Engineering Commons^™

Sistem Cerdas Deteksi Sinyal Elektrokardiogram (Ekg) Untuk Klasifikasi Jantung Normal Dan Abnormal Menggunakan Jaringan Syaraf Tiruan (Jst), Myza Rifali, Dessy Irmawati

Elinvo (Electronics, Informatics, and Vocational Education)

This article aims to describe the accuracy of signal processing using neural networks. The design of this final project hardware consists of Arduino Uno, AD8232 module and electrodes. ECG signals obtained from respondents were used as test data for normal ECG signals, while for abnormal class test data the data used were obtained from the research website, namely physionet with atrial fibrillation class. The design process in this system includes the process of data acquisition, training, feature extraction, testing and classification with artificial neural networks. Based on the results of the performance of this device to record ECG signals on …