A General Strategy for Rapidly Optimizing Wearable Resistive Pressure Sensors

Due to the complicated relationship between wearable electronics performance and various parameters, months even years are needed to obtain a desired sensor by random and time-consuming trial-and-error methods. Herein, a general analytic model based on the micro-element division and equivalent circuit is presented to guide a rapid optimizing strategy for wearable resistive pressure sensors, which is like the method always used in the traditional design of the metal-oxide-semiconductor field-effect transistor for integrated circuits. The quantitative relationship between the sensitivity and related parameters is declared in the presented model, and the optimized parameters are achieved to design a sensor. The demanded ultra-highly sensitive pressure sensor is successfully designed and optimized in minutes based on the built model, and the fabricated sensor is applied in a voice real-time recognition system to obtain 100% recognition accuracy. The on-demand and agile development strategy paves a promising way to greatly accelerate the transition from random and time-consuming to the controllable design of wearable electronics.