Large-Area Noise-Resilient Multiplexing Triboelectric Biomechanical Sensing on Clothing for High-Precision Full-Body Motion Capture in Wearables.

Full-body motion capture is vital for next-generation wearables in virtual reality, the metaverse, and healthcare. However, current systems struggle to scale beyond localized sensing due to severe signal interference, power issues, and lack of scalable and stretchable sensing technology. Here, we develop a large-area noise-resilient multiplexed triboelectric sensing garment enabling active and high-precision full-body motion tracking. A multilayer architecture that applies shielding on both the sensing units and serpentine circuits largely suppresses signal misrecognition to 0.13%, attenuates electromagnetic noise by 57 dB, and raises threshold force to >1.5 N. Complementarily, the hybrid design of SnS2 nanoflowers (NFs)-doped silicone rubber composites and SnS2 NFs-decorated graphite-like carbonized textiles markedly boost charge generation, transport, and retention, achieving high-fidelity, noise-free motion sensing. Further integrated with on-body wireless processing and deep-learning analytics, the system enables reliable acquisition and accurate recognition of multi-site body motion simultaneously. It underpins immersive wearables, demonstrated in virtual gaming scenarios by precise upper-body gesture recognition, lower-limb action classification, and full-body interactive control.