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Application of convolutional neural network classifier for wireless arrhythmia detection
| Content Provider | Scilit |
|---|---|
| Author | Kusumandari, D. E. Rizqyawan, M. I. Yazir, M. Turnip, M. Darma, A. Turnip, A. |
| Copyright Year | 2018 |
| Description | Journal: Journal of Physics: Conference Series The heart as the main system of blood circulation in our body can certainly experience abnormalities called arrhythmia. Information of the arrhythmia is very important in the field of health and electrocardiogram is one of the most commonly used tool to detect the heart abnormalities. A wireless monitoring of the heart activities has been developed. An application of convolutional neural network classifier for arrhythmia detection is proposed. Twenty four health subjects were tested in the three experiment methods. The classification accuracy about average 93,97% is obtained. |
| Related Links | http://iopscience.iop.org/article/10.1088/1742-6596/1080/1/012048/pdf |
| ISSN | 17426588 |
| e-ISSN | 17426596 |
| DOI | 10.1088/1742-6596/1080/1/012048 |
| Journal | Journal of Physics: Conference Series |
| Issue Number | 1 |
| Volume Number | 1080 |
| Language | English |
| Publisher | IOP Publishing |
| Publisher Date | 2018-08-01 |
| Access Restriction | Open |
| Subject Keyword | Journal: Journal of Physics: Conference Series Hardware and Architecture Neural Network Classifier Convolutional Neural Network Arrhythmia Detection |
| Content Type | Text |
| Resource Type | Article |
| Subject | Physics and Astronomy |
