Decoupled approaches for multimodal flexible sensor systems

Abstract

Over the past decade, global industrial and research interest in flexible sensors has boosted their applications in diverse fields across intelligent medicines, human-machine interactions, soft robotics and Metaverse. Among them, multimodal flexible sensor systems play a critical role due to their capability to simultaneously detect multiple stimuli. This review presents an overview of recent advances in decoupled multimodal flexible sensor systems exploring spatial decoupling, temporal decoupling, signal processing, and other methods. Several categories of the systems are highlighted based on anti-interference structure, combinations of multiple mechanisms, surface functional modification, interlayer additional electrical properties and layer-specific differentiated outputs. Furthermore, the significant roles of machine learning and circuit strategies in decoupling mixed stimuli are illustrated. The burgeoning innovations in this research field should benefit the intelligent transformation of society, particularly amid rapid rise of artificial intelligence and automation.