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  • 學位論文

以臨床試驗評估壓力感測枕頭於睡眠監測之準確度研究

Validation of Sensor Pillow System for Sleep Monitoring with Clinical Trial

指導教授 : 郭德盛
共同指導教授 : 賴金鑫 陸哲駒(Jer-Junn Luh)

摘要


本研究採用非侵入式、設備簡單輕巧、易於操作之壓力感測枕頭(Sensor pillow system)蒐集睡眠時之壓力訊號,避免干擾使用者之睡眠品質,為一簡單有效之居家睡眠監測系統。壓力訊號經運算後可獲得上下床、睡姿改變之翻身和呼吸頻率等睡眠資訊,結果將整理為睡眠報告,作為健康照護之參考。 然而壓力感測器僅布置於枕頭下用以偵測頭部之壓力訊號,感測範圍受限,可獲得之資訊較少,因此需要以軟體運算方式提升運算準確度。臥床及睡眠動作等壓力訊號之處理,需由一連串閾值(Threshold)組成之決策條件運算,訊號經過運算流程篩選後,將確認結果寫入睡眠報告紀錄。 除睡眠監測系統外,尚建置健康風險分級機制並提供睡眠監測以外之生理量測功能,包含體溫、血壓、心跳和血氧濃度等。一方面供使用者評估健康狀態與上傳資料至遠端資料庫儲存;另一方面於使用者可能有健康風險時,自動由系統發出立即通知,讓家屬或醫護人員前往探視和救護,確保使用者安全。 本研究透過臨床試驗,評估睡眠監測系統投入實際應用之可行性與有效性,以及獲得演算法之最佳化參數設定。而試驗結果證實採用壓力感測枕頭輔以最佳化之演算法參數,確實可減輕硬體限制影響,準確且即時偵測睡眠之上下床、翻身等壓力訊號獲取睡眠資訊,產生可信之睡眠報告。

並列摘要


In order to provide a simple and effective in-home sleep monitoring system, this research applies a non-invasive and user-friendly sensor pillow system to acquire pressure data during sleep. The system can alleviate the interference from monitoring sensors for comfortableness of the user. Because the area of these pressure sensors is limited, there is an algorithm designed for improving the accuracy for detection of trunk movement instead of head motion only. The acquired pressure signals, such as occupancy and sleep movement, are processed and distinguished by some thresholds, and then output as sleep report. Besides the use of sleep monitoring system, the classification platform of health risk is included to integrate automated warning and vital sign measurement. The platform provides a user with analysis of health data and then uploads data into remote database. Also, it will send message to user’s emergency contact persons when the user is probably in jeopardy. After clinical trial for 30 subjects, its accuracy of the sleep monitoring system is measured, and the optimal parameters are acquired. The result shows the sensor pillow system after optimization with proper algorithm can accurately monitor pressure signals in real-time to distinguish occupancy and sleep movement information.

參考文獻


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