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Anxiety is a complex emotion characterized by an unpleasant feeling of tension when people anticipate a threat or negative consequence. It is regarded as a comprehensive reflection of human thought processes, physiological arousal, and external stimuli. The actual state of emotion can be represented objectively by human physiological signals. This study aims to analyze the differences of ECG (electrocardiogram) characteristics for various types of drivers under anxiety. We used several methods to induce drivers’ mood states (calm and anxiety) and then conducted the real and virtual driving experiments to collect driver’s ECG signal data. Physiological changes in ECG during the experiments were recorded using the PSYLAB software. The independent sample t-test analysis was conducted to determine if there are significant differences in ECG characteristics for different types of drivers in anxious state during driving. The results show that there are significant differences in ECG signal characteristics of drivers by gender, age, and driving experience, in time domain, frequency domain, and waveform under anxiety. Our findings of this study contribute to the development of more intelligent and personalized driver warning system, which could improve road traffic safety.

Analysis of Differences in ECG Characteristics for Different Types of Drivers under Anxiety