Caractérisation de la variabilité du rythme cardiaque par des méthodes hybrides

Abstract

The cardiovascular signals are, in general, quasi-periodic, repeated at each cardiac cycle with a period that is not strictly constant and also their amplitudes can vary from one cycle to another. These variations are due to the action of the autonomic nervous system (ANS). In other words, these changes allow us to draw useful information about everything controlled by the ANS such as the physiological or pathological condition of an individual, in a non-invasive way. The purpose behind this thesis has been divided in three phases i) proposed a solution to the non-stationary problem of Herat Rate Variability (HRV) signals, ii) Study of a human physiological problem, trying to find a link between this problem and the features of HRV and iii) detection of a pathological problem using the HRV signal. As results, we have proposed a simple and effective solution to the non-stationary problem and also to estimate the duration of the sympathetic and parasympathetic ANS behaviours as well as their location in time. For the physiological study, a hybrid method was proposed to study the evolution of the HRV characteristics during a stressful experience, and some HRV features were found strongly linked to stress. This study can help to connect the ANS behaviour to the corresponding stress situations. Finally, for pathological study, a new approach based on Alpha integration was presented to make an automatic detection of arousalin patients suffering from sleep apnoea, a new optimality criterion was introduced. The proposed algorithm was tested on four real signals in order to validate its effectiveness. Theresults of our algorithm were compared to another study on the same data, our method has provided very good results.