Key result
A modified S-transform based QRS complex detection algorithm achieved a sensitivity of 99.91%, positive predictivity of 99.91%, and overall accuracy of 99.77%.
A modified S-transform algorithm provides highly accurate QRS complex detection with an excellent search back range for ECG signal analysis.
May enhance ECG algorithm development; leaves open prospective clinical validation before adoption.
Accurate detection of QRS complexes is essential for the investigation of heart rate variability. Several transform techniques have been proposed and extensively used for the detection and analysis of QRS complexes. In this proposed work, the de-noised ECG signal is subjected to a modified S-transform for QRS complex detection.The performance analysis of the proposed work is evaluated using parameters such as sensitivity, positive predictivity and accuracy. The algorithm delivers sensitivity, positive predictivity and overall accuracy of 99.91, 99.91 and 99.77%, respectively. Furthermore, a search back mechanism is employed, which specifies the filtered electrocardiogram (ECG) segment, which was traced for the true R-peak locations. The modified S-transform based QRS complex detection algorithm provides an excellent search back range of only ±2 samples in comparison with other earlier proposed algorithms.
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Birendra Biswal (2017) studied QRS complex detection in ECG signals. Modified S-transform algorithm vs. Earlier proposed algorithms was evaluated on Sensitivity, positive predictivity, and overall accuracy of QRS complex detection. A modified S-transform based QRS complex detection algorithm achieved a sensitivity of 99.91%, positive predictivity of 99.91%, and overall accuracy of 99.77%.
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