DocumentCode
2394219
Title
Fetal R-wave detection from multichannel abdominal ECG recordings in low SNR
Author
Kharabian, Shahrzad ; Shamsollahi, Mohammad B. ; Sameni, Reza
Author_Institution
Biomed. Signal & Image Process. Lab. (BiSIPL), Sharif Univ. of Technol., Tehran, Iran
fYear
2009
fDate
3-6 Sept. 2009
Firstpage
344
Lastpage
347
Abstract
Abdominal recordings of fetal ECG (fECG) have lower signal-to-noise ratio (SNR) as compared with invasive procedures. In this paper we have combined two previously proposed methods, one for extracting fECG, called piCA and the other, a transformation based on Hilbert transform to enhance the R-peaks. The combination of these methods seems to work well in situations of noisy data and fetal repositioning. Also a comparison is done by using ICA in order to extract the fetal signals. Performance of both methods is studied separately. Results show that applying the transformation on the components extracted with the use of piCA (after maternal ECG cancellation), had a very good performance. Also, as piCA ranks the components according to their resemblance to maternal ECG, it could be used in automatic fetal ECG extraction algorithms.
Keywords
Hilbert transforms; electrocardiography; feature extraction; independent component analysis; medical signal detection; medical signal processing; obstetrics; source separation; Hilbert transform; ICA; SNR; fetal ECG extraction algorithm; fetal R-wave detection; fetal repositioning; independent component analysis; maternal ECG cancellation; multichannel abdominal ECG recordings; signal-to-noise ratio; source separation; Multichannel Fetal ECG; hilbert transform; periodic component analysis; r-wave detection; Abdomen; Algorithms; Artificial Intelligence; Cardiotocography; Diagnosis, Computer-Assisted; Electrocardiography; Humans; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE
Conference_Location
Minneapolis, MN
ISSN
1557-170X
Print_ISBN
978-1-4244-3296-7
Electronic_ISBN
1557-170X
Type
conf
DOI
10.1109/IEMBS.2009.5333578
Filename
5333578
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