Blood Pressure Variation Trend Analysis Based on Model Study
| Autor: | Hao-Jen Ting, 丁浩恁 |
|---|---|
| Rok vydání: | 2018 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 106 Blood pressure variability is an important risk factor of stroke and cardiovascular diseases, but people often ignored it because of the inconvenient of continuous blood pressure measurement. For the last decade people use ambulatory blood pressure measurement to estimate the trend of blood pressure curve, but this method need to set a cuff around the upper arm and fully occluding the arm’s blood circulation during the recording period, makes people feel uncomfortable and affects the quality of sleep. Nowadays an innovative method can estimate blood pressure using electrocardiogram(ECG) and photoplethysmopraphy(PPG). The time delay between R peak and PPG feature point is reversely related to blood pressure. This is a potential method to improve comfort during measurement and the sensor can be design as a wearable device. This study collects ten patient’s data from the MIMIC II database including ECG, PPG and arterial blood pressure to verify the blood pressure estimate result. We build up several blood pressure regression models with PAT as key parameter, and heart rate, interval of pulse and pulse width as minor parameter, and calculate the feature using difference widow length average (10s, 30s and 60s). The 60s widow length give the best result in both correlation and recurrence quantification analysis. The correlation coefficient is 0.66 and the recurrence rate ratio is 0.51 when only estimate the blood with key parameter PAT, and the correlation coefficient and recurrence rate ratio becomes 0.84 and 0.69 after adding minor parameter into the blood pressure regression model. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
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