Author, Institution: Andrius Rapalis, Kaunas University of Technology
Science Area, Field of Science: Technological Sciences, Electrical and Electronic Engineering – 01T
Scientific Supervisor: Dr. Artūras Janušauskas (Kaunas University of Technology, Technological Sciences, Electrical and Electronics Engineering – 01T).
Dissertation Defence Board of Energetics and Power Engineering Science Field:
Prof. Dr. Arminas Ragauskas (Kaunas University of Technology, Technological Sciences, Electrical and Electronic Engineering – 01T) – chairman,
Prof. Dr. Eugenijus Kaniušas (Vienna University of Technology, Technological Sciences, Electrical and Electronic Engineering – 01T),
Prof. Dr. Algimantas Kriščiukaitis (Lithuanian University of Health Sciences, Biomedical Sciences, Biophysics – 02B),
Assoc. Prof. Dr. Raimondas Kubilius (Lithuanian University of Health Sciences, Biomedical Sciences, Medicine – 06B),
Prof. Dr. Liudas Mažeika (Kaunas University of Technology, Technological Sciences, Electrical and Electronic Engineering – 01T).
The Doctoral Dissertation is available at the library of Kaunas University of Technology (K. Donelaičio St. 20, Kaunas)
Annotation:
The dissertation covers two scientific-technological problems: 1) the algorithms for estimating the pulse arrival time (PAT) of existing blood volume are unreliable when photoplethysmogram (PPG) signal is noisy; 2) currently there are no methods and algorithms which could evaluate short-term blood pressure (BP) variability from a PPG signal. The changes of heart rate (HR) and blood pressure variability are related to an increased risk of cardiovascular events and may provide important information about individual blood pressure control mechanisms. In this doctoral thesis, the system for short-term heart rate and blood pressure variability estimation was proposed. This system consists of two parts: pulse arrival time estimation algorithm and instantaneous frequencies from PPG signal extraction algorithm. The proposed system and algorithms were tested using synthetic and experimental data. Results showed that: 1) the proposed PAT estimation algorithm shows better accuracy than the classical and diastole-patching PAT estimation algorithms when PPG signal is noisy (signal-to-noise ratios 0–20 dB); 2) the proposed system for short-term HR and BP variability estimation may be used for short-term HR and BP variability estimation during rest and in non-stationary conditions. The system can be used for monitoring short-term BP variability for a long time.
