Aiding the Detection of QRS Complex in ECG Signals by Detecting S Peaks Independently.
In this paper, a novel algorithm for the accurate detection of QRS complex by combining the independent detection of R and S peaks, using fusion algorithm is proposed. R peak detection has been extensively studied and is being used to detect the QRS complex. Whereas, S peaks, which is also part of QRS complex can be independently detected to aid the detection of QRS complex. In this paper, we suggest a method to first estimate S peak from raw ECG signal and then use them to aid the detection of QRS complex. The amplitude of S peak in ECG signal is relatively weak than corresponding R peak, which is traditionally used for the detection of QRS complex, therefore, an appropriate digital filter is designed to enhance the S peaks. These enhanced S peaks are then detected by adaptive thresholding. The algorithm is validated on all the signals of MIT-BIH arrhythmia database and noise stress database taken from physionet.org. The algorithm performs reasonably well even for the signals highly corrupted by noise. The algorithm performance is confirmed by sensitivity and positive predictivity of 99.99% and the detection accuracy of 99.98% for QRS complex detection. The number of false positives and false negatives resulted while analysis has been drastically reduced to 80 and 42 against the 98 and 84 the best results reported so far.
['Sabherwal|Pooja|P|', 'Singh|Latika|L|', 'Agrawal|Monika|M|']
D000200:Action Potentials D000465:Algorithms D016477:Artifacts D001331:Automation D016022:Case-Control Studies D016208:Databases, Factual D004562:Electrocardiography D005188:False Negative Reactions D005189:False Positive Reactions D006331:Heart Diseases D006339:Heart Rate D006801:Humans D011237:Predictive Value of Tests D015203:Reproducibility of Results D012815:Signal Processing, Computer-Assisted D013997:Time Factors D058067:Wavelet Analysis
QRS complex S peak Fusion algorithm Wavelet transform