Author, Institution: Andrius Sološėnko, Kaunas University of Technology
Science Area, Field of Science: Technological Sciences, Electrical and Electronic Engineering – 01T
Scientific supervisor: Prof. Dr. Vaidotas Marozas (Kaunas University of Technology, Technological Sciences, Electrical and Electronic Engineering 01T).
Dissertation Defence Board of Electrical and Electronic Engineering Science Field:
Assoc. Prof. Dr. Elena Jasiūnienė (Kaunas University of Technology, Technological Sciences, Electrical and Electronic Engineering 01T) – chairperson,
Prof. Dr. Habil. Audrius Aidietis (Vilniaus University, Biomedical Sciences, Medicine – 06B),
Prof. Dr. Raquel Bailon (University of Saragosa, Technological Sciences, Electrical and Electronic Engineering – 01T),
Prof. Dr. Arminas Ragauskas (Kaunas University of Technology, Technological Sciences, Electrical and Electronic Engineering – 01T),
Prof. Dr. Saulius Šatkauskas (Vytautas Magnus University, Biomedical Sciences, Biophysics – 02B).
The doctoral dissertation is available at the library of Kaunas University of Technology (K. Donelaičio g. 20,Kaunas)
Annotation:
Cardiac arrhythmia is usually detected by using ECG, however it requires at least several electrodes attached to the body which is uncomfortable, especially during prolonged monitoring, e.g., day or more. In this thesis, a problem of cardiac arrhythmia, i.e., premature ventricular contractions (PVC) and atrial fibrillation (AF) detection by using photoplethysmogram (PPG) signals as an alternative to ECG is solved. Recording of PPG signals requires only a single electrode attached, e.g., to wrist, however PPG signals are susceptible to movement-induced noises (artifacts), which may cause false alarms. In order to address this problem following objectives were set: 1) to analyze existing methods for arrhythmia monitoring and bio-signal processing, 2) to develop and investigate PPG model capable of simulating various types of arrhythmia, 3) to develop and investigate method for the detection of PVC, 4) to develop and investigate methods for the detection of AF. Results of the research shows that: 1) currently the only PPG model of its kinds capable of simulating signals with various types of arrhythmia by using only the rhythm-based information was developed. The morphology of simulated PPGs corresponds to that of real signals. The model is intended for development and testing of the PPG-based arrhythmia detection methods, 2) a robust PPG-based PVC and bigeminy detection method employing heart-rhythm analysis, artifact detection and artificial neural network was developed, 3) a robust PPG-based AF detection method combining AF detection with PPG signal quality assessment, allowing to achieve high specificity even during low signal to noise ratios, was developed.
