This paper reports on how emotional states elicited by affective sounds can be effectively recognized by means of estimates of Autonomic Nervous System (ANS) dynamics. Specifically, emotional states are modeled as a combination of arousal and valence dimensions according to the well-known circumplex model of affect, whereas the ANS dynamics is estimated through standard and nonlinear analysis of Heart rate variability (HRV) exclusively, which is derived from the electrocardiogram (ECG). In addition, Lagged Poincare Plots of the HRV series were also taken into account. The affective sounds were gathered from the International Affective Digitized Sound System and grouped into four different levels of arousal (intensity) and two levels of valence (unpleasant and pleasant). A group of 27 healthy volunteers were administered with these standardized stimuli while ECG signals were continuously recorded. Then, those HRV features showing significant changes (p $ 0.05 from statistical tests) between the arousal and valence dimensions were used as input of an automatic classification system for the recognition of the four classes of arousal and two classes of valence. Experimental results demonstrated that a quadratic discriminant classifier, tested through Leave-One-Subject-Out procedure, was able to achieve a recognition accuracy of 84.72 percent on the valence dimension, and 84.26 percent on the arousal dimension.

/pdf/recognizing-emotions-induced-by-affective-sounds-through-4wgym4qxen.pdf

Recognizing Emotions Induced by Affective Sounds through Heart Rate Variability

Music can powerfully evoke and modulate emotions and moods, along with changes in heart activity, blood pressure (BP), and breathing. Although there is great heterogeneity in methods and quality among previous studies on effects of music on the heart, the following findings emerge from the literature: Heart rate (HR) and respiratory rate (RR) are higher in response to exciting music compared with tranquilizing music. During musical frissons (involving shivers and piloerection), both HR and RR increase. Moreover, HR and RR tend to increase in response to music compared with silence, and HR appears to decrease in response to unpleasant music compared with pleasant music. We found no studies that would provide evidence for entrainment of HR to musical beats. Corresponding to the increase in HR, listening to exciting music (compared with tranquilizing music) is associated with a reduction of heart rate variability (HRV), including reductions of both low-frequency and high-frequency power of the HRV. Recent findings also suggest effects of music-evoked emotions on regional activity of the heart, as reflected in electrocardiogram amplitude patterns. In patients with heart disease (similar to other patient groups), music can reduce pain and anxiety, associated with lower HR and lower BP. In general, effects of music on the heart are small, and there is great inhomogeneity among studies with regard to methods, findings, and quality. Therefore, there is urgent need for systematic high-quality research on the effects of music on the heart, and on the beneficial effects of music in clinical settings.

https://www.zora.uzh.ch/id/eprint/112776/1/ehv430.pdf

Music and the heart

This paper presents an automatic ECG-based emotion recognition algorithm for human emotion recognition. First, we adopt a musical induction method to induce participants’ real emotional states and collect their ECG signals without any deliberate laboratory setting. Afterward, we develop an automatic ECG-based emotion recognition algorithm to recognize human emotions elicited by listening to music. Physiological ECG features extracted from the time-, and frequency-domain, and nonlinear analyses of ECG signals are used to find emotion-relevant features and to correlate them with emotional states. Subsequently, we develop a sequential forward floating selection-kernel-based class separability-based (SFFS-KBCS-based) feature selection algorithm and utilize the generalized discriminant analysis (GDA) to effectively select significant ECG features associated with emotions and to reduce the dimensions of the selected features, respectively. Positive/negative valence, high/low arousal, and four types of emotions (joy, tension, sadness, and peacefulness) are recognized using least squares support vector machine (LS-SVM) recognizers. The results show that the correct classification rates for positive/negative valence, high/low arousal, and four types of emotion classification tasks are 82.78, 72.91, and 61.52 percent, respectively.

Automatic ECG-Based Emotion Recognition in Music Listening

Physiological sensors and interfaces for mental healthcare are becoming of great interest in research and commercial fields. Specifically, biomedical sensors and related ad hoc signal processing methods can be profitably used for supporting objective, psychological assessments. However, a simple system able to automatically classify the emotional state of a healthy subject is still missing. To overcome this important limitation, we here propose the use of convex optimization-based electrodermal activity (EDA) framework and clustering algorithms to automatically discern arousal and valence levels induced by affective sound stimuli. EDA recordings were gathered from 25 healthy volunteers, using only one EDA sensor to be placed on fingers. Standardized stimuli were chosen from the International Affective Digitized Sound System database, and grouped into four different levels of arousal (i.e., the levels of emotional intensity) and two levels of valence (i.e., how unpleasant/pleasant a sound can be perceived). Experimental results demonstrated that our system is able to achieve a recognition accuracy of 77.33% on the arousal dimension, and 84% on the valence dimension.

/pdf/arousal-and-valence-recognition-of-affective-sounds-based-on-pj9ymb3bdr.pdf

Arousal and Valence Recognition of Affective Sounds Based on Electrodermal Activity

Fil: Perez Lloret, Santiago. Pontificia Universidad Catolica Argentina "Santa Maria de los Buenos Aires". Facultad de Ciencias Medicas. Departamento de Docencia e Investigacion; Argentina. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Oficina de Coordinacion Administrativa Houssay; Argentina

/pdf/effects-of-different-relaxing-music-styles-on-the-autonomic-47p0cs1nq1.pdf

Effects of different "relaxing" music styles on the autonomic nervous system.

https://www.scielo.br/pdf/clin/v68n7/1807-5932-clin-68-07-960.pdf

The effects of auditory stimulation with music on heart rate variability in healthy women

The literature investigated the effects of chronic baroque music auditory stimulation on the cardiovascular system. However, it lacks in the literature the acute effects of different styles of music on cardiac autonomic regulation. To evaluate the acute effects of baroque and heavy metal music on heart rate variability (HRV) in women. The study was performed in 21 healthy women between 18 and 30 years old. We excluded persons with previous experience with music instrument and those who had affinity with the song styles. All procedures were performed in the same sound-proof room. We analyzed HRV in the time (standard deviation of normal-to-normal respiratory rate (RR) intervals, root-mean square of differences between adjacent normal RR intervals in a time interval, and the percentage of adjacent RR intervals with a difference of duration greater than 50 ms) and frequency (low frequency [LF], high frequency [HF], and LF/HF ratio) domains. HRV was recorded at rest for 10 min. Subsequently they were exposed to baroque or heavy metal music for 5 min through an earphone. After the first music exposure they remained at rest for more 5 min and them they were exposed again to baroque or heavy metal music. The sequence of songs was randomized for each individual. The power analysis provided a minimal number of 18 subjects. Shapiro-Wilk to verify normality of data and analysis of variance for repeated measures followed by the Bonferroni test for parametric variables and Friedman's followed by the Dunn's post-test for non-parametric distributions. During the analysis of the time-domain indices were not changed. In the frequency-domain analysis, the LF in absolute units was reduced during the heavy metal music stimulation compared to control. Acute exposure to heavy metal music affected the sympathetic activity in healthy women.

The effects of different styles of musical auditory stimulation on cardiac autonomic regulation in healthy women.

The effects of different styles of musical auditory stimulation on cardiac autonomic regulation in healthy women

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The effects of auditory stimulation with music on heart rate variability in healthy women

The effects of different styles of musical auditory stimulation on cardiac autonomic regulation in healthy women.

The effects of different styles of musical auditory stimulation on cardiac autonomic regulation in healthy women