A hypersensitive neuromorphic airflow sensor inspired by vision-compensatory scorpion mechanoreceptors for respiratory pattern analysis

August 20, 2026| Source: PNAS

Efficient acquisition of spatial airflow information is vital for organisms to orient within complex environments and detect predators. For scorpions with degraded vision, specialized mechanosensory trichobothria provide a crucial vision-compensatory mechanism, enabling hypersensitive perception of subtle airflow fluctuations. Inspired by this evolutionary adaptation, we present a biomimetic neuromorphic airflow sensor (BNAS) integrating a bioinspired lever-amplification structure with a pressure-induced ionic enrichment mechanism. This synergistic design inherits the hypersensitive anemosensation and neural response features of scorpion. The BNAS demonstrates a superior sensitivity of 18.22% (m/s) −1 at low velocities and maintains high performance across a broad dynamic range (0.1 to 10.27 m/s), along with omnidirectional detection capability. The integration of this neuromorphic hardware with AlexNet deep-learning algorithm enables the efficient extraction of human respiratory patterns, achieving 95.56% accuracy in identifying individual “breathing fingerprints.” Our work underscores the potential of bioinspired neuromorphic systems to bridge the gap between biological perception and artificial sensing, establishing a neuromorphic front-end design paradigm that advances next-generation brain-inspired computing.

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