Comparison of Electrodermal Activity Signal Decomposition Techniques for Emotion Recognition

• Published in: IEEE access Vol. 12; pp. 19952 - 19966
• Main Authors: Veeranki, Yedukondala Rao, Ganapathy, Nagarajan, Swaminathan, Ramakrishnan, Posada-Quintero, Hugo F.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Arousal; classification; Computational modeling; Convexity; Decomposition; Deconvolution; electrodermal activity; Emotion; Emotion recognition; Emotions; Feature extraction; Magnetohydrodynamics; phasic component; Physiology; Support vector machines; Sympathetic nervous system; tonic component

Emotions play an essential role in human life as they are linked to well-being and markers of various diseases. Physiological signals can be used to assess emotions objectively and continuously. Electrodermal activity (EDA) is particularly interesting to assess emotions due to its relationship with...