Name
Title | ||
|---|---|---|
Automated Parallel Electrical Characterization of Cells Using Optically-Induced Dielectrophoresis |
Abstract | ||
|---|---|---|
This article reports an automated optically-induced dielectrophoresis (ODEP) system for characterizing the specific membrane capacitance (SMC) of individual cells. The simulation of cell motion is conducted to analyze the electrokinetic forces acting on the cell. A self-developed visual tracking algorithm for multicells is used to realize an automated process for determining the frequency-sweeping range, crossover frequencies, and cell radii. The SMC values of malignant bladder cancer cells (T24 and RT4) and normal urothelial cells (SV-HUC-1) were quantified using the automated system, demonstrating that the system has a measurement speed of ~1 cell/s, an accuracy of 1 kHz for the crossover frequency determination, and an accuracy of
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for the cell radius measurement.
<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</italic>
—The current manual optically-induced dielectrophoresis (ODEP) quantification of the specific membrane capacitance (SMC) values of the cells requires a tedious and time-consuming procedure for measuring the cell size and crossover frequency. The automated ODEP approach presented in this article was developed to identify multiple cells and trigger alternating current (ac) bias potential for measuring the radius and crossover frequency of multiple cells. Compared to the manual method, the automated system significantly improves the efficiency of the SMC measurement. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/TASE.2019.2963044 | IEEE Transactions on Automation Science and Engineering |
Keywords | DocType | Volume |
Automated measurement,biological cell,optically-induced dielectrophoresis (ODEP),specific membrane capacitance (SMC) | Journal | 17 |
Issue | ISSN | Citations |
2 | 1545-5955 | 1 |
PageRank | References | Authors |
0.41 | 0 | 13 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Na Liu | 1 | 2 | 2.11 |
| Yanbin Lin | 2 | 1 | 0.41 |
| Yan Peng | 3 | 95 | 19.21 |
| Liming Xin | 4 | 2 | 0.77 |
| Tao Yue | 5 | 1 | 0.75 |
| Yuanyuan Liu | 6 | 1 | 0.41 |
| Changhai Ru | 7 | 9 | 2.71 |
| Shaorong Xie | 8 | 112 | 38.53 |
| Liang Dong | 9 | 1 | 0.41 |
| Huayan Pu | 10 | 90 | 23.66 |
| Haige Chen | 11 | 1 | 0.41 |
| Wenjung Li | 12 | 171 | 49.26 |
| Yu Sun | 13 | 418 | 69.89 |