ECG features extraction using second-order dynamic system and regeneration using hybrid recurrent network
ECG signals show the heart's condition for each individual. ECG signal's characteristic can be extracted by using several methods such as P-wave conditions, RR-interval, fast-Fourier transform, wavelet transform, and etc. This study shows the relationship between features extraction of ECG...
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| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2016
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/72959/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85006931086&doi=10.1109%2fICSPCC.2016.7753648&partnerID=40&md5=da67d8c342ab8f0ff339cc77eeab11dd |
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| Summary: | ECG signals show the heart's condition for each individual. ECG signal's characteristic can be extracted by using several methods such as P-wave conditions, RR-interval, fast-Fourier transform, wavelet transform, and etc. This study shows the relationship between features extraction of ECG signals by using second-order dynamic system (SODS) technique and ECG signals regeneration by using hybrid-recurrent network (HRN). HRN technique describes the mathematical proof of the algorithms used in SODS. The algorithm was developed by using Matlab software platform. Comparison was made and it was found that the ECG features extracted from SODS can be used to regenerate the ECG signals based on HRN technique. Therefore, the features extracted from SODS were valid to be used for further analysis of ECG signals. |
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