Less computational approach to detect QRS complexes in ECG rhythms
| dc.contributor.author | Younes, Tariq M. | |
| dc.contributor.author | Alkhedher, Mohammad | |
| dc.contributor.author | Al Khawaldeh, Mohamad | |
| dc.contributor.author | ETAL.. | |
| dc.date.accessioned | 2022-02-24T10:21:14Z | |
| dc.date.accessioned | 2023-08-19T08:17:34Z | |
| dc.date.available | 2022-02-24T10:21:14Z | |
| dc.date.available | 2023-08-19T08:17:34Z | |
| dc.date.issued | 2021 | |
| dc.description | Nowadays, 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.abstract | Electrocardiogram (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.citation | Younes, 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.doi | https://doi.org/10.11591/csit.v2i3.p113-120 | |
| dc.identifier.uri | https://edms.wexl.in/handle/1/2768 | |
| dc.language.iso | en | en_US |
| dc.publisher | Institute of Advanced Engineering and Science | en_US |
| dc.subject | Automatic recognition | en_US |
| dc.subject | ECG | en_US |
| dc.subject | Noise removal | en_US |
| dc.subject | QRS detection | en_US |
| dc.subject | Signal processing | en_US |
| dc.title | Less computational approach to detect QRS complexes in ECG rhythms | en_US |
| dc.title.alternative | Journal article | en_US |
| dc.type | Article | en_US |
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