Advancement of AI-assisted self-powered healthcare sensing systems

Self-powered sensors, which derive energy from environmental or physiological sources, provide a sustainable approach to eliminating the reliance on external power supplies. They enable the autonomous operation of sensing systems, paving the way for the increasingly expanding Internet of things (IoTs). The integration of artificial intelligence (AI) into these systems for healthcare has significantly advanced their capabilities in processing complex signals, extracting meaningful features, and delivering high-precision health insights. This review explores the latest advancement in self-powered sensors, involving the various applications of piezoelectricity, triboelectricity, electromagnetism, thermoelectricity, photovoltaics, and biofuel cells in healthcare. The applications of AI methodologies in self-powered sensing systems are covered and reviewed, addressing challenges like noise reduction, data analysis, and multisignal fusion. Future directions emphasize leveraging material innovation, manufacturing technology, structural optimization, and further integration of AI technology, to achieve multifunctional, high-performance, and intelligentized healthcare sensing systems. These developments underscore the potential of AI-assisted self-powered sensors to revolutionize healthcare with sustainable, precise, and intelligent solutions.