- 學位論文
以非侵入式連續血壓探討周邊血管特性
Investigation of peripheral blood vessel characteristic using non-invasive continuous blood pressure
摘要
就如同心電圖一般，可協助連續血壓訊號進行心臟方面疾病之診斷。在臨床應用上，侵入性血壓量測裝置可提供連續血壓訊號，雖精準卻不可能在一般例行性檢查中進行。非侵入性血壓量測計可應用於一般檢查或居家環境中，卻僅能提供收縮壓與舒張壓兩個特徵值，無法呈現完整血壓訊號的資訊。 本研究建構之系統主要包括血壓校正量測系統、穩定之恆定壓力控制迴路及LabVEIW即時訊號處理程式。以單晶片MSP430為核心，搭配PI(比例-積分)控制器進行電動幫浦電壓調控，將氣囊內壓維持於39~41mmHg之間以進行長時間的連續血壓訊號量測。 本研究針對10位無心血管疾病之正常年輕男女的自願受測者，利用憋氣實驗以改變人體生理狀態，並以自製的非侵入式連續血壓波型量測裝置。於憋氣前、憋氣中與憋氣後量測手臂及手腕兩部位的連續血壓波型訊號，即時推導出周邊血管模型與周邊血管特性之關係，藉此探討正常受測者在周邊血管特性之間的差異性。同時評估系統訊號處理程序的有效率以及準確度。 在每一個連續血壓訊號區段進行特徵值分析之前，會先判斷訊號是否會因電動幫浦的充氣動作或是達到飽和狀態，而導致結果偵測錯誤；因此，血壓有效訊號之評估主要可分為整體有效率、手臂有效率以及手腕有效率，其平均有效率分別為：70.62%、73.88%、94.34%。接著比較在相同的頻率範圍下，手臂及手腕的血壓特徵值之間的相關性；將手臂及手腕原始訊號經過相同的頻率濾波後，以人工的方式來檢查各特徵點之偵測結果是否正確。由結果得知，手臂及手腕訊號在每個對應心搏的血壓特徵之平均偵測率，分別為：90.96%、83.13%及45.87%；另外，訊號經過整體平均處理後的血壓特徵平均偵測率，分別為：99.76%、85.93%及53.12%。在每個對應的心搏或是經過整體平均處理的所有血壓特徵之相關度，並沒有呈現出相同的趨勢變化，因此大部份的相關度均不高；其中，有兩位受測者部份的血壓特徵(血壓振幅及增大指數)分析，則是呈現負相關。 本研究尚有許多值得探討與需要改良的地方，如增大指數(AIx)特徵點P1之偵測方法：雖已有學者提出方法，但實際結果還是會有誤差，若能找出更好的方法，對於增大指數分析是非常受用。
並列摘要
Just like electrocardiogram (ECG), the continual blood pressure signal can assist the diagnosis cardiac diseases. In clinical practice, invasive blood pressure measurement devices provide accurate continual blood pressure signal. However, it can't apply to routine inspection. In ordinary circumstances, noninvasive blood pressure measurement devices must be used. Nevertheless, most of them provide only two value, systolic pressure and diastolic pressure, with on additionally information. The proposed system consists of one blood pressure calibration sub-system、stable constant pressure control mechanism and a LabVIEW real time signal processing program. The system uses the microprocessor (MSP430) to implement proportional-integral (PI) controller and maintain the pressure in the cuff between 39-41mmHg such that continuous blood pressure measurement is possible. Ten normal young male and female without cardiovascular disease were recruited, breath holding maneuver was used to change the physical condition. Continuous blood pressure waveforms of brachial and ulnar arteries were measured during the experiment using the proposed system. Real time computation of peripheral vessel model and the peripheral vessel characteristic before breath holding, during breath holding and after breath holding were used to discuss the difference between normal subjects in peripheral vessel characteristic. At the same time, to evaluate the effective rate and accurate rate of signal process procedure of the proposed system. Before analyze each continual blood signal section, inspection was made to identify detection error caused by electric pump activation or signal saturation. The evaluation of blood pressure efficacy is separated into total efficacy, brachial efficacy, and ulnar efficacy. The average efficacy rates are 70.62%, 73.88%, and 94.34%, respectively. Comparisons were also made for same frequency range, the correlation between brachial and ulnar blood signal. The original signal from brachial and ulnar arteries were filtered at the same frequency and inspected manually to exam the correctness of detyection for each characteristic points. The results indicate the average beat to beat detecting rate for total, brachial and ulnar arteries blood pressure signals are 90.96%, 83.13% and 45.87%, respectively. In addition, after ensemble average processing the detecting rate improved to 99.76%, 85.93% and 53.12%. For beat to beat correlation, there is no similar tream on avery blood pressure characteristic, thus the correlations are low. In two subject, negative correlations for blood amplitude and augmentation index appear. In this study, there are a lot of improvement can be made, such as the detection method of augmentation index characteristic point P1. Although there are some methods proposed by other research, but the actual result still had some error. If one can find a better method it will make a great improvement in the analysis of augmentation index.