Attention emotion recognition via ECG signals

作     者：Aihua Mao Zihui Du Dayu Lu Jie Luo Aihua Mao;Zihui Du;Dayu Lu;Jie Luo

作者机构：School of Computer Science&EngineeringSouth China University of TechnologyGuangzhou 510006China School of MedicineSouth China University of TechnologyGuangzhou 510006China School of Fine Art and Artistic DesignGuangzhou UniversityGuangzhou 510006China 

出 版 物：《Quantitative Biology》 (定量生物学（英文版）)

年 卷 期：2022年第10卷第3期

页      面：276-286页

核心收录：

学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：The work of this paper is financially supported by NSF of Guangdong Province(No.2019A1515010833) the Fundamental Research Funds for the Central Universities(No.2020ZYGXZR089) the Social Science Research Base of Guangdong Province-Research Center of Network Civilization in New Era of SCUT 

主　　题：affective computing attention recognition ECG signals 

摘      要：Background:Physiological signal-based research has been a hot topic in affective *** works mainly focus on some strong,short-lived emotions(e.g.,joy,anger),while the attention,which is a weak and long-lasting emotion,receives less *** this paper,we present a study of attention recognition based on electrocardiogram(ECG)signals,which contain a wealth of information related to ***:The ECG dataset is derived from 10 subjects and specialized for attention *** relieve the impact of noise of baseline wondering and power-line interference,we apply wavelet threshold denoising as preprocessing and extract rich features by pan-tompkins and wavelet decomposition *** improve the generalized ability,we tested the performance of a variety of combinations of different feature selection algorithms and ***:Experiments show that the combination of generic algorithm and random forest achieve the highest correct classification rate(CCR)of 86.3%.Conclusion:This study indicates the feasibility and bright future of ECG-based attention research.