Automated Parallel Electrical Characterization of Cells Using Optically-Induced Dielectrophoresis

Na Liu; Yanbin Lin; Yan Peng; Liming Xin; Tao Yue; Yuanyuan Liu; Changhai Ru; Shaorong Xie; Liang Dong; Huayan Pu; Haige Chen; Wen J. Li; Yu Sun

doi:10.1109/TASE.2019.2963044

Author(s)

Na Liu
Yanbin Lin
Yan Peng
Liming Xin
Tao Yue
Yuanyuan Liu
Changhai Ru
Shaorong Xie
Liang Dong
Huayan Pu
Haige Chen
Yu Sun

Related Research Unit(s)

Department of Mechanical Engineering

Detail(s)

Original language	English
Article number	8984249
Pages (from-to)	1084-1092
Journal / Publication	IEEE Transactions on Automation Science and Engineering
Volume	17
Issue number	2
Online published	5 Feb 2020
Publication status	Published - Apr 2020

Link(s)

DOI	DOI https://doi.org/10.1109/TASE.2019.2963044 Final Published version
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Link to Scopus	https://www.scopus.com/record/display.uri?eid=2-s2.0-85082884349&origin=recordpage
Permanent Link	https://scholars.cityu.edu.hk/en/publications/publication(913c586e-f587-430f-92ff-309b9988f654).html

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 0.2 μm for the cell radius measurement.

Research Area(s)

Automated measurement, biological cell, optically-induced dielectrophoresis (ODEP), specific membrane capacitance (SMC)

Citation Format(s)

[ RIS ] [ BibTeX ]

Automated Parallel Electrical Characterization of Cells Using Optically-Induced Dielectrophoresis. / Liu, Na; Lin, Yanbin; Peng, Yan et al.

In: IEEE Transactions on Automation Science and Engineering, Vol. 17, No. 2, 8984249, 04.2020, p. 1084-1092.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review

Liu, N, Lin, Y, Peng, Y, Xin, L, Yue, T, Liu, Y, Ru, C, Xie, S, Dong, L, Pu, H, Chen, H, Li, WJ & Sun, Y 2020, 'Automated Parallel Electrical Characterization of Cells Using Optically-Induced Dielectrophoresis', IEEE Transactions on Automation Science and Engineering, vol. 17, no. 2, 8984249, pp. 1084-1092. https://doi.org/10.1109/TASE.2019.2963044

Liu, N., Lin, Y., Peng, Y., Xin, L., Yue, T., Liu, Y., Ru, C., Xie, S., Dong, L., Pu, H., Chen, H., Li, W. J., & Sun, Y. (2020). Automated Parallel Electrical Characterization of Cells Using Optically-Induced Dielectrophoresis. IEEE Transactions on Automation Science and Engineering, 17(2), 1084-1092. [8984249]. https://doi.org/10.1109/TASE.2019.2963044

Liu N, Lin Y, Peng Y, Xin L, Yue T, Liu Y et al. Automated Parallel Electrical Characterization of Cells Using Optically-Induced Dielectrophoresis. IEEE Transactions on Automation Science and Engineering. 2020 Apr;17(2):1084-1092. 8984249. Epub 2020 Feb 5. doi: 10.1109/TASE.2019.2963044

Liu, Na ; Lin, Yanbin ; Peng, Yan et al. / Automated Parallel Electrical Characterization of Cells Using Optically-Induced Dielectrophoresis. In: IEEE Transactions on Automation Science and Engineering. 2020 ; Vol. 17, No. 2. pp. 1084-1092.