睡眠呼吸中止症是一種常見的睡眠機能失調和慢性疾病，當人們在睡眠時，會有一次或多次的呼吸中止或淺呼吸，因此當人們在睡眠時，人的呼吸道會暫時性或完全地阻塞住，而每一次呼吸中止稱為一次睡眠呼吸中止症的事件，可持續十秒鐘至數分鐘不等。 人們通常是很難意識到自己罹患睡眠呼吸中止症，需要在醫院的睡眠中心透過整晚睡眠測試的診斷，稱為多項睡眠生理檢測(PSG)。 然而傳統的多項睡眠生理檢查是一種勞力密集、受限環境、不舒適且高成本的檢測。 因此本研究應用三軸加速度感測器，是一種低成本又便利的監測系統，兩組三軸加速度感測器貼附在左側胸腹部上，可被用來感測胸腹呼吸動作的訊號。主成分分析演算法 (PCA) 可被用來將三維的三軸訊號轉換到一維的呼吸訊號， Modified PCA 則可被用來增強轉換的效果，表現比PCA還要好，當與PSG訊號做比對時可看出更加的穩定。 本論文從三軸加速度感測器應用Modified PCA 得到一呼吸訊號，與PSG比對相似性可達到90%，判別事件的準確率則可達到80%，其中CSA和HYP事件仍然較難去辨別，整合其他的生理訊號和特徵來增加偵測事件演算法是必要的。

Sleep apnea syndrome (SAS) is a common sleep disorder and chronic disease in which people's airway becomes partially or completely blocked during sleep
and each pause in breathing is called a sleep apnea event, can last from ten seconds to minutes.
In general, people are difficultly conscious of SAS and have to diagnose with an overnight sleep test, which is called a polysomnography (PSG) in the sleeping center of the hospital.
However, PSG examination is a labor-intensive, limited environment, uncomfortable, and high-cost examination.
Therefore, this study implements tri-axial accelerometer (TAA), which is a low-cost and convenient monitoring system.
The two group of TAA attached to the left side of thorax and abdomen and can be used to capture the thoracic (THO) and abdominal (ABD) movement signals.
The principal component analysis (PCA) algorithm used for transfering the three-dimensional raw data sensing from TAA to one-dimensional respiratory signals.
The proposed modified PCA algorithm (modified PCA) can improve on the effect of the transformation, which is better than PCA algorithm, and signals are more stable when comparing with PSG.
This thesis proposed modified PCA to obtain the respiratory waveform from TAA compared with PSG can reach 90\% similarity and detection result can reach closely 80\% Identification.
The event of CSA and HYP still can not distinguished well and the other physiological signal or feature must be incorporated to enhance the identification.

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