Material-Structure Codesign in Triboelectric Sensors: A Body-Region-Specific Roadmap for Human Motion Monitoring and Healthcare

Human motion recognition holds significant value in clinical rehabilitation, human-machine interaction (HMI), and sports science. Self-powered triboelectric sensors (TESs) based on triboelectric effect and electrostatic induction offer promising solutions for applications such as precision medicine, sign language translation, and robotics. However, challenges such as signal stability, complex motion decoupling, and long-term durability remain. This Perspective systematically explores these challenges by focusing on the critical role of material design and structural innovation in enhancing TESs performance. First, we analyze the core triboelectric sensing mechanism and compare traditional polymers with novel high-performance materials that overcome limitations in dielectric properties, mechanical strength, and environmental stability. We then explore structural innovations such as biomimetic design, multimodal integration, and textile integration to enhance sensitivity, comfort, and large-area deployment. In addition, we systematically analyzed the motion recognition mechanisms of the lower limbs, upper limbs, trunk, and head/neck from the perspective of physiological partitioning and summarized the progress of TESs in various application scenarios. Finally, we identify existing technical challenges and general strategies and envision future developments through the integration of artificial intelligence to achieve real-time, precise biomechanical feedback and auxiliary diagnosis of diseases, aiming to provide a technical roadmap for self-powered sensing systems and promote their implementation in smart healthcare and immersive interaction applications.