An Investigation of Dynamic Features Influence in ECG-Apnea Using Detrended Fluctuation Analysis

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dc.contributor.advisorPurnomo, Mauridhi Hery
dc.contributor.authorFahruzi, Iman
dc.contributor.authorPurnama, I Ketut Eddy
dc.contributor.authorPurnama, Mauridhi Hery
dc.date.accessioned2023-06-12T14:40:55Z
dc.date.available2023-06-12T14:40:55Z
dc.date.issued2018-10-18
dc.descriptionInternational Proceeding ICoIAS 2018 Singaporeen_US
dc.description.abstrakHeart Rate Variability(HRV), which can be defined merely as an investigation of the deviation in a time interval of RR between successive cardiac beats(recordings consist of 21326 normal beats event and 6899 apnea beats event) in time duration about 20 minutes ECG-Apnea signal. An Electrocardiogram(ECG), which more information dynamic features, can generate from the extraction process. This paper presents a feature extraction technique in HRV where ECG signal extraction is considered essential to obtain statistical and geometrical HRV for each recording. Dynamic features derived from ECG using two components, HRV analysis, and DFA, were deeply examined and validated its effectiveness to distinguish apnea from the normal signal. Before commencing feature extraction, the ECG signal which is still contaminated by noise needs to be eliminated using pre-processing in the form of noise suppression, and baseline wander removing. Experiment results indicate that suitable for recognizing detail extraction of ECG-Normal and ECG-Apnea events.en_US
dc.identifier.isbn978-1-5386-6331-8
dc.identifier.urihttps://repository.polibatam.ac.id/xmlui/handle/123456789/1689
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjecthrven_US
dc.subjectdynamic featureen_US
dc.subjectapneaen_US
dc.subjectecgen_US
dc.subjectdfaen_US
dc.titleAn Investigation of Dynamic Features Influence in ECG-Apnea Using Detrended Fluctuation Analysisen_US
dc.typeArticleen_US

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