Evaluating the Effects of Traditional Persian Music on Nonlinear Parameters of HRV

Music has the power to evoke particular emotional states. In this research, the impact of three types of traditional Persian music (happy, peaceful, and sad) on nonlinear parameters for heart rate variability (HRV) analysis is studied. After extracting RR intervals from ECG, the nonlinear parameters were obtained. The parameters include normal descriptors of Poincare plot (SD1 and SD2), Global Occurrence Matrix (GOM), and Co-occurrence Matrix (COM) parameters which demonstrate the dynamic in the Poincare plot. The extracted features in three groups of music stimuli were compared with the controls and then k-nearest neighbor classifier used to distinguish different emotions induced by the different music. The results show that the GOM and COM features were significantly different between different emotions induced by music stimuli. Promising results on emotion classification (accuracy of 90%) in response to music stimuli highlight the power of nonlinear analysis of HRV in emotion assessment application.