Changes of Permutation Pattern Entropy and Ordinal Pattern Entropy During Three Emotion States: Natural, Happiness and Sadness

Abstract

Analysis of heart rate variability (HRV) holds an important potential in emotion recognition, especially when the non-linear entropy methods are involved. Permutation pattern entropy (PPEn) and ordinal pattern entropy (OPEn) are two important Shannon entropy approaches for analyzing the inherent dynamic characteristics of RR interval time series and their performances should be tested in the emotion study. In this study, ECG signals were recorded from 60 healthy subjects by RM6240B multi-channel signal acquirement system under three emotion states: natural, happiness and sadness, at a sample rate of 1000 Hz. For each emotion state, ECG signal was recorded for five minutes. QRS complexes were identified and then the RR interval time series were analyzed by the PPEn and OPEn methods. Compared with natural emotion (1.6834±0.06), PPEn increases significantly in both happiness (1.7205±0.05) and sadness (1.7065±0.05) emotions. Meanwhile, PPEn shows significant difference between happiness and sadness emotions. For OPEn, compared with natural emotion (1.8318±0.07), it also increases in both happiness (1.8545±0.07) and sadness (1.8505±0.07) emotions. However, there is no significant difference between happiness and sadness emotions. The changes of PPEn and OPEn values during the three different emotion states suggests that emotion has a non-negligible influence on the inherent dynamic characteristics in cardiovascular system, and the PPEn and OPEn methods can be used in the emotion recognition study.