A robust QRS detection using novel pre-processing techniques and kurtosis based enhanced efficiency. (June 2016) - Sharma, Lakhan Dev; Sunkaria, Ramesh Kumar
Highlights: The technique works with minimum pre-processing required and on simple decision logic. R-peak detection with improved accuracy. A Kurtosis based false positive correction has been proposed. The technique is widely validated over four standard databases. Abstract: The QRS complex detection is very imperative step prior to detecting any other wave component, beat segments, or any other morphological parameters of electrocardiogram (ECG). The paper presents a novel technique for QRS complex detection with minimum pre-processing required. The technique uses two-stage median filter and Savitzky–Golay smoothing filter for pre-processing. The decision rule is based on root-mean-square of the signal. The technique evolves with a novel approach for isoelectric line detection and a kurtosis-based false positive correction method. The robustness of the proposed technique been substantiated on Fantasia Database (FTD), MIT-BIH Arrhythmia Database (MIT-AD), MIT-BIH Normal Sinus Rhythm Database (MIT-NSD), and BIDMC Congestive Heart Failure Database (CHFD). The detection sensitivity (Se), positive predictivity (+P), detection error rate (DER), and accuracy (Ac) of proposed technique on FTD is Se = 99.90%, +P = 99.91%, DER = 0.19%, and Ac = 99.81%. On MIT-AD the technique has Se = 99.50%, +P = 99.56%, DER = 0.93%, and Ac = 99.08%. The technique shows Se = 99.36%, +P = 99.43%, DER = 1.21%, and Ac = 98.81% on MIT-NSD. Tested on CHFD, the techniques has Se = 99.68%, +P = 99.78%, DER = 0.52%, and Ac = 99.46%. The technique is also tested on self-recorded data-set and has Se = 99.97%, +P = 99.99%, DER = 0.04%, and Ac = 99.96%. The observation of above results shows the high performance and robustness of QRS complex detection, which will lead to highly accurate cardiac health prognosis.