A Neuromorphic Multifunctional Sensing Fiber for Deep Learning Enhanced Wearable Human‐Machine Interaction

Le résumé fourni par la source

Abstract Next‐generation human‐machine interaction demands neuromorphic input pathways that can seamlessly encode human intent with spatial precision, flexibility, and artificial intelligence (AI) compatibility. Conventional tactile systems often rely on multi‐electrode matrices for localization, resulting in complex wiring, crosstalk, and limited textile integration. Here, a neuromorphic multifunctional sensing single‐fiber (MSSF) fabricated via melt‐extrusion 3D printing of a thermoplastic polyurethane/ionic liquid ionogel is presented that can achieve continuous touch position decoding with only terminal electrodes. A folded‐parallel configuration modulates the distributed electric field along the fiber, allowing contact‐induced capacitance variations to be mathematically mapped to location with millimeter‐level resolution. Moreover, MSSF additionally enables high‐sensitivity strain and temperature sensing. Coupled with deep neural networks, the system achieves 100% recognition accuracy in touch intent and gestures. MSSF forms an integrated perception‐transmission‐recognition‐feedback loop within a scalable, textile‐compatible architecture, offering a transformative platform for embodied, intelligent, and spatially aware human‐machine interfaces.

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