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Volume 7, Issue 1
Detrended Fluctuation Analysis Based on the Affective ECG

Jing Cheng & Guangyuan Liu

Journal of Fiber Bioengineering & Informatics, 7 (2014), pp. 91-102.

Published online: 2014-07

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  • Abstract
Electrocardiography (ECG) is one of the most important physiological signals, which has been proven to contain reliable affective information. Four kinds of objective affects including happiness, sadness, angry and fear, are induced by affective fragments from movies, and ECG signals are recorded by Biopac MP 150 synchronously. In an independent experiment the affective videos are played twice, and in the second presentation the press file of affective re-evaluation is obtained, which registers the subjective experience of participants and help us intercept the reliable affective ECG. The detrended fluctuation analysis is used to quantitate the temporal correlations by the scaling exponent in affective ECG. And the result showed that ECG of happiness, sadness, angry and fear had long-range correlations. Then the scaling exponent is used by the binary classifier of Fisher as an affective feature, and the result showed that the correct recognition rate of happiness, sadness, angry and fear are 89.74%, 90.1%, 70.43%, 84.44% respectively. The whole experiment displays that the nonlinear features have a fine distinction in different emotions.
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@Article{JFBI-7-91, author = {}, title = {Detrended Fluctuation Analysis Based on the Affective ECG}, journal = {Journal of Fiber Bioengineering and Informatics}, year = {2014}, volume = {7}, number = {1}, pages = {91--102}, abstract = {Electrocardiography (ECG) is one of the most important physiological signals, which has been proven to contain reliable affective information. Four kinds of objective affects including happiness, sadness, angry and fear, are induced by affective fragments from movies, and ECG signals are recorded by Biopac MP 150 synchronously. In an independent experiment the affective videos are played twice, and in the second presentation the press file of affective re-evaluation is obtained, which registers the subjective experience of participants and help us intercept the reliable affective ECG. The detrended fluctuation analysis is used to quantitate the temporal correlations by the scaling exponent in affective ECG. And the result showed that ECG of happiness, sadness, angry and fear had long-range correlations. Then the scaling exponent is used by the binary classifier of Fisher as an affective feature, and the result showed that the correct recognition rate of happiness, sadness, angry and fear are 89.74%, 90.1%, 70.43%, 84.44% respectively. The whole experiment displays that the nonlinear features have a fine distinction in different emotions.}, issn = {2617-8699}, doi = {https://doi.org/10.3993/jfbi03201408}, url = {http://global-sci.org/intro/article_detail/jfbi/4769.html} }
TY - JOUR T1 - Detrended Fluctuation Analysis Based on the Affective ECG JO - Journal of Fiber Bioengineering and Informatics VL - 1 SP - 91 EP - 102 PY - 2014 DA - 2014/07 SN - 7 DO - http://doi.org/10.3993/jfbi03201408 UR - https://global-sci.org/intro/article_detail/jfbi/4769.html KW - Affective ECG KW - Press File of Affective Re-evaluation KW - Detrended Fluctuation Analysis KW - Scaling Exponent AB - Electrocardiography (ECG) is one of the most important physiological signals, which has been proven to contain reliable affective information. Four kinds of objective affects including happiness, sadness, angry and fear, are induced by affective fragments from movies, and ECG signals are recorded by Biopac MP 150 synchronously. In an independent experiment the affective videos are played twice, and in the second presentation the press file of affective re-evaluation is obtained, which registers the subjective experience of participants and help us intercept the reliable affective ECG. The detrended fluctuation analysis is used to quantitate the temporal correlations by the scaling exponent in affective ECG. And the result showed that ECG of happiness, sadness, angry and fear had long-range correlations. Then the scaling exponent is used by the binary classifier of Fisher as an affective feature, and the result showed that the correct recognition rate of happiness, sadness, angry and fear are 89.74%, 90.1%, 70.43%, 84.44% respectively. The whole experiment displays that the nonlinear features have a fine distinction in different emotions.
Jing Cheng & Guangyuan Liu. (2019). Detrended Fluctuation Analysis Based on the Affective ECG. Journal of Fiber Bioengineering and Informatics. 7 (1). 91-102. doi:10.3993/jfbi03201408
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