神經外科加護病房中,醫師們在對病患預後做預測時,大多憑靠他們個人的臨床經驗,雖然可做出相當程度之預測,但仍有一些較難判斷的案例。因此,本研究則以模糊理論,將許多專業醫師多年來的臨床經驗,歸納成模糊規則,而以這些規則架構的模糊模型,使用者只需將指定的參數輸入,即可得到所需的輸出(患者預後狀況)。 本論文吸取文獻的研究經驗,探討影響患者腦傷預後之因素,並依據現有的環境與設備,發展出生醫訊號擷取系統以連續監測及記錄病患之血壓與顱內壓等生理訊號。接著,以此系統針對頭部外傷之病患進行訊號的擷取收集,之後再輔以相關性分析及模糊理論,並綜合臺大醫院神經外科加護病房醫師們的臨床知識,進而對病患做出預測性的預後評估,並將此評估定為FOS(Fuzzy Outcome Scale)。 此研究不僅能在醫師的臨床判斷上提供一客觀的評估方法,醫師也可藉由系統的評估,調整適合每個病人的治療方式,對病情達到最佳的控制。
When neurosurgeons predict the prognosis of neurocritical ill patients with severe head injuries, mostly by their personal clinical experiences, though can make the prediction analogous to the degree, but there are some cases more difficult to judge. For this reason, we set up a fuzzy model with fuzzy logic theory and clinical experiences of neurosurgeons. The user can get the state of patient's prognosis only needs to input some designated parameters. This thesis is probing into those factors of patient's prognosis by research, and build a system to continuous monitor and write down physiological signals of patients, like BP(blood pressure) and ICP(intracranical pressure) etc., according to existing environments and equipments. Moreover, the data capture by this system is mainly aimed at patients with severe head injuries. Afterward, it predicts the prognosis with fuzzy logic theory, Pearson product-moment correlation coefficient, and clinical experiences of neurosurgeons. In the end, we define the predictive prognosis as FOS(Fuzzy Outcome Scale)。 The contribution of this study is offer neurosurgeons an objective assessment method in the clinical judge and neurosurgeons can change treatment way which suitable each patient's with the assessment of the system to reach the best control to the condition.