[1]许 君,温宇航,李宜潼,等.基于柔性传感器的呼吸监测智能服装[J].服装学报,2024,9(05):464-470.
　XU Jun,WEN Yuhang,LI Yitong,et al.Smart Clothing for Respiratory Monitoring Based on Flexible Sensor[J].Journal of Clothing Research,2024,9(05):464-470.
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基于柔性传感器的呼吸监测智能服装()
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《服装学报》[ISSN:2096-1928/CN:32-1864/TS]

卷:
第9卷
期数:
2024年05期
页码:
464-470
栏目:
柔性传感器专题
出版日期:
2024-11-01

文章信息/Info

Title:
Smart Clothing for Respiratory Monitoring Based on Flexible Sensor
作者:
许 君1; 2;  温宇航1;  李宜潼1;  何天虹1;  张 诚2
1.天津工业大学 纺织科学与工程学院,天津 300387; 2.天津工业大学 电子信息与工程学院,天津 300387
Author(s):
XU Jun1; 2;  WEN Yuhang1;  LI Yitong1;  HE Tianhong1;  ZHANG Cheng2
1. School of Textile Science and Engineering, Tiangong University, Tianjin 300387, China; 2.School of Electronics and Information Engineering, Tiangong University,Tianjin 300387, China
分类号:
TP 212; TS 941.73
文献标志码:
A
摘要:
为了不影响智能服装正常监测,同时达到服装可清洗目的,对现有智能呼吸监测服装进行分析,设计一种可拆卸佩戴式呼吸监测带T恤。通过围度差测试,确定最适宜呼吸监测的人体部位,设计可拆卸智能监测服装呼吸监测带; 同时采用无缝缝合工艺缝制服装,提升服装的舒适性; 对呼吸监测智能服装的呼吸波形与呼吸频率进行评估测试,并与两种商用传感器进行对比验证。结果表明,该智能服装与商用传感器监测结果的一致性超过了0.85,呼吸频率的监测准确度高达80%,满足了商用呼吸监测的标准,能够实现人们日常呼吸状态的高精准实时监测。
Abstract:
To avoid influencing the normal monitoring of smart clothing and to achieve the purpose of making the clothing washable, an analysis was carried out on the existing smart respiratory monitoring clothing, and a detachable and wearable respiratory monitoring belt T-shirt was designed. Through the girth difference test, the most suitable body part for respiratory monitoring was determined, and the detachable intelligent respiratory monitoring belt was designed for the clothing. Meanwhile, the seamless sewing process was employed to stitch the clothing, enhancing its comfort. The respiratory waveform and respiratory frequency of the intelligent respiratory monitoring clothing were evaluated and tested, and compared and verified with two commercial sensors. The results indicate that the consistency of the monitoring results between this smart clothing and the commercial sensors exceeded 0.85, and the monitoring accuracy of respiratory frequency was as high as 80%, meeting the commercial respiratory monitoring standards and enabling highly accurate real-time monitoring of people’s daily respiratory status.

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(责任编辑:张 雪)

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更新日期/Last Update: 2024-10-30