Comparison of Different Clasification Algorithms Using Easily Calculated Features

Scientific Meeting on Electric Electronics, Computer Science, Biomedical Engineerings (EBBT) -- APR 20-21, 2017 -- Istanbul Arel Univ, Istanbul, TURKEYWOS: 000413686600037Telemedicine has started to be beneficial to patients in remote regions. It is very important to monitor the ECG signals of these patients with heart disorders. Developments in information technology have started to provide important contribution to the clinical decision support systems for early detection and diagnosis. This study aimed to be part of clinical decision support systems and used easily calculated features for detection of ECG arrhythmia. Different classification methods are compared using these features. The performance of the method is tested on data used obtained from the PhysioNet database.IEEE Turkey Sect, IEEE EMB, IEEEScientific and Technological Research Council of Turkey (TUBITAK)Turkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [114E452]This research is supported by The Scientific and Technological Research Council of Turkey (TUBITAK) under Grant 114E452