Driven by the rapid evolution of flexible electronics, rehabilitation healthcare is shifting toward devices that seamlessly interface with human body. Yet, existing solutions often simply layer flexible sensor units over rigid components, making it difficult to combine high elasticity, mechanical robustness, and true imperceptibility. Here, we are pioneering a super-tough (∼54.7 MPa) and highly stretchable (>400% strain) triboelectric webbing (T-webbing) that overcomes this long-standing trade-off through the synergistic integration of an embedded textured architecture and functional elastic yarns. The T-webbing supports mass customization, exhibits outstanding electrical durability (>100 000 cycles), and enables reliable self-powered sensing capability with tunable mechanical properties for diverse rehabilitation tasks. In a proof-of-concept demonstration, the T-webbing is seamlessly integrated into a machine-learning-enabled lower-limb rehabilitation platform, achieving a motion recognition accuracy of 97.9% while enabling seamless one-click data sharing, intuitive human-machine interaction, and real-time remote guidance. By bridging high mechanical resilience with imperceptible wearability, our study offers a brand-new solution for data-driven, high-compliance, home-based rehabilitation within the Internet-of-Things ecosystem-addressing a pressing clinical need for scalable, patient-friendly solutions.
Wang et al. (Thu,) studied this question.