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首页> 外文期刊>Journal of fiber bioengineering and informatics >Detrended Fluctuation Analysis Based on the Affective ECG
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Detrended Fluctuation Analysis Based on the Affective ECG

机译：基于情感心电图的去趋势波动分析

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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.
机译：心电图（ECG）是最重要的生理信号之一，已被证明包含可靠的情感信息。电影中的情感片段会诱发包括幸福，悲伤，愤怒和恐惧在内的四种客观影响，而Biopac MP 150会同时记录ECG信号。在一个独立的实验中，情感视频被播放了两次，在第二个演示中，获得了情感重新评估的新闻文件，该文件记录了参与者的主观体验，并帮助我们拦截了可靠的情感心电图。去趋势波动分析用于通过情感心电图中的缩放指数来量化时间相关性。结果表明，幸福，悲伤，愤怒和恐惧的心电图具有长期的相关性。然后将比例指数由Fisher的二元分类器用作情感特征，结果表明，正确识别幸福感，悲伤，愤怒和恐惧的正确率分别为89.74％，90.1％，70.43％，84.44％。整个实验表明，非线性特征在不同的情感上有很好的区别。

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