Biomimetic 3D Tactile Sensor System With Neuromorphic Encoding for Fascicle‐Level Feedback

Restoring tactile feedback that can be delivered through selective neural interfaces is essential for prosthetic embodiment. This study presents a biomimetic 3D tactile sensor system designed to convert skin‐like mechanical interactions into functionally selective neural stimulation patterns at the fascicle level. The system integrates a polydimethylsiloxane (PDMS)‐based artificial skin layer with tunable mechanical compliance, embedded slow‐adapting (SA) and fast‐adapting (FA) sensor channels, and a neuromorphic encoding framework that transforms analog sensor outputs into receptor‐potential‐like waveforms and action potential spike trains. MWCNT‐PDMS piezoresistive composites provide sustained pressure‐sensitive SA outputs, whereas BaTiO ₃ ‐PDMS triboelectric composites provide transient dynamic‐event‐sensitive FA outputs. The size, footprint, and embedding depth of the sensors were selected to generate distinct receptive‐field‐inspired response profiles within the 3D skin matrix. In vivo validation using rat sciatic nerve stimulation showed that encoded pressing and tapping patterns elicited distinguishable electromyographic (EMG) responses in the tibialis anterior (TA) and gastrocnemius (GC) muscles. These results support the feasibility of a functionally selective biomimetic tactile front‐end for future closed‐loop neuroprosthetic feedback, while further device‐level durability, frequency‐response characterization, and real‐time integration remain necessary for clinical translation.