Application of convolutional neural network classifier for wireless arrhythmia detection

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Abstract

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.

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Kusumandari, D. E., Rizqyawan, M. I., Yazir, M., Turnip, M., Darma, A., & Turnip, A. (2018). Application of convolutional neural network classifier for wireless arrhythmia detection. In Journal of Physics: Conference Series (Vol. 1080). Institute of Physics Publishing. https://doi.org/10.1088/1742-6596/1080/1/012048

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