人口老化的問題在全球是日益嚴重，不僅造成醫療的龐大的負擔，同時也是社會一大負擔。失智症是其中一項很重要的問題，它會造成老人記憶力衰退、注意力不集中、甚至是喪失工作的能力等等問題。因此，健康照護顯然變得如此重要。如何有效地檢測出老年痴呆症則被熱烈的討論與提出方法。正因如此，大多數的文獻也著重在利用影像與慣性感測器來測量外在行為與心智功能之間的關聯性。本篇論文即是提出一個在三軸慣性感測器的測量方法下，使用隱藏式馬可夫模型來尋找步伐上面的種種特徵。分析個人化之下，正常與非正常的步伐的差異程度，配合神經心理學測驗，輔助醫務人員檢測阿茲海默氏症者。結果也顯示，在隱藏式馬可夫模型的描述下，更能突顯正常與非正常步伐之間的差異程度。未來也期盼這樣簡單的測量方式可以廣泛應用於居家的檢測，幫助更多的老年人提早發現失智的潛在危機，減輕社會大眾的負擔。

The problem of aging population is getting worse in the world. It is not only huge medical burden but also social burden. Dementia is one of the important problems and it makes deep fading of memory, attention, and incapacity, etc. Therefore, the health care becomes more important. How to effectively detect dementia needs to be proposed. Accordingly, most research focus on the relationship between the cognition and behavior using video or inertial sensors. This thesis proposed a series of methods to analyze the association using an accelerometer and a gyroscope and to find the features using Hidden Markov model (HMM). Analyze the normal and abnormal walking via sensor mounted on the foot, mapping to the neuropsychological tests. Help medical staff to detect the mild Alzheimer's disease which is common one of the dementia, and classify a participant. Results show that the score of the HMM is significant differences between normal control and Alzheimer’s disease in our walking tests. In the future, wish a simple walking detection method by subjects themselves using inertial sensors could be widely used.

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