چاپ صفحه |  صفحه نخست سامانه |  چکیده مقاله |  نویسندگان |  دانلود مقاله | دانشگاه علوم پزشکی تبریز |
| نویسنده ثبت کننده مقاله | رقیه ارونقی |
| مرحله جاری مقاله | تایید نهایی |
| دانشکده/مرکز مربوطه | دانشکده علوم نوین پزشکی |
| کد مقاله | 62098 |
| عنوان فارسی مقاله | Fusion of ECG and ABP signals based on wavelet transform for cardiac arrhythmias classification |
| عنوان لاتین مقاله | Fusion of ECG and ABP signals based on wavelet transform for cardiac arrhythmias classification |
| ناشر | 4 |
| آیا مقاله از طرح تحقیقاتی و یا منتورشیپ استخراج شده است؟ | بلی |
| عنوان نشریه (خارج از لیست فوق) | Computer Methods and Programs in Biomedicine |
| نوع مقاله | Research Letter |
| نحوه ایندکس شدن مقاله | ایندکس شده سطح یک – ISI - Web of Science |
| آدرس لینک مقاله/ همایش در شبکه اینترنت | https://www.sciencedirect.com/science/article/pii/S0169260716314638# |
| Background and Objective: Each of Electrocardiogram (ECG) and Atrial Blood Pressure (ABP) signals contain information of cardiac status. This information can be used for diagnosis and monitoring of diseases. The majority of previously proposed methods rely only on ECG signal to classify heart rhythms. In this paper, ECG and ABP were used to classify five different types of heart rhythms. To this end, two mentioned signals (ECG and ABP) have been fused. Methods: These physiological signals have been used from MINIC physioNet database. ECG and ABP signals have been fused together on the basis of the proposed Discrete Wavelet Transformation fusion technique. Then, some frequency features were extracted from the fused signal. To classify the different types of cardiac arrhythmias, these features were given to a multi-layer perceptron neural network. Results: In this study, the best results for the proposed fusion algorithm were obtained. In this case, the accuracy rates of 96.6%, 96.9%, 95.6% and 93.9% were achieved for two, three, four and five classes,respectively. However, the maximum classification rate of 89% was obtained for two classes on the basis of ECG features. Conclusions: It has been found that the higher accuracy rates were acquired by using the proposed fusion technique. The results confirmed the importance of fusing features from different physiological signals to gain more accurate assessments. |
| نویسنده | نفر چندم مقاله |
|---|---|
| رقیه ارونقی | اول |
| سبلان دانشور | دوم |
| نام فایل | تاریخ درج فایل | اندازه فایل | دانلود |
|---|---|---|---|
| letter.doc | 1396/10/20 | 1206784 | دانلود |
| fusion.pdf | 1396/10/20 | 1676273 | دانلود |
