Data fusion of electrophysiological and haemodynamic signals for ventricular rhythm tracking.
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Critical Care↗
Biomedical subjects
G Carrault
Publications and source records attributed to G Carrault.
Surface electromyogram automatic analysis and Guillain-Barré syndrome follow up.
An automatic and quantitative framework for the analysis of surface EMG interference patterns at maximal non-controlled force is described. The main contents are focused on different ways to represent surface EMG signals and to analyse collected data set through principal component analysis. The methods are tested on control individuals and on patients with Guillain-Barré Syndrome examined at different moments after the beginning of the disease (first week, three months, and one year). The results exhibit that a high diagnostic yield can be provided and furthermore that quantification and differentiation can be expected. Surface EMG interference pattern may be hoped to be a useful tool in daily practice.
Adult↗
Segmentation of depth-EEG seizure signals: method based on a physiological parameter and comparative study.
The analysis of stereoelectroencephalographic (intracerebral recording) signals provides information on the electrical activity of brain structures implied in epileptic seizures. A simple nonparametric adaptive segmentation method, based on a physiologically relevant parameter, is presented and compared with three methods reported in the literature. The comparative frame allows us to objectively test methods for their performances on the same basis. Results show that the proposed method is robust with respect to the types of change studied and easier to conduct, even if it is less accurate about the estimation of instants of change than another method presented in this study. Signals are segmented throughout the duration of seizures without parameter readjustment and generate instants of change in accordance with those interactively delimited by the clinician.
Algorithms↗