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dc.contributor.authorYaqoob, Touseef
dc.contributor.authorAziz, Saira
dc.contributor.authorAhmed, Sajid
dc.contributor.authorAmin, Osama
dc.contributor.authorAlouini, Mohamed-Slim
dc.date.accessioned2020-05-06T08:48:30Z
dc.date.available2020-05-06T08:48:30Z
dc.date.issued2020-04-09
dc.identifier.citationYaqoob, T., Aziz, S., Ahmed, S., Amin, O., & Alouini, M.-S. (2020). Fractional Fourier Transform Based QRS Complex Detection in ECG Signal. ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). doi:10.1109/icassp40776.2020.9052939
dc.identifier.isbn978-1-5090-6632-2
dc.identifier.issn1520-6149
dc.identifier.doi10.1109/ICASSP40776.2020.9052939
dc.identifier.urihttp://hdl.handle.net/10754/662743
dc.description.abstractBy exploiting fractional-Fourier-transform (FrFT), a novel technique for the QRS complex detection is proposed. The application of the FrFT rotates the Electrocardiograph (ECG) signal in the time-frequency plane. We claim this rotation can give simple and effective QRS complex detection even in the presence of versatile artifacts, such as left-bundle-branch-block, right-bundle-branch-block, and negative polarization. In this work, in the first step, the noise and baseline drifts are removed by applying a wavelet transform on the given ECG signal. While, in the next step, the clean ECG signal is passed through the proposed algorithm, which rotates the ECG signal in the time-frequency plane and detects the QRS complex very easily. The proposed algorithm validated over the 48 signals of the MIT-BIH arrhythmia database, and it yielded 26 false-positive and only five false-negatives compared to the 80 and 42, the best result reported so far.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttps://ieeexplore.ieee.org/document/9052939/
dc.relation.urlhttps://ieeexplore.ieee.org/document/9052939/
dc.relation.urlhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9052939
dc.rightsArchived with thanks to IEEE
dc.subjectECG
dc.subjectQRS Complex Detection
dc.subjectMIT-BIH Arrhythmia Database
dc.subjectSensitivity (Se(%))
dc.subjectPositive Predictivity (+Pr)
dc.titleFractional Fourier Transform Based QRS Complex Detection in ECG Signal
dc.typeConference Paper
dc.contributor.departmentCommunication Theory Lab
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.conference.date4-8 May 2020
dc.conference.nameICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
dc.conference.locationBarcelona, Spain
dc.eprint.versionPost-print
dc.contributor.institutionInformation Technology University (ITU),Department of Electrical Engineering,Lahore,Pakistan
kaust.personAmin, Osama
kaust.personAlouini, Mohamed-Slim
dc.date.published-online2020-04-09
dc.date.published-print2020-05


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