New Measurement Analysis for Emotion Detection Using ECG Data

被引：1
|
作者：
Dorner, Verena [1 ]
Ortiz, Cesar Enrique Uribe [1 ,2 ]
机构：
[1] Vienna Univ Econ & Business, Vienna, Austria
[2] Vienna Univ Technol, Vienna, Austria
来源：
INFORMATION SYSTEMS AND NEUROSCIENCE, NEUROIS RETREAT 2022 | 2022年 / 58卷
关键词：
ECG; Heart Rate Variability; Algorithm; Experiment; HEART-RATE-VARIABILITY; STRESS; AROUSAL; METAANALYSIS;
D O I：
10.1007/978-3-031-13064-9_23
中图分类号：
B84 [心理学];
学科分类号：
04 ; 0402 ;
摘要：
Electrocardiography (ECG) offers a lot of information that can be processed to make inferences about levels of arousal, stress, and emotions. One of the most popular measures is the Heart Rate Variability (HRV), a measure of the variation on the heart beats, which is only taken from one heart movement of the cardiac cycle, the R-wave. We explore the other heart movements of the cardiac cycle observed in the ECG with the aim of deriving new proxy measures for stress and arousal to enrich and complement HRV analysis. This article discusses existing approaches, suggests new measurements for stress and arousal detected in an ECG, and examines their potential to contribute new information based on their correlations with two HRV measures.
引用
收藏
页码：219 / 227
页数：9
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