Ultra‐Robust and Hyperelastic Triboelectric Webbing for Self‐Powered Rehabilitation Sensing with Invisible and Embedded Design

W Wei Wang Y Yulong Wang (State Key Laboratory of High Pressure and Superhard Materials, College of Physics) D Di Guo S Shidai Tian (Beijing Key Laboratory of High‐Entropy Energy Materials and Devices Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of Sciences Beijing P. R. China) S Shuhui Wang Q Qichang Hu (Fujian Key Laboratory of Agricultural Information Sensoring Technology, College of Mechanical and Electrical Engineering, Fujian Agriculture and Forestry University 1 , Fuzhou, Fujian 350002,) A Aifang Yu (Beijing Key Laboratory of High‐Entropy Energy Materials and Devices Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of Sciences Beijing P. R. China) Z Zhong Lin Wang (Center for High-Entropy Energy and Systems) J Junyi Zhai

Abstract

ABSTRACT 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.

Article Details

Volume / Issue Vol. 38, Issue 28
Published May 01, 2026
ISSN 0935-9648
Publisher Unknown Publisher

Journal Info

Advanced Materials

Unknown Publisher

ISSN: 0935-9648 Physical Sciences

Authors (9)

W

Wei Wang

Y

Yulong Wang

State Key Laboratory of High Pressure and Superhard Materials, College of Physics

D

Di Guo

S

Shidai Tian

Beijing Key Laboratory of High‐Entropy Energy Materials and Devices Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of Sciences Beijing P. R. China

S

Shuhui Wang

Q

Qichang Hu

Fujian Key Laboratory of Agricultural Information Sensoring Technology, College of Mechanical and Electrical Engineering, Fujian Agriculture and Forestry University 1 , Fuzhou, Fujian 350002,

A

Aifang Yu

Beijing Key Laboratory of High‐Entropy Energy Materials and Devices Beijing Institute of Nanoenergy and Nanosystems Chinese Academy of Sciences Beijing P. R. China

Z

Zhong Lin Wang

Center for High-Entropy Energy and Systems

J

Junyi Zhai