Key result
Shannon energy application on a bandpass filter achieved 99.52% accuracy for ECG R-peak detection, slightly outperforming the Stockwell transform method (99.33% accuracy).
Why the study?
Direct comparison between Shannon energy-based R-peak detection methods could not be made due to differences in databases, beats analyzed, frequency ranges, and signal processing techniques.
Does the Shannon energy application on a bandpass filter improve R-peak detection performance compared to the Stockwell transform method in ECG data?
Does the Shannon energy application on a bandpass filter improve R-peak detection performance compared to the Stockwell transform method in ECG data?
Absolute Event Rate: 99.52% vs 99.33%
Shannon energy application using a bandpass filter provides slightly better sensitivity, positive predictivity, and accuracy for ECG R-peak detection compared to the Stockwell transform method.
Standardized evaluation needed for Shannon energy R-peak detectors; leaves open optimal method for clinical ECG use.
Shannon energy-based algorithm has been implemented in peak detection method of various physiological signals including electrocardiogram, which is used to enhance significant peaks for accurate peak detection. Two significant methods of R-peak detection that apply Shannon energy are identified. However, direct comparison cannot be made due to the differences in database used, number of beat analysed, frequency range selected, and signal processing technique applied. This paper aimed to properly evaluate the performance of Shannon energy-based algorithms for R-peak detection on two methods of bandpass filter and Stockwell transform. Simple enveloping technique using moving average filter is proposed, and a threshold is set to localize R-peak at a selected frequency range of 7-15 Hz. Performance of both methods were then evaluated using all 48 data from MIT-BIH Arrhythmia database. Result showed that both methods are equivalently useful in reducing P and T waves interference and produced similar output of Shannon energy envelope. However, Shannon energy application on bandpass filter offered 99.71% sensitivity, 99.80% positive predictivity and 99.52% accuracy, slightly better than that of the Stockwell transform method that only produced 99.65% sensitivity, 99.68% positive predictivity and 99.33% accuracy.
No takes yet. Share an insight, caveat, or question.
Suboh et al. (2020) studied ECG R-peak detection (n=48). Shannon energy application on bandpass filter vs. Stockwell transform method was evaluated on Accuracy of R-peak detection. Shannon energy application on a bandpass filter achieved 99.52% accuracy for ECG R-peak detection, slightly outperforming the Stockwell transform method (99.33% accuracy).
Synapse has enriched 4 closely related papers on similar clinical questions. Consider them for comparative context: