Journal of Vascular Medicine & Surgery

Enhanced ischemia classifier for ECG signals

World Congress on Vascular Diseases, Medicine & Surgeons Summit

October 24-25, 2016 Chicago, USA

Amit Kumar Manocha

Maharaja Agrasen University, India

Posters & Accepted Abstracts: Vasc Med Surg

Abstract:

In this research, a novel method has been developed for the detection of ischemia using an iso-electric energy function (IEEF) resulting from ST segment deviations in ECG signals. The method consists of five stages: Pre-processing, delineation, measurement of iso-electric energy, a beat characterization algorithm and detection of ischemia. The iso-electric energy threshold is used to differentiate ischemic beats from normal beats in two stages for ischemic episode detection. Then, ischemic episodes are classified as transmural or sub-endocardial. The method is validated for entire recordings of the annotated European ST-T database (EDB). The results show 96.74% average sensitivity (SE) and 97.16% average positive predictivty (+P). These results are significantly better than those of existing methods cited in the literature. The advantage of the developed method includes simplicity, ruggedness and automatic discarding of noisy beats. The efficacy of the developed method encourages to be used in existing clinical systems.

Biography :

Email: manocha82@gmail.com