摘要: | 本研究的目的是以生理機制與臨床實驗數據做為調整參數的依據,並使用等效電路及數學函數來建構呼吸系統模型,來模擬正常情形、環境改變以及疾病狀態的生理現象。我們以集總參數的方法將呼吸系統分為上通氣道、可塌陷氣道、小氣道以及肺泡區域四個部分,並加入呼吸中樞調控機制,讓模型能夠模擬氧氣與二氧化碳對呼吸行為的影響,並顯示酸鹼度變化對呼吸頻率與潮氣容積的影響。本論文的呼吸系統模型包含三種情形的模擬: ( 1 ) 正常情形時的呼吸, ( 2 ) 環境變化時呼吸行為的改變, ( 3 ) 疾病狀態下的呼吸情形。在正常情形時模擬結果可顯示呼吸氣流量、潮氣容積、呼吸頻率等特徵。模擬高二氧氧化碳環境時,我們分別將環境中二氧化碳含量由正常值0.3%調整為3%、5%、6%以及7%,此時過多的二氧化碳會造成血液中的pH值下降,刺激呼吸中樞,使潮氣容積、呼吸頻率等數值明顯增加,進而使總換氣量分別增加為原來的1.7倍、3.06倍、4.3倍以及6倍,讓體內累積過多的二氧化碳可以排出體外;而在低氧環境時,我們將環境中的氧氣分壓由正常值20%調整為9%、8%與7%,此時正常呼吸無法提供維持正常生理機能所需要的氧氣,導致呼吸頻率與潮氣容積增加,總換氣量增加為原來的2.3倍、3.2倍與4.4倍,加速氧氣進入體內以維持正常的生理機能。從此結果可以看出,呼吸行為對環境中氧氣分壓的改變較為敏感,當環境中氧氣含量降為原來的一半時,總換氣量即有明顯的改變;二氧化碳含量則必須增加為原來的十倍才能達到同等效果。模擬疾病時,我們分別模擬氣喘、慢性支氣管炎以及肺氣腫等疾病,模型可模擬由呼吸道阻塞所引起的血碳酸過高以及缺氧的情形,此時呼吸頻率增加,但呼吸流量減少導致潮氣容積並沒有明顯增加,總換氣量有小幅的增加。 模擬結果顯示本模型具有模擬正常情形呼吸的能力,加入呼吸調控機制後,更可以模擬環境與疾病狀態時,氧氣及二氧化碳改變對呼吸造成的影響。本模型能夠做不同情境下呼吸行為改變的研究,並提供環境變化與疾病狀態的預測。;The purpose of this study is to build a respiratory system model with physiological regulatory mechanism by using equivalent analog circuits and mathematical functions. Based on the physiological mechanism and clinical experimental data, we can adjust the parameters to simulate the physiological phenomenon of normal condition, environmental changes and pathological conditions. We used the lumped parameter method to build the respiratory system model and divided it into four sections: upper airways, collapsible airways, small airways and alveolar regions. Furthermore, by adding the respiratory control mechanism into the system, we could simulate the effects of oxygen and carbon dioxide on the respiratory behavior, and show how pH value affects breathing frequency and tidal volume with this model. The respiratory system model in this thesis could be used to simulate three conditions: (1) normal condition, (2) environmental changes, and (3) disease situations. In normal condition, the simulation results could show physiologically normal air flow, tidal volume and respiratory rate. When simulating the situation of hypercapnia, we adjust the inspiratory carbon dioxide from normal level, which is 0.3%, to 3%、5%、6% and 7%. Under these conditions, excess carbon dioxide has been inhaled, causing a drop in pH values. Respiratory rate and tidal volume were significantly increased. Furthermore, total ventilation was increased to 1.7, 3.06, 4.3 and 6 times larger than that of the original, respectively. When simulating the situation of hypoxia, we adjust the inspiratory oxygen from normal level, which is 20%, to 9%、8% and 7%. Under these circumstances, respiratory rate and tidal volume were significantly increased. Total ventilation was increased to 2.3, 3.2 and 4.4 times larger than that of the original, respectively. Based on these results, it could be implied that oxygen is more sensitive to respiratory behaviors. When simulating disease situations, we simulated asthma, chronic bronchitis and emphysema. Our model could have the ability to simulate hypercapnia and hypoxia caused by airway obstruction. In this case, respiratory rate was increased, but the tidal volume was not changed, and the total ventilation was increased slightly. In summary, our results showed that this model was capable of simulating air flow, tidal volume, breathing frequency and other characteristics under normal conditions. By adding respiratory control mechanism, we could simulate respiratory rate and tidal volume responses caused by oxygen and carbon dioxide changes due to conditions of environmental changes and diseases. The model we built in this study provides a research tool for studying respiratory behavior changes under different conditions, and a prediction of respiratory behavior affected by environmental changes and diseases. |