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A Deep Learning-Enabled Skin-Inspired Pressure Sensor for Complicated Recognition Tasks with Ultralong Life

机译:支持深度学习的仿肤压力传感器用于复杂的识别任务具有超长寿命

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摘要

Flexible full-textile pressure sensor is able to integrate with clothing directly, which has drawn extensive attention from scholars recently. But the realization of flexible full-textile pressure sensor with high sensitivity, wide detection range, and long working life remains challenge. Complex recognition tasks necessitate intricate sensor arrays that require extensive data processing and are susceptible to damage. The human skin is capable of interpreting tactile signals, such as sliding, by encoding pressure changes and performing complex perceptual tasks. Inspired by the skin, we have developed a simple dip-and-dry approach to fabricate a full-textile pressure sensor with signal transmission layers, protective layers, and sensing layers. The sensor achieves high sensitivity (2.16 kPa−1), ultrawide detection range (0 to 155.485 kPa), impressive mechanical stability of 1 million loading/unloading cycles without fatigue, and low material cost. The signal transmission layers that collect local signals enable real-world complicated task recognition through one single sensor. We developed an artificial Internet of Things system utilizing a single sensor, which successfully achieved high accuracy in 4 tasks, including handwriting digit recognition and human activity recognition. The results demonstrate that skin-inspired full-textile sensor paves a promising route toward the development of electronic textiles with important potential in real-world applications, including human–machine interaction and human activity detection.
机译:柔性全纺织压力传感器能够直接与服装集成,近年来引起了学者的广泛关注。但是,实现具有高灵敏度、宽检测范围和长工作寿命的柔性全纺织压力传感器仍然具有挑战性。复杂的识别任务需要复杂的传感器阵列,这些阵列需要大量的数据处理并且容易受到损坏。人类皮肤能够通过编码压力变化和执行复杂的感知任务来解释触觉信号,例如滑动。受皮肤的启发,我们开发了一种简单的浸干法来制造具有信号传输层、保护层和传感层的全织物压力传感器。该传感器具有高灵敏度 (2.16 kPa−1)、超宽检测范围(0 至 155.485 kPa)、令人印象深刻的 100 万次加载/卸载循环无疲劳的机械稳定性以及低材料成本。收集本地信号的信号传输层可通过单个传感器实现现实世界的复杂任务识别。我们开发了一个利用单个传感器的人工物联网系统,成功地在笔迹数字识别和人类活动识别等 4 项任务中实现了高精度。结果表明,受皮肤启发的全纺织品传感器为电子纺织品的发展铺平了一条充满希望的道路,在实际应用中具有重要潜力,包括人机交互和人体活动检测。

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