دورية أكاديمية
Detection of Coronary Artery Disease Using Multi-Domain Feature Fusion of Multi-Channel Heart Sound Signals
| العنوان: | Detection of Coronary Artery Disease Using Multi-Domain Feature Fusion of Multi-Channel Heart Sound Signals |
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| المؤلفون: | Tongtong Liu, Peng Li, Yuanyuan Liu, Huan Zhang, Yuanyang Li, Yu Jiao, Changchun Liu, Chandan Karmakar, Xiaohong Liang, Mengli Ren, Xinpei Wang |
| المصدر: | Entropy, Vol 23, Iss 6, p 642 (2021) |
| بيانات النشر: | MDPI AG, 2021. |
| سنة النشر: | 2021 |
| المجموعة: | LCC:Science LCC:Astrophysics LCC:Physics |
| مصطلحات موضوعية: | heart sound, coronary artery disease, multi-channel, entropy, cross entropy, Science, Astrophysics, QB460-466, Physics, QC1-999 |
| الوصف: | Heart sound signals reflect valuable information about heart condition. Previous studies have suggested that the information contained in single-channel heart sound signals can be used to detect coronary artery disease (CAD). But accuracy based on single-channel heart sound signal is not satisfactory. This paper proposed a method based on multi-domain feature fusion of multi-channel heart sound signals, in which entropy features and cross entropy features are also included. A total of 36 subjects enrolled in the data collection, including 21 CAD patients and 15 non-CAD subjects. For each subject, five-channel heart sound signals were recorded synchronously for 5 min. After data segmentation and quality evaluation, 553 samples were left in the CAD group and 438 samples in the non-CAD group. The time-domain, frequency-domain, entropy, and cross entropy features were extracted. After feature selection, the optimal feature set was fed into the support vector machine for classification. The results showed that from single-channel to multi-channel, the classification accuracy has increased from 78.75% to 86.70%. After adding entropy features and cross entropy features, the classification accuracy continued to increase to 90.92%. The study indicated that the method based on multi-domain feature fusion of multi-channel heart sound signals could provide more information for CAD detection, and entropy features and cross entropy features played an important role in it. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1099-4300 |
| Relation: | https://www.mdpi.com/1099-4300/23/6/642; https://doaj.org/toc/1099-4300 |
| DOI: | 10.3390/e23060642 |
| URL الوصول: | https://doaj.org/article/fde4d76f427f4694b8dc5905eeca06ad |
| رقم الأكسشن: | edsdoj.fde4d76f427f4694b8dc5905eeca06ad |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 10994300 |
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| DOI: | 10.3390/e23060642 |