Less computational approach to detect QRS complexes in ECG rhythms

dc.contributor.authorYounes, Tariq M.
dc.contributor.authorAlkhedher, Mohammad
dc.contributor.authorAl Khawaldeh, Mohamad
dc.contributor.authorETAL..
dc.date.accessioned2022-02-24T10:21:14Z
dc.date.accessioned2023-08-19T08:17:34Z
dc.date.available2022-02-24T10:21:14Z
dc.date.available2023-08-19T08:17:34Z
dc.date.issued2021
dc.descriptionNowadays, one of the most common methods for diagnosis and recognition of cardiovascular diseases is electrocardiography (ECG). The ECG signal is characterized by a set of peaks. In these peaks, the time and amplitude parameters are diagnosed [1]. As a normal practice by cardiologists, the procedure of finding the characteristics of ECG peaks is performed using drawing accessories.en_US
dc.description.abstractElectrocardiogram (ECG) signals are normally affected by artifacts that require manual assessment or use of other reference signals. Currently, Cardiographs are used to achieve basic necessary heart rate monitoring in real conditions. This work aims to study and identify main ECG features, QRS complexes, as one of the steps of a comprehensive ECG signal analysis. The proposed algorithm suggested an automatic recognition of QRS complexes in ECG rhythm. This method is designed based on several filter structure composes low pass, difference and summation filters. The filtered signal is fed to an adaptive threshold function to detect QRS complexes. The algorithm was validated and results were checked with experimental data based on sensitivity test.en_US
dc.identifier.citationYounes, T. M., Alkhedher, M., Al Khawaldeh, M., Nawash, J., & Al-Abbas, I. (2021). Less computational approach to detect QRS complexes in ECG rhythms. Computer Science and Information Technologies, 2(3), 113-120.en_US
dc.identifier.doihttps://doi.org/10.11591/csit.v2i3.p113-120
dc.identifier.urihttps://edms.wexl.in/handle/1/2768
dc.language.isoenen_US
dc.publisherInstitute of Advanced Engineering and Scienceen_US
dc.subjectAutomatic recognitionen_US
dc.subjectECGen_US
dc.subjectNoise removalen_US
dc.subjectQRS detectionen_US
dc.subjectSignal processingen_US
dc.titleLess computational approach to detect QRS complexes in ECG rhythmsen_US
dc.title.alternativeJournal articleen_US
dc.typeArticleen_US

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