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DETECTION OF THE R-WAVE IN ECG SIGNALS
- Date Issued:
- 2005
- Abstract/Description:
- 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.
Title: | DETECTION OF THE R-WAVE IN ECG SIGNALS. |
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16 downloads |
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Name(s): |
Valluri, Sasanka, Author Weeks, Arthur, Committee Chair University of Central Florida, Degree Grantor |
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Type of Resource: | text | |
Date Issued: | 2005 | |
Publisher: | University of Central Florida | |
Language(s): | English | |
Abstract/Description: | 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. | |
Identifier: | CFE0000498 (IID), ucf:46369 (fedora) | |
Note(s): |
2005-05-01 M.S. Engineering and Computer Science, Department of Electrical and Computer Engineering Masters This record was generated from author submitted information. |
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Subject(s): |
ecg wavelets pvc adaptive threshold |
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Persistent Link to This Record: | http://purl.flvc.org/ucf/fd/CFE0000498 | |
Restrictions on Access: | campus 2015-01-31 | |
Host Institution: | UCF |