TrustUs: Fetal electrocardiogram multi-channel analysis

Electronic fetal monitoring (EFM) is a widely used practice in ensuing the health and safety of the fetus during pregnancy, especially during labor. Existing EFM techniques such as cardiotocography and doppler monitoring allow doctors to detect, analyze and diagnose the heartbeat of the fetus to det...

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Main Authors: Adriano, Carlo D.C., Bihis, Raphael Emmanuel B., Bringas, Jaimie Lou A., Hong, Charisse B.
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Language:English
Published: Animo Repository 2016
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Online Access:https://animorepository.dlsu.edu.ph/etd_bachelors/7645
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Institution: De La Salle University
Language: English
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spelling oai:animorepository.dlsu.edu.ph:etd_bachelors-82902022-05-24T02:35:29Z TrustUs: Fetal electrocardiogram multi-channel analysis Adriano, Carlo D.C. Bihis, Raphael Emmanuel B. Bringas, Jaimie Lou A. Hong, Charisse B. Electronic fetal monitoring (EFM) is a widely used practice in ensuing the health and safety of the fetus during pregnancy, especially during labor. Existing EFM techniques such as cardiotocography and doppler monitoring allow doctors to detect, analyze and diagnose the heartbeat of the fetus to determine its condition. Using information provided by EFM, a doctor is able to identify if the fetus is in distress and recommend when an emergency ceasarian section is required. These techniques however can only provide fetal heart rate (FHR). Other methods such as fetal electrocardiogram (FECG) overcome this limitation by providing more information not limited to FHR. As stable FECG can be obtained upon reaching 8 months of gestational age, it may be possible to use this in obtaining information that indicate the fetal condition. This study proposes a fetal ECG extraction method from an AECG sample that reduces noise by a series of digital filters. The signal undergoes wavelet decomposition to eliminate baseline wander by utilizing Coiflet 5. Powerline noise removal is accomplished by using comb notch filter with the order of 20. Based on the results, a comb notch filter yields better results that a regular notch fitler. Other noise components are attenuated by using a Chebyshev Type II low pass filter that attenuates frequencies above 80 Hz. FECG is extracted by subtracting a synthetic MECG from the AECG by using a template matching algorithm. The resulting FECG is analyzed by the design system for feature extraction and is usable for further studies. 2016-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/etd_bachelors/7645 Bachelor's Theses English Animo Repository Fetal heart rate monitoring Fetal monitoring
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
topic Fetal heart rate monitoring
Fetal monitoring
spellingShingle Fetal heart rate monitoring
Fetal monitoring
Adriano, Carlo D.C.
Bihis, Raphael Emmanuel B.
Bringas, Jaimie Lou A.
Hong, Charisse B.
TrustUs: Fetal electrocardiogram multi-channel analysis
description Electronic fetal monitoring (EFM) is a widely used practice in ensuing the health and safety of the fetus during pregnancy, especially during labor. Existing EFM techniques such as cardiotocography and doppler monitoring allow doctors to detect, analyze and diagnose the heartbeat of the fetus to determine its condition. Using information provided by EFM, a doctor is able to identify if the fetus is in distress and recommend when an emergency ceasarian section is required. These techniques however can only provide fetal heart rate (FHR). Other methods such as fetal electrocardiogram (FECG) overcome this limitation by providing more information not limited to FHR. As stable FECG can be obtained upon reaching 8 months of gestational age, it may be possible to use this in obtaining information that indicate the fetal condition. This study proposes a fetal ECG extraction method from an AECG sample that reduces noise by a series of digital filters. The signal undergoes wavelet decomposition to eliminate baseline wander by utilizing Coiflet 5. Powerline noise removal is accomplished by using comb notch filter with the order of 20. Based on the results, a comb notch filter yields better results that a regular notch fitler. Other noise components are attenuated by using a Chebyshev Type II low pass filter that attenuates frequencies above 80 Hz. FECG is extracted by subtracting a synthetic MECG from the AECG by using a template matching algorithm. The resulting FECG is analyzed by the design system for feature extraction and is usable for further studies.
format text
author Adriano, Carlo D.C.
Bihis, Raphael Emmanuel B.
Bringas, Jaimie Lou A.
Hong, Charisse B.
author_facet Adriano, Carlo D.C.
Bihis, Raphael Emmanuel B.
Bringas, Jaimie Lou A.
Hong, Charisse B.
author_sort Adriano, Carlo D.C.
title TrustUs: Fetal electrocardiogram multi-channel analysis
title_short TrustUs: Fetal electrocardiogram multi-channel analysis
title_full TrustUs: Fetal electrocardiogram multi-channel analysis
title_fullStr TrustUs: Fetal electrocardiogram multi-channel analysis
title_full_unstemmed TrustUs: Fetal electrocardiogram multi-channel analysis
title_sort trustus: fetal electrocardiogram multi-channel analysis
publisher Animo Repository
publishDate 2016
url https://animorepository.dlsu.edu.ph/etd_bachelors/7645
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