Mood Estimation Considering Features to Contribute Mood Using ECG Signals during Recalling Incidents from the Past
Mood Estimation Considering Features to Contribute Mood Using ECG Signals during Recalling Incidents from the Past
复制标题
在回忆过去的事件期间使用心电图信号进行情绪估计，考虑贡献情绪的特征
DOI：
10.1109/gcce.2018.8574771
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Shohei Kato
中科院分区：
文献类型：
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作者：
A. Kitagawa;Shohei Kato
The purpose of this study is to evaluate mood quantitatively using ECG signals for preventing depression and anxiety. For this purpose, we calculate indexes of the heart rate variability and chaos from ECG signals during recalling incidents from the past and classify mood using Support Vector Machine (SVM). The results of estimating the intensity of five kinds of mood using a combination of Random Forest (RF) and SVM show more than 70 % accuracy rate for any mood except pleasantness. The results indicate the effectiveness of mood classification using ECG signals during recalling incidents from the past.
