Biomedical subjects

C Berthomier

Publications and source records attributed to C Berthomier.

3 recordsLinked to original sources

PubMed2001

Multigate doppler signal analysis using 3-D regularized long AR modelling.

Autoregressive (AR) modelling has already been proposed as an alternative to fast Fourier transform to process ultrasound (US) Doppler signals. Previous works introduced long AR models, set up under a regularization framework. The latter may be in 1-D (frequency) or 2-D (frequency and space or time). This study generalizes the spectrum regularization in the three dimensions frequency, space and time. The problem of the penalization function is addressed, and a new convex solution is proposed, taking into account possible nonstationarity of the Doppler signal. The parameter tuning is based on simulations using a standard Doppler signal model. The first results show that this processing improves the spectral estimation, and is well suited to flow interpretation.

Algorithms↗

PubMed1999

Automatic sleep EEG analysis using filter banks.

Filter banks analysis is an easy and quick computing way to implement time-scale methods, these being well suited for short events as well as for large waveforms detection tasks. We propose a non-uniform oversampled filter banks to analyze sleep EEG single channel signal, the different subbands matching the classical EEG rhythms. In order to preserve the temporal shapes information, filter banks are oversampled. Coupling the informations conveyed by the different outputs allow to perform an automatic hypnogram.

Adult↗

PubMed1997

EEG analysis using non-uniform oversampled filter banks.

Time-frequency or time-scale methods are well suited for short events as well as for large waveforms detection tasks. Filter banks analysis is an easy and quick computing way to implement these methods. We propose a non-uniform oversampled filter banks to analyze EEG single channel signal, the different subbands matching the classical EEG rhythms. We use oversampled filter banks to preserve the temporal shapes information. In order to illustrate this method, we show different spindle temporal structures as also their meaning in terms of sleep stage detection.

Adult↗