Recent Advances in Machine Learning Assisted Hydrogel Flexible Sensing

Abstract

AbstractHydrogel flexible sensors are widely used in wearable devices, health care, intelligent robots and other fields due to their excellent flexibility, biocompatibility and high sensitivity. With the development of single sensor to multi‐channel and multi‐mode sensor network, the sensor data also presents the characteristics of multi‐dimension, complex and massive. Traditional data analysis methods can no longer meet the data analysis requirements of hydrogel flexible sensor networks. The introduction of machine learning (ML) technology optimizes the process of data analysis. With the continuous development of multi‐layer neural network technology and the improvement of computer performance, deep learning (DL) algorithm is increasingly used to achieve higher efficiency and accuracy, provides a powerful tool for data analysis of hydrogel flexible sensor, and accelerates the intelligent process of hydrogel flexible sensor equipment. This paper introduces the classification of hydrogel flexible sensors and the working mechanism and common algorithms of ML, and summarizes the application of ML technology to assist hydrogel flexible sensors in data analysis in the fields of health care and information recognition. This review will provide inspiration and reference for integrating ML technology into the field of hydrogel flexible sensors.