Automatic Detection of Characteristic Waves in Electrocardiogram

Abstract

The goal of automatic ECG analysis is to assess the clinical status of the heart system as accurately as possible, and the identification of P and T waves plays a significant role in this matter. This works presents original algorithms for the detection of P and T waves. These algorithms are based on the morphological and temporal characteristics of the electrocardiogram. To test and compare the algorithms' performance, we considered the QTDB and MIT-BIH Arrhythmia annotated databases. The developed algorithms obtained a good performance for the detection of both peaks. In particular, in both the QTDB and MIT-BITH database the P wave detection algorithm obtained considerably higher performance than those presented in the literature (QTDB: 95.87% vs 89.05%; MIT-BITH: 84.65% vs 83.36% for Lead 1). The T wave detection algorithm, achieved best performance than those in literature in the QTDB (89.05% vs 87.49%) while in the MIT-BITH database results were almost comparable to those reported in the literature. These findings suggest the high potential of the proposed simple algorithms for P and T wave detection in ECG.