PAS-Net is a fully multiplier-free spiking neural network that enforces human joint constraints spatially and uses causal neuromodulation temporally to achieve state-of-the-art accuracy on IMU HAR with up to 98% lower dynamic energy via early-exit.
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TCNet modulates handcrafted feature anchors with neural context from raw signals to achieve higher mF1 scores on five HAR benchmarks than prior methods like rTsfNet.