能量收集
可穿戴计算机
波形
可穿戴技术
能量(信号处理)
计算机科学
功率(物理)
数码产品
能源消耗
持续监测
电子工程
人体运动
结构健康监测
功率消耗
运动传感器
运动检测
电气工程
柔性电子器件
信号(编程语言)
功率密度
测距
运动捕捉
电解质
电力电子
储能
机械能
声学
作者
Zhechen Zhang,Yuetong Tian,Shujia Wang,Zhida Gao,Yanyan Song,Li-Ping Mei,Junjian Zhao
标识
DOI:10.1021/acs.analchem.5c05546
摘要
Wearable electronics that enable multimodal sensing have the potential to revolutionize personalized health monitoring and human-machine interfaces. However, current sensors need to integrate several single-functional sensors to achieve multifunctional detection. Furthermore, the simultaneous generation, acquisition, and analysis of multimodal signals often result in high power consumption and may introduce electrical interference, thereby compromising the sensing accuracy. This study innovatively developed a self-powered mechanoluminescent (ML)-hydrovoltaic motion sensing patch for simultaneously monitoring human motion parameters and sweat electrolyte concentrations in one device without external energy input. Under various mechanical stimuli, parameters such as deformation frequency (0.33 Hz-1 Hz), intensity, direction, and sweat electrolyte levels can be directly inferred from the waveform and amplitude of the output voltage. Furthermore, secreted sweat serves as both a sensing medium and an energy source, driving continuous direct-current generation up to 0.584 V and 4.46 μA. A single sensing patch can achieve a maximum output power density of 7.9 mW/m2 and demonstrate excellent durability for over 300 usage cycles. Based on this unique design strategy, the sensing patch is programmed and utilized for information transport, demonstrating its potential in human-machine interaction. This multidimensional, self-powered patch offers a platform for integrated motion sensing, biochemical monitoring, and energy harvesting in next-generation wearables.
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