The evolution of flexible technology has progressed beyond traditional energy storage systems toward multifunctional platforms that unify energy harvesting, storage, and sensing within a single and flexible architecture. This transformation is propelled by advancements in nanomaterials, responsive substrates, and self-powered mechanisms that enable real-time biosensing and dynamic energy management. Notably, recent developments highlight the potential of extracting sensing signals directly from the intrinsic aberrations in energy storage behavior such as voltage or capacitance changes in response to mechanical strain, temperature, humidity, and light stimuli, eliminating the need for separate sensing units. However, most existing literature either focuses on the preservation of stable output under stress or isolates sensing to individual components, falling short of realizing a truly integrated system. Innovative device architectures that incorporate multifunctional materials, co-fabricated energy sensor elements, and low-power electronics are now being coupled with machine learning and artificial intelligence (AI) to interpret subtle performance shifts as meaningful environmental data. These intelligent systems promise to convert electrochemical fluctuations into actionable feedback while maintaining a power supply to onboard electronics. Despite ongoing challenges in material resilience, system integration, and scalable fabrication, emerging solutions such as AI-assisted response mapping, hybrid stimuli-responsive materials, and all-in-one designs are unlocking the path to self-sustaining and intelligent wearable platforms. This convergence of materials science, AI, and next-generation energy technologies marks a paradigm shift toward adaptive and predictive wearables for healthcare, fitness, and industrial applications.
Lee et al. (Thu,) studied this question.