The interfacial engineered triboelectric sensor achieved a high sensitivity of 4.28 V/kPa and enabled driver fatigue recognition with 94% average accuracy using a 1D-CNN model.
The developed IETS provides highly sensitive pulse wave monitoring even under pre-stress, offering a potential wearable solution for cardiovascular health and fatigue monitoring.
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.
Lei et al. (Sun,) conducted a other in Driver fatigue (n=5). Interfacial engineered triboelectric sensor (IETS) vs. Traditional sensors without microstructures was evaluated on Fatigue recognition accuracy. The interfacial engineered triboelectric sensor achieved a high sensitivity of 4.28 V/kPa and enabled driver fatigue recognition with 94% average accuracy using a 1D-CNN model.