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

IF 10.7 2区 材料科学 Q1 CHEMISTRY, PHYSICAL Small Methods Pub Date : 2024-11-26 DOI:10.1002/smtd.202401189
Yan Shi, Heran Li, Liman Yang, Yixuan Wang, Zhibo Sun, Chi Zhang, Xianpeng Fu, Yanxia Niu, Chengwei Han, Fei Xie
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Abstract

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.

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用于连续呼吸监测和人机同步控制的自供电可穿戴位移传感器
柔性可穿戴电子设备在日常监测、医疗诊断和人机交互中发挥着重要作用,这类设备对便携性、集成性、舒适性和自供电有很大的要求。本研究提出了一种集成在柔性胸带中的三电纳米发电机,作为位移传感器来监测胸廓扩张的位移和频率。基于三个具有相位差的平行插补电极结构,三电纳米发电机(TENG)的输出信号脉冲数可表征滑动位移,分辨率超过 1 毫米,耐用性超过 70 万次。基于柔性印刷电路处理技术,传感器体积小于 8.5 立方厘米,重量小于 3.2 克,提高了设备的便携性。基于无线射频技术,将采集到的信号传输到上位机,再通过仿真机实现呼吸生理信号的监测和呼吸机的人机同步控制,超调在1.5%以内,控制误差在5%以内。这项工作为日常和医疗呼吸监测提供了一种传感方法,展示了摩擦电传感器在智能医疗应用中的巨大潜力。
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来源期刊
Small Methods
Small Methods Materials Science-General Materials Science
CiteScore
17.40
自引率
1.60%
发文量
347
期刊介绍: Small Methods is a multidisciplinary journal that publishes groundbreaking research on methods relevant to nano- and microscale research. It welcomes contributions from the fields of materials science, biomedical science, chemistry, and physics, showcasing the latest advancements in experimental techniques. With a notable 2022 Impact Factor of 12.4 (Journal Citation Reports, Clarivate Analytics, 2023), Small Methods is recognized for its significant impact on the scientific community. The online ISSN for Small Methods is 2366-9608.
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