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<p>Accurate detection of arterial pulse waves is crucial for wearable warning systems but faces challenges under non-close contact or pre-stress. Here, an interfacial engineered triboelectric sensor (IETS) has been proposed to improve the detection accuracy of pulse waves. It consists of a stress-transferring sensor-skin interface with piezo-frustums array and a gradient triboelectric interface with mountain-like microstructures. The mountain-like microstructures provide stress concentration points even under a pre-stress of 10 kPa with capturing all details of the pulse waves. Additionally, the incorporation of piezo-frustums array at the sensor-skin interface not only facilitates stress transfer but also generates piezoelectric charges. Such mechano-electric coupling effect endows IETS with a high sensitivity of 4.28 V/kPa. Integrated with machine learning, a wearable system based on IETS allows for drivers’ health and fatigue assessment via pulse wave analysis, offering an effective approach to prevent road accidents caused by sudden cardiovascular diseases and fatigue driving.</p>

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Optimized stress transfer interfaces enabled wearable nano-electronics for fatigue driving monitoring

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月15日

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  • Hao Lei,
  • Lingjie Xie,
  • Xuan Qin,
  • Guoxuan Sun,
  • Peihao Huang,
  • Weinuo Wang,
  • Bohan Lu,
  • Jiawei Yan,
  • Yuxi Wang,
  • Yina Liu,
  • Eng Gee Lim,
  • Xin Tu,
  • Chun Zhao,
  • Xuhui Sun,
  • Zhen Wen

摘要

Accurate detection of arterial pulse waves is crucial for wearable warning systems but faces challenges under non-close contact or pre-stress. Here, an interfacial engineered triboelectric sensor (IETS) has been proposed to improve the detection accuracy of pulse waves. It consists of a stress-transferring sensor-skin interface with piezo-frustums array and a gradient triboelectric interface with mountain-like microstructures. The mountain-like microstructures provide stress concentration points even under a pre-stress of 10 kPa with capturing all details of the pulse waves. Additionally, the incorporation of piezo-frustums array at the sensor-skin interface not only facilitates stress transfer but also generates piezoelectric charges. Such mechano-electric coupling effect endows IETS with a high sensitivity of 4.28 V/kPa. Integrated with machine learning, a wearable system based on IETS allows for drivers’ health and fatigue assessment via pulse wave analysis, offering an effective approach to prevent road accidents caused by sudden cardiovascular diseases and fatigue driving.