Key result
Music stimulation significantly altered the Largest Lyapunov exponent of heart rate variability compared to baseline (p<0.01, Cohen's d>0.8), enabling an 84% overall correct classification rate of emotional states using an SVM classifier.
Why the study?
Does listening to different types of music affect human emotions as measured by the Largest Lyapunov Exponent of Heart Rate Variability in healthy subjects?
Observational (n=30)
No
Does listening to different types of music affect human emotions as measured by the Largest Lyapunov Exponent of Heart Rate Variability in healthy subjects?
Effect estimate: Cohen's d > 0.8
p-value: p=<0.01
Different types of music evoke distinct emotional patterns that can be objectively classified using the Largest Lyapunov Exponent of Heart Rate Variability.
May aid objective emotion assessment via HRV; hypothesis-generating and should not yet change practice.
The relationship between music and human emotions is a very interesting area. But how exactly music affects human emotions and what the valid parameters needed to classify the pattern is also an open question. In this paper, we consider the effect of four different types of music on human emotions through the nonlinear analysis of Heart rate variability (HRV). The t-test shows that the Largest lyapunov exponent (LLE) of HRV acquired from subjects with or without music stimulation is significantly different (p<0.01, Cohen's d>0.8). More importantly, the LLE of HRV is also influenced by different types of music respectively, and then we applied LLE as the affective features to recognize the subjects' emotional state which induced by specific types of music. An overall correct rate of 84 percent for quinary classification of amusement, excitement, sadness, fear and the baseline state by SVM classifier are obtained.
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Juan et al. (2016) conducted an observational in Healthy (n=30). Music stimulation (amusement, excitement, sadness, fear) vs. Baseline state (no music) was evaluated on Largest Lyapunov exponent (LLE) of HRV (Cohen's d > 0.8, p=<0.01). Music stimulation significantly altered the Largest Lyapunov exponent of heart rate variability compared to baseline (p<0.01, Cohen's d>0.8), enabling an 84% overall correct classification rate of emotional states using an SVM classifier.
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