Development of Telemedicine applications on Smartphones

This thesis is a part of the general development framework for embedded applications in telemedicine.We started with a thorough study of the ECG signal through a full analysis of QRSTA (QRS-T-area) parameter of this signal. This study led to the development of our first application "DIAGNOSE ECG", embedded on a smartphone, for the determination of the QRSTA parameter, which is considered as an indicator of sudden death. Then, we studied the hemodynamic cardiorespiratory interactions in order to analyze their impact on sleep apnea and the condition of the drivers. In this context, we have contributed on the development of a multi-varied causal model, based on Granger's causality analysis between respiratory, hemodynamic and cardiac signals. Finally, we developed a new approach of analyzing physiological signal based on panel co-integration approach, allowing short- and long-term quantification using FM-OLS and DOLS estimators.