本論文提出一針對頸椎損傷等病患所研發之電視人機介面（Human-machine-interface；HMI），此一人機介面係結合眼動圖（Electrooculography；EOG）與腦波圖（Electroencephalography；EEG）電生理訊號所開發而成。上述兩電生理訊號提供病患眼球之水平與垂直移動方向與眼睛之閉合等資訊，以作為開關電視以及頻道與音量控制之機制。此外，本論文研發一電生理訊號放大與處理模組，其藉由擷取2通道之水平與垂直眼動訊號與1通道之Pz腦波訊號來產生5個獨立觸發事件訊號（包括：眼球朝上、下、左、右方向以及眼睛閉合）作為電視人機介面之控制方法觸發機制；本文並以裴氏圖無線感測節點架構（Petri Net based Wireless Sensor Node Architecture；PN-WSNA）建構電視人機介面控制模型；藉由情境模擬來分析期可達到性以驗證模組可靠度。本論文以一嵌入式PN-WSNA感測節點實現所設計之PN-WSNA模型並進行相關實驗。最後，本文進行相關實驗，並探討此本論文所提出方法之可行性。

This study presents a TV human-machine-interface (HMI) for high-level spinal cord patients. The TV HMI is developed with combining the electrooculography (EOG) and electroencephalography (EEG) biopotential signals. The above biopotential signals are responsible for detecting horizontal and vertical eye-gazing directions, as well as for recognizing opening and closing of eyes, so that the commands for TV on/off and changing channels and volumes can be desirable. In addition, a biopotential amplifier and processing device is futthetr developed to convert the two-channel EOG signals and a Pz EEG signal as five independent signal events, including the up-moving, down-moving, left-moving, right-moving of eye balls, and the closing of eyes. The five events are treated as the signal triggers for constructing a Petri net based wireless sensor node architecture (PN-WSNA) TV HMI model. Furthermore, the control scenario of generating the TV commands are implemented and evaluated by using the PN-WSNA approaches. A PN-WSNA-based autonomous sensor node is used to realize the TV HMI control system in terms of model-based implementation approach. Finally, several experiment results were discussed and evaluated to verify the feasibility of the proposed approaches.

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