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Developpement et validation d'un instrument non-invasif de caracterisation du comportement musculaire respiratoire

Posted on:2009-05-27Degree:Ph.DType:Thesis
University:Universite de Montreal (Canada)Candidate:Aithocine, EliseFull Text:PDF
GTID:2448390005459308Subject:Engineering
Abstract/Summary:
Better care in an anaesthesia and critical care could be achieved by reducing monitoring duration and improving the quality of recovery. For the particular case of respiratory assistance, the capacity to track and optimize patient-ventilator synchrony is essential to quality care. As a first step, this thesis adresses the development and validation of an instrument which characterizes respiratory behavior by studying the time lag between onset of upper airway muscles and rib cage muscles, cycle by cycle during respiration. This tool must take into account the constraints imposed by the clinical environment; measuring respiratory muscles by surface electromyographic measurements (EMG). Measurement of the onset time lag, cycle by cycle and non invasively, is a true challenge in a critical care clinical environment. Here the approach is two-fold: (i) The development of a tool for events detection. (ii) The definition of an original protocol on healthy subjects. The tool development constitutes a knowledge bases to eventually develop automation of the processes in future work. From a physiological point of view, the influence of respiratory rate on the EMG onset time lag during inspiration has not been studied. Thus we measured this time lag in normocapnia at various respiratory rates imposed by a sound stimulus. Statistically, the instrumental tool can distinguish two physiological situations in this experimental protocol, which confirms its sensitivity.;Keywords: surface electromyographic measure, respiratory muscles, filtering, detection of events, time-scale, structural intensity.;The second step of this thesis is part of an optimization of events detection methods with singularities of interest. The chosen solution is based on structural intensity which computes the "density" of the locations of the modulus maxima of a wavelet representation along various scales in order to identify singularities of an unknown signal. An improvement is proposed by applying Berkner transform which allows maxima linkage to insure accurate localization of landmarks. An application to cancel ECG interference in diaphragmatic EMG without a reference signal is also proposed.
Keywords/Search Tags:EMG, Time lag, Care
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