Fetal electrocardiogram extraction and R-peak detection for fetal heart rate monitoring using artificial neural network and correlation
Conventional techniques are often unable to achieve the Fetal Electrocardiogram FECG extraction and Rpeak detection in FECG from the abdominal ECG (AECG) in satisfactorily level for Fetal Heart Rate (FHR) monitoring. A new methodology by combining the Artificial Neural Network (ANN) and Corr...
| Main Authors: | , , |
|---|---|
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2011
|
| Subjects: | |
| Online Access: | http://irep.iium.edu.my/6473/ http://irep.iium.edu.my/6473/ http://irep.iium.edu.my/6473/ http://irep.iium.edu.my/6473/1/Fetal_electrocardiogram_extraction_and_R-peak_detection_for_fetal_heart_rate_monitoring_using_artificial_neural_network_and_Correlation.pdf |
| Summary: | Conventional techniques are often unable to
achieve the Fetal Electrocardiogram FECG extraction and Rpeak detection in FECG from the abdominal ECG (AECG) in
satisfactorily level for Fetal Heart Rate (FHR) monitoring. A
new methodology by combining the Artificial Neural Network
(ANN) and Correlation approach has been proposed in this
paper. Artificial Neural Network is chosen primarily since it is
adaptive to the nonlinear and time-varying features of the ECG
signal. The supervised multilayer perception (MLP) network
has been used because it requires a desired output in order to
learn. Similarly, the Correlation method has been chosen as the
correlation factor can be used to scale the MECG when
subtracting it from the AECG, in order to get the FECG. By
combining these two approaches the proposed methodology
gives better and efficient result in terms of accuracy for FECG
extraction and R-peak detection in the AECG signal due to its
above characteristics. The proposed approach involves the
FECG extraction from the AECG signal with the accuracy of
100% and R-peak detection performance is 93.75%, even
though the overlapping situation of MECG and FECG signal in
the AECG signal. Therefore the physician and clinician can
make the correct decision for the well-being status of the fetus
and mother during the pregnancy period. |
|---|