在醫學、運動科學和人機互動等多元的領域中，專業且實用的表面肌電訊號(Surface Electromyography, sEMG)採集系統扮演關鍵角色，特別是在數據採集階段，具有小巧外觀、模組化設計、且具備擴展性等特點的方案。在本項研究中，我們提出了一套系統解決方案，透過多個搭載表面肌電訊號採集電路的感測器節點，構成一個無線感測器網路，能夠實現同時測量使用者不同部位的肌肉活動，並能應用到同時多人使用的場景。得益於我們的可擴展架構，此架構顯著減少了管理每個節點的複雜度，使各種終端設備能更容易與本系統連接。值得注意的是，本系統除了表面肌電訊號外，更支援整合第三方感應器，從而使得可蒐集的數據種類更多樣。在本論文中，我們首先驗證了單一傳感器節點的數據收集能力，包括類比前端的頻率響應及其在肱二頭肌上的應用。隨後，為了證明了系統的可擴展性，我們使用八個感應器節點收集數據，並且三個終端裝置訂閱所有數據流，中央處理節點的總網路流量僅為74.04kB/s。

Practical surface electromyography (sEMG) acquisition systems play a crucial role in areas such as medicine, sports science, and human-machine interaction, especially in addressing common problems in data acquisition such as size, modularity, and scalability. In this study, we propose a solution through the implementation of a wireless sensor network composed of multiple sensor nodes, capable of simultaneous measurement of muscles at different locations, as well as applications within multi-person scenarios. Benefiting from our scalable architecture, the complexity of managing each node is reduced, facilitating an easier connection with various terminal devices. Notably, this system is adapted for sEMG and supports the integration of third-party sensors. In this thesis, we validated the data collection capability of a single sensor node, including the frequency response in the AFE and its application on the biceps brachii. Subsequently, we tested the system's scalability by experimenting with eight sensors collecting data and three terminal devices subscribing to all data streams, with total network traffic on the central processing node at just 74.04kB/s.

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