Self-powered three-dimensional one-piece flexible pressure sensing system for human motion information aquisition

人体运动 运动(物理) 压力传感器 计算机科学 工程类 纳米技术 计算机视觉 声学 材料科学 机械工程 物理
作者
Lu Chen,Bao Shi,Wei Zhang,Xinying Liu,Ge Fang,Lixia Jia,Ruosi Yan
出处
期刊:Chemical Engineering Journal [Elsevier BV]
卷期号:488: 150891-150891 被引量:12
标识
DOI:10.1016/j.cej.2024.150891
摘要

Continuous monitoring of vital signals through electronic devices, independent of external power supply, is a crucial technology driving the development of wearable electronics as the next generation of medical devices. This study presents a self-powered flexible pressure sensing system, combining a one-piece, three-dimensional (3D) flexible fabric with Ti3C2Tx-MXene. The system integrated supercapacitors and pressure sensors, facilitating the monitoring of vital human activities and capturing motion data. The MXene/Zn flexible hybrid supercapacitors with a 3D one-piece fabric structure streamlined the assembly process and offered structural stability with superior rate performance. These supercapacitors exhibited an impressive 94.2 % capacitance retention and 97.1 % coulombic efficiency even after 10,000 charge–discharge cycles. With an energy density of 11.25 μWh/cm2 and a power density of 25 mW/cm2, they were well-suited as a reliable energy source to power pressure sensors. The 3D porous network structure improved the pressure strain sensitivity, and the MXene/SPN flexible pressure sensors, featuring a 3D one-piece fabric structure, exhibited fast response (60 ms), good sensitivity (0.11 kPa−1), and cycling stability (10,000 cycles). They efficiently recognized human joint movements, integrating two fabrics with the same structure into a sensing system with an energy device creates an implantable garment capable of measuring pressure generated by muscle movement during physical activity. The integration of this device holds promising applications in the field of medical monitoring, facilitating long-term non-invasive health assessments and enabling quantitative analysis of chronic diseases.
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