| Title |
Physiological signal processing algorithms for short-term heart rate and blood pressure variability estimation / |
| Translation of Title |
Fiziologinių signalų apdorojimo algoritmai trumpalaikiam širdies ritmo ir kraujo spaudimo variabilumui vertinti. |
| Authors |
Rapalis, Andrius |
| Full Text |
|
| Pages |
133 |
| Keywords [eng] |
heart rate variability ; blood pressure variability ; physiological signal processing ; monitoring |
| Abstract [eng] |
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. |
| Dissertation Institution |
Kauno technologijos universitetas. |
| Type |
Doctoral thesis |
| Language |
English |
| Publication date |
2017 |
