近年來,由於MEMS的製程技術顯著的改進,再加上通訊裝置在市場上的需求性,加速RF的發展. MEMS的優點不僅可以大量製造,也可以微小化,相對於傳統的裝置更可以運作的更有效率.而RF量測與MEMS運用在生醫感測技術上,更是能使原本在阻抗量測方面獲得改善.例如:增進細胞定位的確切性,細胞的附著程度,電極的可靠度,量測訊號的正確性等.藉由這些改進,可將原本低頻在量測方面的不足與難題,轉換以射頻量測來克服.
本論文提出了一個可重複使用的共平面波導之開路電極來做細胞量測,藉由在射頻下的網路分析,提出對整個量測裝置的定性分析,例如製程變異,以及電極的長短.經由時域反射器的驗證,降低對基板的電容效應以提升量測的訊雜比以及網路分析儀的校準運算.從量測結果可以得知,此裝置的確有效的改善低頻量測的缺陷(電雙層電容),並能辨別濃度的不同,溶液的不同,細胞有無.從設計的結構,可以深入探討細胞膜的特性.此不僅解決了細胞量測的舊缺陷,更開啟了生醫感測的新思維.希望未來能在疾病量測等應用方面推進一步.

In the past years, since the processing techniques for MEMS (Micro-Electro-Mechanical Systems) have improved significantly, and the commercial demand for communication devices increases RF-tech development. Apart from having the advantages of mass production, and being miniaturized, MEMS lead to more efficient systems rather than conventional ones. Besides, the dielectric spectroscopy will be improved after using RF measurement and MEMS on biological sensing. For example, the precision of cellular localization, the extent of cell attachment, the reliability of electrodes, and the accuracy of measurement signal and so on. Through these improvements, the shortcomings and Gordian knots of measurement at relatively low frequency will overcome and improved using radio frequency measurement.
This study proposes a repeatable coplanar waveguide open-ended probe to perform cell measurement. Leaning on the network analysis at radio frequency, a quantitative analysis is investigated for the overall measurement device, such as fabrication deviation and stretch of probe. Verified by TDR (Time-Domain Reflectometer), capacitance effect of substrate is eliminated to improve signal-to-noise ratio on measurement and correct the calibration calculation of VNA (Vector Network Analyzer). Based on the measurement result, this device actually improves the shortcomings of measurement at low frequency, and discriminates different concentration of electrolyte, various solution, and single cell. For further investigation, cell membrane can be analyzed due to design schematic. It will promote the biological application such as disease detection in the future.

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