Real-Time QRS Detector Using Stationary Wavelet Transform for Automated ECG Analysis

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dc.contributor.ORCID0000-0003-4523-9376 (Tamil, L)
dc.contributor.authorKalidas, Vignesh
dc.contributor.authorTamil, Lakshman
dc.contributor.utdAuthorKalidas, Vignesh
dc.contributor.utdAuthorTamil, Lakshman
dc.date.accessioned2019-08-21T22:09:48Z
dc.date.available2019-08-21T22:09:48Z
dc.date.created2017-10
dc.descriptionFull text access from Treasures at UT Dallas is restricted to current UTD affiliates (use the provided Link to Article).
dc.description.abstractIn this paper, we propose an online QRS detector algorithm using Stationary Wavelet Transforms (SWT) for real time beat detection from single-lead electrocardiogram (ECG) signals. Daubechies 3 (â€db3’) wavelet is chosen as the mother wavelet for SWT analysis. The information from the first ten seconds of the ECG signal is used as a learning template by the algorithm to initialize thresholds for beat detection. These thresholds are then modified every three seconds, thereby quickly adapting to changes in heart rate and signal quality. Hence false beat detections are vastly suppressed in this approach, while identifying true beats with a high degree of accuracy. Our algorithm yields a sensitivity (SE) of 99.88% and a positive predictive value (PPV) of 99.84% on the MIT-BIH Arrhythmia Database, SE of 99.80% and PPV of 99.91% on the AHA database and an SE of 99.97% and PPV of 99.90% on the QT database.
dc.description.departmentErik Jonsson School of Engineering and Computer Science
dc.identifier.bibliographicCitationKalidas, V., and L. Tamil. 2017. "Real-time QRS detector using stationary wavelet transform for automated ECG analysis." Proceedings - International Conference on Bioinformatics and Bioengineering, 17th: 457-461, doi:10.1109/BIBE.2017.00-12
dc.identifier.issn9781538613245
dc.identifier.urihttps://hdl.handle.net/10735.1/6786
dc.identifier.volume2017
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.isPartOfProceedings - International Conference on Bioinformatics and Bioengineering, 17th
dc.relation.urihttp://dx.doi.org/10.1109/BIBE.2017.00-12
dc.rights©2017 IEEE
dc.subjectElectrocardiography
dc.subjectWavelets (Mathematics)--Data processing
dc.subjectBioinformatics
dc.subjectDatabases
dc.subjectTransformations (Mathematics)
dc.titleReal-Time QRS Detector Using Stationary Wavelet Transform for Automated ECG Analysis
dc.type.genrearticle

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