Ionic Composite Nanofiber Membrane‐Based Ultra‐Sensitive and Anti‐Interference Flexible Pressure Sensors for Intelligent Sign Language Recognition

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Abstract
The escalating population affected by deafness and hearing loss demands solutions to revolutionize traditional sign language recognition based on interpreters. The emergence of wearable sensors could provide a promising alternative but suffer from poor mechanical stability, external signal inferences, less sensitivity, and signal hysteresis. Herein, an ultrasensitive and anti‐interference flexible ionic composite nanofiber membranes (ICNM) based pressure sensor is developed through precisely manipulating polymer‐blending interactions, where ionic liquid and silver nanowire additives are well anchored on thermoplastic polyurethane polymer scaffolds without leakage via unique hydrogen bond networks, leading to a substantial areal capacitance of 20 µF cm −2 , and effectively mitigating external noise. The ICNM‐based sensor showcases high sensitivity (57.2 kPa −1 ), ultralow detection limit (≈1.2 Pa), fast response time (15 ms), expansive detection range (1.2 Pa –220 kPa), and exceptional stability for over 10 000 continuous compression and recovery cycles, showing great promise for capturing subtle facial expressions, large joint movements, and high‐frequency (≈25.5 Hz) pressure sensing in a high accuracy and resolution. Together with advanced machine learning algorithms, an intelligent sign language recognition glove achieves 96.8% accuracy for 24 letters within 0.1 s, ushering in a new era for ultrasensitive pressure sensors and significantly contributing to next‐generation intelligent sign language recognition systems.
Funding Information
  • National University of Singapore
  • National Key Research and Development Program of China (2022YFB3205500)
  • National Natural Science Foundation of China (U23A20360)

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