V. Šiaučiūnaitė “Application of nonlinear dynamics methods and algorithms in cardiac signal analysis” doctoral dissertation defence

Author, Institution: Vaiva Šiaučiūnaitė, Kaunas University of Technology

Science area, field of science: Natural Sciences, Informatics, N009

Scientific Supervisor: Prof. Hab. Dr. Minvydas Ragulskis (Kaunas University of Technology, Natural Sciences, Informatics, N009)

Scientific Advisor: Prof. Hab. Dr. Alfonsas Vainoras (Lithuanian Health Science University, Biomedicine, Medicine, M001)

Dissertation Defence Board of Informatics Science Field:
Prof. Habil. Dr. Rimantas Barauskas (Kaunas University of Technology, Natural Sciences, Informatics, N009) – chairperson
Prof. Dr. Srecko Gajovic (University of Zagreb, Croatia, Biomedicine, Medicine, M001)
Prof. Dr. Arvydas Martinkėnas (University of Klaipėda, Natural Sciences, Informatics, N009)
Prof. Dr. Daiva Petruševičienė (Lithuanian University of Health Sciences, Biomedicine, Nursing, M005)
Assoc. Prof. Dr. Kristina Poškuvienė (Kaunas University of Technology, Natural Sciences, Informatics, N009)

Dissertation defence meeting will be at M7 Hall at The Campus Library of Kaunas University of Technology (Studentų 48–M7, Kaunas)

The doctoral dissertation is available on the internet and at the library of Kaunas University of Technology (K. Donelaičio g. 20, Kaunas).

Annotation:

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.