Arousal recognition system based on heartbeat dynamics during auditory elicitation

• Published in: 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) Vol. 2015; pp. 6110 - 6113
• Main Authors: Nardelli, Mimma, Valenza, Gaetano, Greco, Alberto, Lanata, Antonio, Scilingo, Enzo Pasquale
• Format: Conference Proceeding Journal Article
• Language: English
• Published: United States IEEE 01.01.2015
• Subjects: Accuracy; Adult; Algorithms; Arousal - physiology; Autonomic Nervous System - physiology; Electrocardiography; Emotions - physiology; Feature extraction; Frequency measurement; Heart Rate - physiology; Heart rate variability; Humans; Nonlinear dynamical systems; Nonlinear Dynamics; Physiology
• ISSN: 1094-687X; 1557-170X
• DOI: 10.1109/EMBC.2015.7319786

This study reports on the recognition of different arousal levels, elicited by affective sounds, performed using estimates of autonomic nervous system dynamics. Specifically, as a part of the circumplex model of affect, arousal levels were recognized by properly combining information gathered from standard and nonlinear analysis of heartbeat dynamics, which was derived from the electrocardiogram (ECG). Affective sounds were gathered from the International Affective Digitized Sound System and grouped into four different levels of arousal. A group of 27 healthy volunteers underwent such elicitation while ECG signals were continuously recorded. Results showed that a quadratic discriminant classifier, as applied implementing a leave-one-subject-out procedure, achieved a recognition accuracy of 84.26%. Moreover, this study confirms the crucial role of heartbeat nonlinear dynamics for emotion recognition, hereby estimated through lagged Poincare plots.