Wearable respiratory strain monitoring system based on textile-based capacitive strain sensor

Author:

Jun ZHONG,Chun-na LI,Wen-liang ZHU,Hong ZHOU,Yong-feng LIU,Xue-feng HAN

Abstract

Abstract Respiratory state analysis based on respiratory strain monitoring plays an increasingly important role in the assessment of the continuous dynamic physiological state of the human body. The proposed respiratory strain monitoring system uses the STM32F411 single-chip microcomputer as the main control chip, combined with the FDC2214 capacitor-to-digital converter, collects the capacitance value of the flexible cloth-based capacitive strain sensor through the IIC method, and sends the collected result to the upper computer for processing and analysis through Bluetooth. The device collects the respiratory strain signal of the chest in three motion states: stationary, walking, and running. Through data acquisition and algorithm processing, it can clearly display the waveform of respiratory strain, and the extraction accuracy of the respiratory rate is ±1rpm. The experimental results show that the system has good stability and accuracy, strong anti-interference ability, and can meet the requirements of continuous dynamic high-precision respiratory rate monitoring.

Publisher

IOP Publishing

Subject

General Physics and Astronomy

Reference12 articles.

1. Research on algorithm for extracting respiratory signal based on electrocardiographic signal [J];Lian;Chinese Medical Physics Journal,2019

2. Research on wearable breathing detection method based on chest impedance method [J];Guangda;Journal of Biomedical Engineering,2016

3. Vision-based automatic detection method of non-contact breathing frequency [J];Jinyue;Chinese Journal of Scientific Instrument,2019

4. Research status of respiratory frequency detection technology [J];Xu;Beijing Biomedical Engineering,2017

Cited by 15 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3