Extraction Of Fetal Electrocardiogram Using An Adaptive Neuro- Fuzzy System
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Date
2014-01
Authors
Alamu, Femi
Journal Title
Journal ISSN
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Publisher
Network and Complex Systems www.iiste.org
Abstract
In this paper, adaptive neuro fuzzy inference system (ANFIS) was used for the cancellation of maternal
electrocardiogram (MECG) in fetal electrocardiogram extraction (FECG) from the composite abdominal
electrocardiogram (AECG). This technique is used to estimate the MECG present in the abdominal signal of a
pregnant woman. The FECG is then extracted by subtracting the estimated MECG from the abdominal signal.
In the furtherance of extraction, MATLAB (version 7.6) was used to code the system in order to
generate the maternal heartbeat signal and the fetal heartbeat signal which were added to form the measured
signal. For the fetal heartbeat signal to be recovered from the interference (maternal heartbeat) signal, a reference
signal (which is a clean version of the original maternal heartbeat signal) was introduced in the system. It is this
signal that cancelled the maternal heartbeat signal in the measured signal, thereby leaving the fetal heartbeat
signal as an error signal.
However, though the recovered signal still contained some traces of the maternal heartbeat signal,
performance of the soft computing technique applied is in terms of the capability of adaptive neuro fuzzy
inference system in removing the overlapping between the MECG and the FECG signals. The results obtained
show that this method is a simple and powerful means for the extraction of Fetal Electrocardiogram.
Description
Keywords
Fetal Electrocardiogram Extraction (FECG), Neuro-fuzzy system, Noise Cancellation