The emerging multifunctional flexible electronic-skin for establishing body-electric interaction can enable real-time monitoring of personal health status as a new personalized medicine technique. A key difficulty in the device design is the flexible power supply. Here a self-powered wearable noninvasive electronic-skin for perspiration analysis has been realized on the basis of a piezo-biosensing unit matrix of enzyme/ZnO nanoarrays. The electronic-skin can detect lactate, glucose, uric acid, and urea in the perspiration, and no outside electrical power supply or battery is used in the biosensing process. The piezoelectric impulse of the piezo-biosensing units serves as the power supply and the data biosensor. The working mechanism can be ascribed to the piezoelectric-enzymatic-reaction coupling effect of enzyme/ZnO nanowires. The electronic-skin can real-time/continuously monitor the physiological state of a runner through analyzing the perspiration on his skin. This approach can promote the development of a new-type of body electric and self-powered biosensing electronic-skin.

Comparing to human vision, conventional machine vision composed of image sensor and processor suffers from high latency and large power consumption due to physically separated image sensing and processing. Neuromorphic vision system with brain-inspired visual perception provides a promising solution to solve the challenge. Here we propose and demonstrate a prototype neuromorphic vision system by networking retinomorphic sensor with a memristive crossbar. We fabricate the retinomorphic sensor by using WSe2/h-BN/Al2O3 van der Waals heterostructures with gate-tunable photoresponses, to closely mimic the human retinal capabilities in simultaneously sensing and processing images. We then network such sensor with a large-scale Pt/Ta/HfO2/Ta one-transistor-one-memristor (1T1R) memristive crossbar, which serves as the role similar to the visual cortex in human brain. The realized neuromorphic vision system allows for fast letter recognition and object tracking, indicating the capabilities of image sensing, processing and recognition in the full analog regime. Our work suggests that such neuromorphic vision system may open up unprecedented opportunities in future visual perception applications.

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