ECG artifacts detection in noncardiovascular signals using Slope Sum Function and Teager Kaiser Energy

Abstract

A new method for ECG artifacts detection from noncardiovascular physiological signals namely Electroencephalogram (EEG), Electrooculogram (EOG) and Electromyogram (EMG), without the need of any additional synchronous ECG channel, is being proposed. This ECG artifacts (R peaks) detection method uses Slope Sum Function and Teager Kaiser Energy operator with an adaptive threshold. The performance of algorithm has been evaluated on PhysioNet database of challenge 2014 and MIT BIH polysomnographic database. The algorithm has shown improved ECG artifacts detection results as compared to that of direct application of Teager Kaiser energy operator on noncardiovascular signals. The detection rates of ECG artifacts with the new method is 96.12 percent with FN rate of 3.88 percent and FP rate of 3.16 percent for PhysioNet database challenge 2014. For MIT BIH database the artifacts detection rate is 95.57 percent with FN rate of 4.44 percent and FP rate of 3.57 percent, which shows an excellent performance in ECG artifacts detection.