臺灣博碩士論文加值系統

據調查，在美國約有9% 的中年男性及4 % 的中年女性人口有睡眠呼吸暫停症候群；而在日本的調查發現，約人口數的1% 有睡眠呼吸暫停。在台灣預估有超過四十萬的人口患有此疾病。因為這個問題都發生在睡眠時，病人較難自己查覺，常常都要靠家人及醫師有高度的警覺性才會懷疑到。一般而言醫生在做睡眠障礙檢驗時，需要患者在醫院附設的睡眠中心渡過一夜，配合多通道的生理量測儀，才能夠準確的判斷是否罹患呼吸中止症。因此我們提出一個非侵入且不需接觸到人體，便能感測到睡眠鼾聲訊號的系統。依據其鼾聲特性，作為初次測試呼吸中止症的檢驗。利用本系統來節省受測者的時間與耗費的醫療資源。

Based on the investigation of Population Health Sciences & Biostatistics and Medical Informatics Dept. Univ. of Wisconsin, there are about 9% autumnal males and 4% autumnal females affected by SAS(Sleep Apnea Syndrome). In Japan’s investigation, there are about 1% of total populations affected by SAS. The case in Taiwan, it’s almost 0.4 million people. Because, the condition of SAS usually happen in sleep, the patients hard to aware. Hence, sometimes SAS be noticed by patients’ family or doctors. In the common case, when doctor diagnosing the “sleep disturbance” always need the patient staying in the “center of sleep medicine” for a night with polysomnography (PSG). That’s can know if the patient got SAS correctly. So, we develop a “non-invasive” system to detect the snoring sound of sleeping people for the initial test by self. It can decrease the cost of medical resource and save private time.

致謝 i
中文摘要 ii
Abstract iii
目錄 iv
圖目錄 vi
表目錄 ix
第一章 背景 1
1.1 研究動機 1
1.2 阻塞性呼吸中止症介紹 2
1.3 研究目的 6
1.4 相關研究 7
第二章 系統設計 11
2.1 系統架構 11
2.2 鼾聲介紹 13
2.2.1 鼾聲形成原因 13
2.2.2 鼾聲聲音特性 16
2.3 鼾聲接收硬體電路 17
2.3.1 感測器 18
2.3.2 放大電路 18
2.3.3 濾波電路 19
2.3.4 類比轉數位訊號模組 22
2.3.5 微處理器部份 25
2.3.6 藍芽無線傳輸部分 31
2.3.7 硬體實現 37
第三章 軟體設計 40
3.1 阻塞型呼吸中止症診斷依據 40
3.2 訊號前處理 42
3.3 鼾聲擷取演算法 43
第四章 實驗結果 49
4.1 模擬結果 49
4.1.1 臨界值的分析 49
4.1.2 鼾聲分析 51
第五章 結論與未來展望 64
5.1 結論 64
5.2 未來展望 64
參考文獻 66

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