Abedi Behzad, Abbasi Ataollah, Goshvarpour Atefeh, Khosroshai Hamid Tayebi, Javanshir Elnaz
School of Advanced Medical Sciences, Tabriz University of Medical Sciences, Tabriz, Iran.
Computational Neuroscience Laboratory, Department of Biomedical Engineering, Faculty of Electrical Engineering, Sahand University of Technology, Tabriz, Iran.
Indian Heart J. 2017 Jul-Aug;69(4):491-498. doi: 10.1016/j.ihj.2016.12.016. Epub 2017 Jan 10.
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 not similar. Therefore, in the present study, we have sought to examine the effects of traditional Persian music on the cardiac function in young women. Twenty-two healthy females participated in this study. ECG signals were recorded in two conditions: rest and music. For each of the 21 ECG signals (15 morphological and six wavelet based feature) features were extracted. SVM classifier was used for the classification of ECG signals during and before the music. The results showed that the mean of heart rate, the mean amplitude of R-wave, T-wave, and P-wave decreased in response to music. Time-frequency analysis revealed that the mean of the absolute values of the detail coefficients at higher scales increased during rest. The overall accuracy of 91.6% was achieved using polynomial kernel and RBF kernel. Using linear kernel, the best result (with the accuracy rate of 100%) was attained.
在过去几十年中,多项研究报告了听音乐的生理效应。不同类型的音乐对不同人的生理效应并不相同。因此,在本研究中,我们试图研究传统波斯音乐对年轻女性心脏功能的影响。22名健康女性参与了本研究。在休息和听音乐两种状态下记录心电图信号。针对21个心电图信号中的每一个(15个形态学特征和6个基于小波的特征)提取特征。支持向量机分类器用于对听音乐期间和之前的心电图信号进行分类。结果表明,听音乐时心率平均值、R波、T波和P波的平均振幅降低。时频分析显示,休息期间较高尺度上细节系数绝对值的平均值增加。使用多项式核和径向基函数核实现了91.6%的总体准确率。使用线性核时,获得了最佳结果(准确率为100%)。