本研究的主旨為探討卡爾曼濾波器於動脈壁局部單點性質之計算方法驗證，此計算方法是利用單點量測的方式，能早期診斷出病人的動脈局部是否有硬化的現象。參數識別過程需以狀態-空間方程式定義血管內壓力、流量(或流速)及直徑變化之關係式，並代入三種量測方法分別為壓力-流量(pq)、壓力-流速(pU)及徑-流速(DU)法；其中DU法可藉由非侵入式的超音波量測重建血管內壓力波形，此方法可解決長久以來需靠侵入式量測壓力值之問題。因此本研究為建構一套仿生理循環測試平台，用實驗的方式來探討此計算方法，其中動脈端為使用局部硬化及均勻硬化的矽膠人工血管代表，用來模擬不同血管硬化現象。實驗方法為在測試台的動脈端局部單點量取流量、壓力及直徑變化並代入壓力-流量(pq)、壓力-流速(pU)及徑-流速(DU)法；儘管量測中包含許多量測誤差，如雜訊(noise)、偏差(bias)、純量因子誤差(scale factor error)，但藉由以卡爾曼濾波器為基礎之識別系統仍可準確的識別出血管壁特徵，如截面積、脈動波速及楊氏係數。當識別均勻硬化血管的特徵時，以非侵入式的直徑-流速法最為準確，其誤差小於4%。識別局部硬化血管時，三種方法皆能有效識別出血管硬化的區域及趨勢，因此可證實此計算方法可用於動脈壁之診斷。以DU法重建局部硬化血管內壓力波形之最大偏差約為20 mmHg，可於未來修正計算方法以達到估測之準確性。

The objective of the present research was to verify the validity of a newly proposed Kalman filter-based state estimator and parameter identification procedure that can assess the arterial stiffness based on point-wise measurements. This identification procedure needs a state-space model to define the relationships among pressure, flowrate (or velocity) and vessel cross-sectional area. Variants in state-space formulation includes Pressure-Flowrate (pq), Pressure-Velocity (pU) and Diameter-Velocity (DU) identification systems. Specifically, DU method is associated with the advancement of non-invasive vascular ultrasonography because it can provide an in-situ pressure waveform reconstruction which has been traditionally lacking. In order to verify these newly proposed identification methods, a mock circulation loop was constructed. On this mock loop, pressure, cross-sectional area, and volume flowrate were measured. There are two types of silicone rubber artificial arteries that were used for method evaluation. One is made of homogeneous wall material and another by sandwiching a harder segment in between two softer adjacent segments, mimicing a diseased vessel with early-stage atherosclerotic plaque. The flowrate, pressure, and diameter measured at the allocated points of the artificial descending aorta were used for validating the pq, pU and DU identification procedure. Despite the presence of measurement errors (noise, bias and scale factor error), arterial wall properties, such as the stress-free cross-sectional area, pulse wave velocity, and Young's modulus were all identified with high accuracy by these three Kalman filter-based identification systems. The ultrasound-related DU method was found to be most accurate. It shows that DU method can achieve a parameter identification error less than 4% for uniform vessel wall stiffness. All three methods, pq, pU and DU, can unambiguously capture the vascular property jump appearing in the atherosclerotic juncture and the diseased segment, indicating the potential of the present methods to be used in aortic wall prognosis. Pressure waveform reconstructed by DU suffers inaccuracy (~20 mmHg) around the juncture of the atherosclerotic site, which warrants further investigation to improve the present identification accuracy.

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