2004-12-012024-05-15https://scholars.lib.ntu.edu.tw/handle/123456789/664479摘要：這個計畫主要在做生醫訊號處理以及表面電漿共振與橢偏儀之整合。生醫訊號是來自於系統前端的感測器，而這些訊號通常都會受到環境噪音與感測元件的影響。做為一個生醫監控輔助系統，同時也會需要以人工智慧來輔助診斷。在此計畫中，我們將熱門的小波轉換理論與模糊分類理論做一個連接。小波轉換理論可以辨識一般訊號的症狀，而模糊分類理論則可以幫助我們分辨哪些是健康的人，哪些是病人。這種程序不僅可以幫助我們對於病人的情形做一個初步的判定，他也大大的減低了網路上的資料流量，並且降低了病人找醫生做詳細檢查的次數。 表面電漿共振技術已經證明了在檢測生醫訊號方面是一個很有效的方法。這個計畫同時也對於相關的光學技術以及所需的感測器技術做了相關的研究。最後，這個計畫會研究如何將這個系統微型化，並且使其成為桌上型的系統。 目標技術包含(其中有已達成及尚未達成的)： l 以進階的數位訊號處理技術來進行生醫訊號分析 l 以人工智慧來做電腦輔助之診斷 l 以WinCE為架構的嵌入式系統 l PXI系統架構與PXI周邊驅動程式開發 l 表面電漿共振橢偏儀系統之光機電整合<br> Abstract: This project is in charge of the biomedical signal processing and the integration of the Ellisometry system based upon Surface Plasmon Resonance (ESPR). The biomedical signal coming from the front end sensor is usually contaminated with environmental noise and sensor drifting. As a health care assisting system, it is also desirable to use artificial intelligence to assist diagnostics. This project investigates the method of concatenating the popular wavelet transformation with fuzzy clustering technique. The wavelet transform helps identify typical signal syndromes and the fuzzy clustering technique helps distinguish healthy person from patients with possible diseases. This process not only help preliminary finding on the patient conditions it also greatly reduces the amount of data flow over the network as well as the amount of patients for the doctor to conduct more detailed examination. Surface plasmon resonance (SPR) technology has proven to be an effective mean for detecting biomedical signals. This project also researches on the associated optics and the required sensor technologies. The project would then investigate methods to miniaturizing the system and to reduce the system for desktop applications. Some of the target technologies achieved or to be accomplished includes: l Biomedical signal analysis based upon advanced digital signal processing technique l Computer assisted diagnostics using artificial intelligence l WinCE based embedded system technology l PXI system architecture and PXI peripheral driver development l Opto-mechanical integration for the Surface Plasmon Resonance Ellisometry system生醫訊號處理表面電漿共振橢偏儀設計小波訊號分析嵌入式系統biomedical signal processingEllisometry systemSurface Plasmon ResonanceWavelet TransformEmbedded System