Abstract：According to the emotional states of calm and fear, some emotional information of the Electrocardiogram （ECG）data samples were collected, and researched in both emotional and emotionless states. By the analysis of scatter plots of QT-RR intervals, the 1/f distribution law of ECG signals spectrum and the poincare sections of Heart Rate Variability (HRV), the recognition rate of nonlinear characteristics with these two types of emotional states was calculated, and compared with the recognition rate of statistical characteristics. The results indicate that extracting nonlinear characteristics of ECG signals has a better recognition result compared with statistical characteristics when distinguishing emotional states and emotionless states.
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