Deformable Part Model Based Arrhythmia Detection Using Time Domain Features

Abstract

Heart disease is one of the major causes of death in many advanced countries. For prevention or treatment of heart disease, getting an early diagnosis from a long time period of electrocardiogram (ECG) examination is necessary. However, it could be a large burden on medical experts to analyze this large amount of data. To reduce the burden and support the analysis, this paper proposes an arrhythmia detection method based on a deformable part model, which absorbs individual variation of ECG waveform and enables the detection of various arrhythmias. Moreover, to detect the arrhythmia in low processing delay, the proposed method only utilizes time domain features. In an experimental result, the proposed method achieved 0.91 F-measure for arrhythmia detection.