Emotion Recognition Using Electrodermal Activity Signals and Multiscale Deep Convolutional Neural Network
Author:
Publisher
Springer Science and Business Media LLC
Subject
Health Information Management,Health Informatics,Information Systems,Medicine (miscellaneous)
Link
http://link.springer.com/content/pdf/10.1007/s10916-020-01676-6.pdf
Reference56 articles.
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2. Affanni A, Bernardini R, Piras A, et al (2018) Driver’s stress detection using skin potential response signals. Measurement 122:264–274. https://doi.org/10.1016/j.measurement.2018.03.040
3. Nazarov AI (2018) Comparison of frequency components of EEG and skin potential (quantitative analysis). Exp. Psychol. 11:95–109. https://doi.org/10.17759/exppsy.2018110207
4. Akay A, Hess H (2019) Deep learning: current and emerging applications in medicine and technology. IEEE J. Biomed. Health Inform. 23:906–920. https://doi.org/10.1109/JBHI.2019.2894713, (2019)
5. Alarcao SM, Fonseca MJ (2017) Emotions recognition using EEG signals: a survey. IEEE Trans. Affect. Comput. 10:374–393. https://doi.org/10.1109/TAFFC.2017.2714671
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