Triboelectric Wearable Sensors for Human-Centric Smart Electronics: From Self-Powered Sensing to Artificial Intelligence-Assisted Human–Machine Interface Systems - Ra, Yoonsang; Cho, Sumin; Guo, Xinge; Choi, Dongwhi; Lee, Chengkuo (Nano-Micro Letters, 2026)
As intelligent electronics become increasingly integrated into daily life, health care, virtual interaction, and assistive systems, human–machine interfaces (HMIs) require sensing platforms that are not only wearable and self-powered but also capable of translating human signals into adaptive machine functions. Triboelectric wearable sensors are particularly attractive in this regard because they directly transduce human-generated mechanical stimuli, provide broad material and structural design freedom, and are readily adaptable to body-interfaced formats. In this review, wearability refers to body-mounted, skin-interfaced, textile-integrated, or otherwise human-attached triboelectric sensing platforms, whereas human-centric smart electronics refers to downstream electronic systems that remain functionally anchored to human-originated sensing, interpretation, feedback, or control. From this perspective, we review triboelectric wearable sensors from fundamentals to applications, covering working principles, material selection, device architectures, and fabrication strategies. We further discuss artificial intelligence-assisted signal processing, triboelectric artificial synapses, and neuromorphic computing as key bridges from self-powered sensing to intelligent HMI. Representative application spaces, including health care, gesture recognition, device control, immersive virtual interaction, wearable-to-robotic extensions, and intelligent transportation are discussed only when wearable triboelectric sensing serves as the primary human–input interface. Finally, the remaining challenges and future directions toward next-generation human-centric smart electronics are outlined. Highlights: 1 A wearable-centered review framework is presented for triboelectric sensors, covering self-powered sensing principles, material selection, device architectures, and fabrication strategies. 2 Artificial intelligence-assisted signal processing, triboelectric artificial synapses, and neuromorphic computing are identified as key bridges from self-powered sensing to adaptive human–machine interfaces. 3 Representative applications and future directions are organized toward human-centric smart electronics, including health care, gesture interaction, robotics, intelligent transportation, and next-generation embodied systems.