A General Strategy for Rapidly Optimizing Wearable Resistive Pressure Sensors

Abstract

Abstract 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.

Keywords

• agile design
• analytic models
• optimized parameters
• wearable resistive pressure sensors