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.
Zhang et al. (Wed,) studied this question.