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","Master of Science (M.S.)","College of Engineering and Computer Science","Electrical and Computer Engineering","Electrical Engineering"]},{"key":"dc:description.abstract","label":"Abstract","values":["This thesis aims at providing a new approach for detecting R-waves in the ECG signal and generating the corresponding R-wave impulses with the delay between the original R-waves and the R-wave impulses being lesser than 100 ms. The algorithm was implemented in Matlab and tested with good results against 90 different ECG recordings from the MIT-BIH database. The Discrete Wavelet Transform (DWT) forms the heart of the algorithm providing a multi-resolution analysis of the ECG signal. The wavelet transform decomposes the ECG signal into frequency scales where the ECG characteristic waveforms are indicated by zero crossings. The adaptive threshold algorithms discussed in this thesis search for valid zero crossings which characterize the R-waves and also remove the Preventricular Contractions (PVC's). The adaptive threshold algorithms allow the decision thresholds to adjust for signal quality changes and eliminate the need for manual adjustments when changing from patient to patient. The delay between the R-waves in the original ECG signal and the R-wave impulses obtained from the algorithm was found to be less than 100 ms."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Detection Of The R-wave In Ecg Signals"]}]}],"canonical_facts":{"dc:contributor":["Weeks, Arthur"],"dc:creator":["Valluri, Sasanka"],"dc:description":["If this is your thesis or dissertation, and want to learn how to access it or for more information about readership statistics, contact us at STARS@ucf.edu
","Master of Science (M.S.)","College of Engineering and Computer Science","Electrical and Computer Engineering","Electrical Engineering"],"dc:description.abstract":["This thesis aims at providing a new approach for detecting R-waves in the ECG signal and generating the corresponding R-wave impulses with the delay between the original R-waves and the R-wave impulses being lesser than 100 ms. The algorithm was implemented in Matlab and tested with good results against 90 different ECG recordings from the MIT-BIH database. The Discrete Wavelet Transform (DWT) forms the heart of the algorithm providing a multi-resolution analysis of the ECG signal. The wavelet transform decomposes the ECG signal into frequency scales where the ECG characteristic waveforms are indicated by zero crossings. The adaptive threshold algorithms discussed in this thesis search for valid zero crossings which characterize the R-waves and also remove the Preventricular Contractions (PVC's). The adaptive threshold algorithms allow the decision thresholds to adjust for signal quality changes and eliminate the need for manual adjustments when changing from patient to patient. The delay between the R-waves in the original ECG signal and the R-wave impulses obtained from the algorithm was found to be less than 100 ms."],"dc:format":["application/pdf"],"dc:identifier":["CFE0000498"],"dc:identifier.uri":["https://stars.library.ucf.edu/etd/407"],"dc:language":["English"],"dc:subject":["ecg","wavelets","pvc","adaptive threshold","Electrical and Computer Engineering","Electrical and Electronics","Engineering"],"dc:title":["Detection Of The R-wave In Ecg Signals"],"dc:type":["Masters Thesis (Open Access)"]},"updated_at":"2026-07-24T05:08:39Z"}