Application the intelligent Neural Network to Design the Novel Blood Pressure Monitor
碩士 === 崑山科技大學 === 電子工程研究所 === 99 === Various physiological parameters have been widely used for diseases, prevention and detection, which can observe the occurrence of cardiovascular diseases, through daily measurement of blood pressure. Currently, the most common blood pressure measurement method r...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2011
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| Online Access: | http://ndltd.ncl.edu.tw/handle/50294392061270283000 |
| Summary: | 碩士 === 崑山科技大學 === 電子工程研究所 === 99 === Various physiological parameters have been widely used for diseases, prevention and detection, which can observe the occurrence of cardiovascular diseases, through daily measurement of blood pressure. Currently, the most common blood pressure measurement method records the pressure on the wrist. The subject might feel uncomfortable and tension of pressure on the arm that it might lead to the measurement error of blood pressure. Electrocardiogram (ECG) represents the electrical activities of the heart functions, which also contains blood pressure-related information. This research in an attempt to extract the related features of blood pressure from the ECG signal. This research developed a new non-invasive blood pressure measurement technology that utilizes the intelligent neural network algorithms to calculate the blood pressure value from the parameters of ECG. The designed blood pressure measurement approach is called the ECG-blood pressure machine. The proposed approach alleviates the errors caused by discomfort, which can provide a feasibility to continuously monitor blood pressure in a less stressful condition.
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