遠距醫療系統的研究與建置已行之有年，本研究提出一套無線遠距醫療系統，除了整合既有的遠距醫療系統功能之外，並運用類神經網路於無線網路的資料傳輸偵測。以心跳表為例，當接受體能訓練的學員於戶外場所進行訓練，運用無線網路將心跳資料回傳至遠距醫療系統時，遠距醫療系統除了能接收學員的無線訊號之外，並能正確反應無線網路傳輸的狀況給學員或是管理員，即可增強遠距醫療系統的可靠性。
而使用無線網路進行資料傳輸，需要考量無線干擾、天候、網路拓樸、傳輸距離等問題，因此本研究先使用NS-2(Network simulation version 2)進行無線網路環境的模擬，以了解無線網路傳輸資料時的狀況，再以類神經網路學習之後，於其他無線網路節點上面驗證類神經網路的可用性，最後實作無線網路傳輸的程式，經由類神經網路於遠距醫療系統內部運算後，將無線網路傳輸的狀況，透過網際網路服務，回饋給使用者，或是管理者。此機制不僅能增強系統與使用者之間的互動，提昇遠距醫療系統與無線網路傳輸之間的可靠度，在管理層面上，進而能節省人力的成本。
The research and build telemedicine system has been many years. In this study, we propose a wireless telemedicine system integrate many functions developed and using neural network for wireless network detection during the data transmission. We use heart rate monitor for example, when students in outdoor places for physical training and using wireless network send data to telemedicine system. The telemedicine system not only receiving the heart rate data, also response the wireless network states to students or managers. It will improve the wireless telemedicine systems reliability.
However, using wireless network for data transmission, need to consider radio interrupt, weather, network topology, transmission distance etc. In this study we use NS-2(Network simulation version 2) for wireless network simulated for understand the wireless transmission states. And then use neural network to learn the wireless transmission states. After neural network learned, we use different wireless nodes to verify the availability of neural network in wireless telemedicine system. In the end, we implantation wireless transmission programs through neural network compute inside wireless telemedicine system. Then output the wireless transmission states by WEB service to users or managers. This function not only interaction with users, also improved the reliability between wireless telemedicine system and wireless network.
III
For management purpose, it also saves the cost of human resource.
