生理訊號數位化的研究已有許多可行性高的期刊論文發表，應用上也逐漸有相關產品以及醫療級儀器出現在市面上，包含心跳、異常呼吸以及血液成分等等。在生理訊號量測方面，非接觸、非侵入性的也有不少，整套系統輕量化、便於攜帶的近年來也出現很多。但在呼吸訊號方面，大多還是異常呼吸偵測以及單一麥克風收音為主，因此我們朝著普通呼吸偵測以及多個麥克風配合為方向。本文提出了一種多麥克風的聲音訊號演算法，可用於非侵入式生理訊號量測，同時整個設備體積小、便於攜帶。在生理訊號量測的部分，使用多個麥克風進行同步但不同位置的測量，固定在人體上的方式簡易好操作且黏貼的材料容易取得，並且在錄音過程中全程聲音放大倍率保持不變，僅需時域處理並以及數值上的運算，可以適應每位不同受測者的呼吸強度以及習慣，得出左右肺部呼吸的數據，證明左右肺部存在的差異，以及其差異的大小。

With the development of medical-grade measurement products, many consumers can measure physiological data with portable and lightweight sensors. Several studies on abnormal physiological signals demonstrate the feasibility of digitization and analysis. Due to the simplicity of respiratory signals, most abnormal respiration detecting systems are based on a single microphone. For the meticulousness of the analysis, we use multichannel microphones. Meanwhile, the non-invasive measurement system is contact and lightweight. In this thesis, we devise a multi-microphone-based system to detect the divergence and abnormalities between the lungs. Furthermore, the related algorithm can adapt to the physiological difference of various subjects.

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