Enabling glucose adaptive self-healing hydrogel based triboelectric biosensor for tracking a human perspiration

Abstract

A breakthrough in intelligent healthcare enables the collection of real-time patient data and active diagnosis via the advancement of medical technology. Monitoring glucose levels steady is essential to minimize diabetes-related issues since glucose is used by cells as an essential source of energy. Despite the range of commercially available glucose monitoring devices, the pain of repetitive blood testing and complex power demands has addressed the shortcomings of painless compact glucose biosensors. To address these drawbacks, self-healing glucose adaptive hydrogel based triboelectric biosensors (GAH-TES) are proposed as a biocompatible noninvasive technique for simultaneous glucose monitoring. With the assistance of a -cyclodextrin inclusion complex, glucose-adaptive PVA hydrogels may be utilized as an immobilization matrix for the glucose oxidase enzyme. The modulation of dynamic hydrogel networks in the presence of diversified glucose environments leads in changes in conductivity that boost electrical performance. Introducing glucose-adaptive hydrogel into a triboelectric nanogenerator (TENG) allows for efficient energy conversion from motion-based glucose stimuli in human sweat to electrical output. Higher glucose concentrations were shown to boost TENG production due to the greater conductivity and polarization effect caused by the increased ionic strength carried by the enzymatic activity. Due to its ability to detect high glucose levels autonomously, GAH-TES has broadened the scope of diabetes management by highly selective, flexible, and reliable real-time monitoring of human perspiration.