Programmable Auxetic Metamaterial‐Based E‐Skin for Conformable Dual‐Mechanism Spatiotemporal Sensing

ABSTRACT

While self‐powered flexible e‐skins based on nanogenerators hold immense promise for wearable electronics, severe interfacial mechanical mismatches occur under complex joint deformations, limiting reliable multichannel sensing. Herein, a 4D‐printed mechanical metamaterial‐enabled e‐skin with an auxetic scaffold and AI‐assisted decoding is developed to improve deformation accommodation and support multichannel sensing during joint motion. Benefiting from an auxetic architecture with a tunable negative Poisson's ratio (−0.41 to −1.76), the metamaterial skeleton expands laterally under stretch to mimic the strain‐stiffening behavior of biological tissues. By concentrating local stress, this geometrical programmability transforms the skeleton into an active mechanical amplifier, significantly boosting the triboelectric‐piezoelectric (TENG/PENG) responses. An integrated nine‐channel array captures these amplified spatiotemporal features with high fidelity. During fast running, the device yields robust 3 V outputs and resolves 3 Hz rhythmic motions. Further, by introducing a lightweight 1D convolutional neural network (1D‐CNN) to decouple intricate spatiotemporal crosstalk, the system achieves advanced motion‐state classification with an exceptional accuracy of over 95% on average across different tasks. This integration of mechanics and artificial intelligence offers a robust platform for next‐generation intelligent wearable rehabilitation and human‐machine interfaces.