近年來，表面肌電訊號 (surface EMG) 受到了許多關注，無論是學術文章或是國際期刊，都對表面肌電訊號投入了大量的研究。EMG訊號用於分析肌肉的活動或者評估患者的肌肉狀態，現行市面上用於商業用途的表面肌電系統，不僅價格昂貴，且消耗功率極高，而本篇論文主要在於實現支援高取樣率和超低功耗的表面肌電訊號感測系統，透過分析和優化肌電訊號之感測電路的各個環節，且同時結合了擁有BLE的MCU，以優化現行市面上系統呈現上的不足。此外，本系統使用了兩種不同的CPU時脈頻率，並且結合了乒乓緩衝器作為記憶體架構，實驗結果顯示，與商用的表面肌電系統相比，本文所提出的表面肌電系統架構之平均電流可以降低高達92.72%，且電池壽命提高了9.057倍之多，且在相關係數上高達99.5%，這代表了商用的表面肌電系統和我們所提出的系統之間有著高度的一致和相關性，由此可見，未來若將本文所提之表面肌電訊號感測系統用於市面上，將有其不可取代的競爭力。

In recent years, the surface electromyography (surface EMG) signal has received a lot of attention. EMG signals are used to analyze muscle activity or to evaluate a patient's muscle status. The commercial surface EMG systems are expensive and have high power consumption. This thesis is to implement a surface EMG acquisition system supporting high sampling and ultra-low power consumption measurement. This work analyzes and optimizes each part of the EMG acquisition circuit and combines an MCU with BLE. The system used two different frequency CPU clock sources and proposed a ping-pong buffer as the memory architecture. The results show that all the average current of the proposed architecture can be reduced by 92.72% compared with the commercial devices, the battery life is 9.057 times. In addition, the correlation coefficients are up to 99.5%, which represent a high relative agreement between the commercial and the proposed system.

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