Application of Permutation Entropy and Permutation Min-Entropy in Multiple Emotional States Analysis of RRI Time Series

This study’s aim was to apply permutation entropy (PE) and permutation min-entropy (PME) over an RR interval time series to quantify the changes in cardiac activity among multiple emotional states. Electrocardiogram (ECG) signals were recorded under six emotional states (neutral, happiness, sadness,...

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Bibliographic Details
Authors: Xia, Yirong, Yang, Licai, Zunino, Luciano José, Shi, Hongyu, Zhuang, Yuan, Liu, Chengyu
Format: article
Status:Published version
Publication Date:2018
Country:Argentina
Institution:Universidad Nacional de La Plata
Repository:SEDICI (UNLP)
Language:English
OAI Identifier:oai:sedici.unlp.edu.ar:10915/67692
Online Access:http://sedici.unlp.edu.ar/handle/10915/67692
Access Level:Open access
Keyword:Ingeniería
permutation entropy; permutation min-entropy; emotion recognition; heart rate variability; electrocardiogram (ECG)
Patrón de Electrocardiograma
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Summary:This study’s aim was to apply permutation entropy (PE) and permutation min-entropy (PME) over an RR interval time series to quantify the changes in cardiac activity among multiple emotional states. Electrocardiogram (ECG) signals were recorded under six emotional states (neutral, happiness, sadness, anger, fear, and disgust) in 60 healthy subjects at a rate of 1000 Hz. For each emotional state, ECGs were recorded for 5 min and the RR interval time series was extracted from these ECGs. The obtained results confirm that PE and PME increase significantly during the emotional states of happiness, sadness, anger, and disgust. Both symbolic quantifiers also increase but not in a significant way for the emotional state of fear. Moreover, it is found that PME is more sensitive than PE for discriminating non-neutral from neutral emotional states.