ECG-Based Real-Time Drivers’ Fatigue Detection Using a Novel Elastic Dry Electrode

In view of the complicated placement process of wet electrodes used for driving fatigue detection based on electrocardiogram (ECG) characteristics, this study proposed a novel elastic dry electrode for real-time acquisition of ECG signals from the palm of hand. This type of dry electrode eliminated the need for applying conductive paste when collecting the driver’s ECG. Meanwhile, it avoids the requirement of penetrating the cuticle layer of the skin surface to reduce impedance as well, thus minimizing the risk of skin infection. To alleviate driver fatigue resulting from prolonged driving, a periodic man–machine interaction mode (PMIM) was proposed. To assess the efficacy of PMIM in mitigating driver fatigue, this study compared and evaluated driver mental fatigue based on electroencephalogram (EEG) and heart rate variability (HRV) characteristics across two driving modes. The findings demonstrated that the novel elastic dry electrode effectively captured changes in driving fatigue characteristics by acquiring ECG signals from the palm of the hand. In addition, the proposed PMIM effectively mitigated driving fatigue resulting from prolonged periods of driving.