Accession Number:

ADA411564

Title:

Denoising EMG and EEG for Monitoring Small Animal Models During NMR Experiments

Descriptive Note:

Conference paper

Corporate Author:

UNIVERSITE DE TECHNOLOGIE DE COMPIEGNE (FRANCE)

Report Date:

2001-10-25

Pagination or Media Count:

5.0

Abstract:

The present growing field of molecular imaging, including multimodality microimaging techniques and spectroscopic approaches, is mainly based on small animal studies. Monitoring such models requires an efficient treatment and use of electrophysiological signals which may be spoiled by environmental effects especially when working with nuclear magnetic resonance NMR since radiofrequency RF pulses and magnetic field gradient commutations may create spurious supplementary signals. In this work, a method is given for FEG and EMG denoising of signals acquired during phosphorous magnetic resonance MR brain spectroscopy data acquisition on a rat model developed for sleepawake studies. The proposed approach is based on wavelet decomposition and the key method is to turn into profit the shape variations of EMG during the time course of sleepawake cycles. Statistical properties of the noise are studied using EMG recorded during paradoxical sleep as noise model. A specific estimation of noise level using FMG recorded during slow sleep leads to an optimal wavelet coefficients thresholding. This approach is well suited to improve signal to noise ratio of EFG and EMG and to preserve small amplitude electrophysiological signals.

Subject Categories:

  • Medicine and Medical Research
  • Theoretical Mathematics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE