG) output signal pulse number can characterize the sliding displacement, with a resolution of more than 1 mm and a durability of more than 700,000 cycles. Based on the flexible printed circuit processing technology, the volume of the sensor is less than 8.5 cm3, and the weight is less than 3.2 g, which improves the portability of the device. Based on wireless radio frequency technology, the collected signals are transmitted to the upper computer, and then the monitoring of respiratory physiological signals and the human-machine synchronous control of the ventilator are achieved within the overshoot of 1.5% and the control error of 5% through a simulation machine. This work provides a sensing method for daily and medical respiratory monitoring and demonstrates the enormous potential of frictional electric sensors in intelligent medical applications.
引用
收藏
页数:9
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