隨著科技的高度發展，人們為了追求效率往往忽略了日常的飲食，罹患糖尿病的人口正快速增加中，因此糖尿病的預防與偵測逐漸成為很重要的課題。許多研究證實，控制糖化血色素的濃度能有效偵測及延緩糖尿病併發症的產生，相對於偵測血糖，糖化血色素不容易受到短期飲食、運動、服用藥物及情緒所影響而導致誤判，但目前偵測糖化血色素技術受到成本高、操作複雜、不易攜帶等的限制，因此本篇論文著重在研究成本低、設備小、可攜式晶片自動量測系統的開發平台。
本篇研究採用低成本的可攜式自動化阻抗量測系統及環形指叉式電極來檢測糖化血色素所占整體血色素的比例，正常人糖化血色素比例約為4.0%~7.0%，大於7%即有患糖尿病的風險。為了偵測糖化血色素比例，首先必須利用自主性單分子層固定蛋白質，蛋白質附著的多寡會影響電場通過的量並讓交流阻抗產生變化，藉由阻抗變化量來換算蛋白質覆蓋電極的面積，搭配微流道與微型幫浦驅動分離包含糖化血色素的血色素溶液，使用單晶片微型電腦自動對各電極進行阻抗量測與資料分析，加總所換算出的蛋白質覆蓋電極之面積，即可自動偵測不同比例的糖化血色素。本研究使用自動量測系統儀器，藉由計算蛋白質覆蓋面積合，成功檢測出4%~7%比例的糖化血色素，改善量測儀器的攜帶不易、成本高的缺陷，自動化系統有效減輕實驗操作者的負擔，且僅需量測阻抗即可辨別糖化血色素的比例，故本研究已相當接近實際的臨床應用。

Glycated hemoglobin (HbA1c) which can reflect the glucose level for long-term monitored is one of the most important indexes of diabetic. In order to improve the drawbacks of instruments for HbA1c detection, such as large, expensive and hard to operate, an automated measurement systems device is proposed to detect the ratio of HbA1c to Hb. It is label-free, and low sample volume needed and no other reagent required.
The ring-shaped interdigital electrodes were coated with self-assembled monolayer to immobilize HbA1c. The amount of the protein adhering on the electrode affects the impedance deviation caused by electric field. By separating the HbA1c in Hb on separation electrodes with microfluidic channel and micropump, the impedance deviation of the electrodes will be calculated. The protein coverage of the electrodes was obtained through the microcontroller, and the different ratio of HbA1c can be detected automatically by summing up the area of protein covered on each separation electrodes.
The 4% to 7% ratios of HbA1c to Hb which is the actual body range are successively distinguished through the automatic impedance measurement system and the ring-shaped intedigital electrode in this study. The shortcoming of human consumption and bulky instrument is reduced. The automatic system is a simple way to analyze the impedance deviation and it effectively reduces the loading on the operator. The proposed method for the detection of HbA1c has potential for point-of-care diagnostics and is extremely close to clinical needs in this research.

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