Investigating the effect of traditional Persian music on ECG signals in young women using wavelet transform and neural networksBehzad Abedi1, Ataollah Abbasi2, Atefeh Goshvarpour2
1School of Advanced Medical Science, Tabriz University of Medical Sciences; Tabriz-Iran
2Computational Neuroscience Laboratory, Department of Biomedical Engineering, Faculty of Electrical Engineering, Sahand University of Technology; Tabriz-Iran
Objective: In the past few decades, several studies have reported the physiological effects of listening to music. The physiological effects of different music types on different people are different. In the present study, we aimed to examine the effects of listening to traditional Persian music on electrocardiogram (ECG) signals in young women.Keywords: artificial neural network, discrete wavelet transform, electrocardiogram, music, probabilistic neural network
Methods: Twenty-two healthy females participated in this study. ECG signals were recorded under two conditions: rest and music. For each ECG signal, 20 morphological and wavelet-based features were selected. Artificial neural network (ANN) and probabilistic neural network (PNN) classifiers were used for the classification of ECG signals during and before listening to music.
Results: Collected data were separated into two data sets: train and test. Classification accuracies of 88% and 97% were achieved in train data sets using ANN and PNN, respectively. In addition, the test data set was employed for evaluating the classifiers, and classification rates of 84% and 93% were obtained using ANN and PNN, respectively.
Conclusion: The present study investigated the effect of music on ECG signals based on wavelet transform and morphological features. The results obtained here can provide a good understanding on the effects of music on ECG signals to researchers. (Anatol J Cardiol 2017; 17: 000-00)
Corresponding Author: Ataollah Abbasi, Iran