| Abstract [eng] |
New algorithms for monitoring the relationships between electrocardiography (ECG) parameters, dynamic processes, and complex human body systems under changing environmental conditions (physical load, local geomagnetic field, vagus nerve stimulation) are presented in this dissertation. Algorithms of algebraic analysis based on matrices of differences of analyzed processes are used for the evaluation of dynamic ECG signal relationships. The main objective of the dissertation is to investigate the applicability of existing nonlinear methodologies, to propose new algorithms, and use them to monitor the dynamics of ECG relationships. Information reduction methodologies and algorithms for optimal reconstruction of attractors into the delay phase planes are developed and applied. In addition, algorithms and methodologies for monitoring cardiac parameters, their relationships to the local magnetic field, and to the vagus nerve stimulation are developed. It is demonstrated that algorithms for visualizing the relationships of ECG parameters developed during the investigation can be applied to determine pathological conditions of the cardiovascular system. The developed methodologies can be used to monitor and assess human health. |
