Biopolymer-Based Stimuli-Responsive and Self-Healing Conductive Hydrogels for Next-Generation Bioelectronics Interfaces

Bioelectronics is crucial for recording, analyzing, and controlling biological processes in the setting of rapid Industry 4.0 and Health 4.0 evolution, which has increased the need for soft, flexible, smart, and biocompatible platforms. The mechanical mismatch between traditional materials and soft biological tissues has resulted in several challenges when employed as biointerface materials due to their intrinsic rigidity. Hydrogels are an emerging material being researched due to their intrinsic softness, multistimuli response, and tunable characteristics, along with a biocompatible foundation. When these hydrogels are designed with self-healing and multiresponsive functionalities, they exhibit an excellent bioelectronics platform for an intelligent system. This review article focuses on the detailed mechanisms of self-healing, such as Schiff-based, Diels–Alder-based, and ionic interaction systems, and also discusses a design strategy of stimuli-responsive hydrogels, including temperature-responsive, electrical-responsive, and light-responsive systems in the field of biopolymer-based responsive hydrogels for advanced bioelectronics. Furthermore, the review focuses on both natural, such as chitosan, gelatin, and synthetic polymers, such as polyvinylpyrrolidone and polyethylene glycol, as well as in conjunction with conductive elements such as nanomaterials and ionic salts. Moreover, their potential applications in the field of E-skin, implanted devices, robotics, flexible electronics, health care, and biosignal detecting systems are highlighted. However, currently, these systems have several translational challenges, such as reproducibility, limited stimulus response, long-term biological stability, dehydration resistance, and scalable production. Another key challenge is combining multisensing and multiacting responsiveness in a single platform. Finally, this review recommends research directions for achieving intelligent bioelectronics systems from biopolymer-based stimuli and self-healing soft biomaterial.