Denoising of the uterine EHG by an undecimated wavelet transform

The authors propose two original methods of denoising of the uterine electrohysterography (EHG) signal by wavelets. This external electrophysiological signal is corrupted by electronic, electromagnetic noises and by the remaining electrocardiogram of the mother. The interfering signals have overlapp...

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Bibliographic Details
Published in:IEEE transactions on biomedical engineering 1998-09, Vol.45 (9), p.1104-1113
Main Authors: Carre, P., Leman, H., Fernandez, C., Marque, C.
Format: Article
Language:English
Subjects:
Abdomen
Algorithms
Biological and medical sciences
Biomedical measurements
Electrodiagnosis. Electric activity recording
Electromagnetic interference
Electromyography - methods
Electrophysiology
Engineering Sciences
Female
Filtering
Filters
Fourier Analysis
Humans
Interference suppression
Investigative techniques, diagnostic techniques (general aspects)
Male
Medical sciences
Miscellaneous. Technology
Monitoring
Monitoring, Physiologic
Noise reduction
Pregnancy
Pregnancy - physiology
Signal and Image processing
Signal filtering and prediction
Signal processing
Signal Processing, Computer-Assisted
Spurious signal noise
Uterine Contraction - physiology
Wavelet transforms
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Summary:The authors propose two original methods of denoising of the uterine electrohysterography (EHG) signal by wavelets. This external electrophysiological signal is corrupted by electronic, electromagnetic noises and by the remaining electrocardiogram of the mother. The interfering signals have overlapping spectra. Therefore, a classical filtering is unusable. Wavelets should be a very well-suited denoising tool. The first proposed method uses the algorithm "a trou" with nonsymmetrical filters. The computation is rapid and the results are satisfying compared to the classical denoising techniques. The second algorithm is an improvement of the first method. It uses orthogonal wavelets and the result of the thresholding corresponds to the average of all circulant shifts denoised by a decimated wavelet transform. Results are compared to traditional denoising algorithms by wavelet (orthogonal, maximally decimated). The proposed algorithms are more efficient on simulated signals as well as on uterine EHG.
ISSN:0018-9294
1558-2531
DOI:10.1109/10.709554