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Digital signal processing methods for impedance microfluidic cytometry

Digital signal processing methods for impedance microfluidic cytometry
Digital signal processing methods for impedance microfluidic cytometry
Impedance microfluidic cytometry is a noninvasive, label-free technology that can characterize the dielectric properties of single particles (beads/cells) at high speed. In this paper we show how digital signal processing methods are applied to the impedance signals for noise removal and signal recovery in an impedance microfluidic cytometry. Two methods are used; correlation to identify typical signals from a particle and for a noisier environment, an adaptive filter is used to remove noise. The benefits of adaptive filtering are demonstrated quantitatively from the correlation coefficient and signal-to-noise ratio. Finally, the adaptive filtering method is compared to the Savitzky–Golay filtering method.
1613-4982
179-187
Sun, Tao
b2f8e932-a7e6-4fe7-94dd-5c4ce725eacb
Berkel, Cees van
e7867822-0251-471a-84f6-bbe3715dd38f
Green, Nicolas G
d9b47269-c426-41fd-a41d-5f4579faa581
Morgan, Hywel
de00d59f-a5a2-48c4-a99a-1d5dd7854174
Sun, Tao
b2f8e932-a7e6-4fe7-94dd-5c4ce725eacb
Berkel, Cees van
e7867822-0251-471a-84f6-bbe3715dd38f
Green, Nicolas G
d9b47269-c426-41fd-a41d-5f4579faa581
Morgan, Hywel
de00d59f-a5a2-48c4-a99a-1d5dd7854174

Sun, Tao, Berkel, Cees van, Green, Nicolas G and Morgan, Hywel (2008) Digital signal processing methods for impedance microfluidic cytometry. Microfluidics and Nanofluidics, 6, 179-187. (doi:10.1007/s10404-008-0315-3).

Record type: Article

Abstract

Impedance microfluidic cytometry is a noninvasive, label-free technology that can characterize the dielectric properties of single particles (beads/cells) at high speed. In this paper we show how digital signal processing methods are applied to the impedance signals for noise removal and signal recovery in an impedance microfluidic cytometry. Two methods are used; correlation to identify typical signals from a particle and for a noisier environment, an adaptive filter is used to remove noise. The benefits of adaptive filtering are demonstrated quantitatively from the correlation coefficient and signal-to-noise ratio. Finally, the adaptive filtering method is compared to the Savitzky–Golay filtering method.

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Published date: 14 June 2008
Organisations: Electronics & Computer Science

Identifiers

Local EPrints ID: 265944
URI: https://eprints.soton.ac.uk/id/eprint/265944
ISSN: 1613-4982
PURE UUID: e5b37bd5-f48e-410e-88d9-11045292926a
ORCID for Nicolas G Green: ORCID iD orcid.org/0000-0001-9230-4455
ORCID for Hywel Morgan: ORCID iD orcid.org/0000-0003-4850-5676

Catalogue record

Date deposited: 14 Jun 2008 17:01
Last modified: 29 Aug 2019 00:44

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Contributors

Author: Tao Sun
Author: Cees van Berkel
Author: Nicolas G Green ORCID iD
Author: Hywel Morgan ORCID iD

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