چاپ صفحه |  صفحه نخست سامانه |  چکیده مقاله |  نویسندگان |  دانلود مقاله | دانشگاه علوم پزشکی تبریز |
| نویسنده ثبت کننده مقاله | بهزاد عابدی |
| مرحله جاری مقاله | تایید نهایی |
| دانشکده/مرکز مربوطه | دانشکده علوم نوین پزشکی |
| کد مقاله | 60663 |
| عنوان فارسی مقاله | Investigating the effect of traditional Persian music on ECG signals in young women using wavelet transform and neural networks |
| عنوان لاتین مقاله | Investigating the effect of traditional Persian music on ECG signals in young women using wavelet transform and neural networks |
| ناشر | 3 |
| آیا مقاله از طرح تحقیقاتی و یا منتورشیپ استخراج شده است؟ | خیر |
| عنوان نشریه (خارج از لیست فوق) | |
| نوع مقاله | Original Article |
| نحوه ایندکس شدن مقاله | ایندکس شده سطح یک – ISI - Web of Science |
| آدرس لینک مقاله/ همایش در شبکه اینترنت | http://www.anakarder.com/jvi.aspx?pdir=anatoljcardiol&plng=eng&un=AJC-60430&look4= |
| 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. 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: 398-403) |
| نویسنده | نفر چندم مقاله |
|---|---|
| بهزاد عابدی | اول |
| نام فایل | تاریخ درج فایل | اندازه فایل | دانلود |
|---|---|---|---|
| AJC-60430-ORIGINAL_INVESTIGATION-ABBASI.pdf | 1396/02/21 | 170585 | دانلود |
