A novel silicon membrane-based biosensing platform using distributive sensing strategy and artificial neural networks for feature analysis


A novel biosensing system based on a micromachined rectangular silicon membrane is proposed and investigated in this paper. A distributive sensing scheme is designed to monitor the dynamics of the sensing structure. An artificial neural network is used to process the measured data and to identify cell presence and density. Without specifying any particular bio-application, the investigation is mainly concentrated on the performance testing of this kind of biosensor as a general biosensing platform. The biosensing experiments on the microfabricated membranes involve seeding different cell densities onto the sensing surface of membrane, and measuring the corresponding dynamics information of each tested silicon membrane in the form of a series of frequency response functions (FRFs). All of those experiments are carried out in cell culture medium to simulate a practical working environment. The EA.hy 926 endothelial cell lines are chosen in this paper for the bio-experiments. The EA.hy 926 endothelial cell lines represent a particular class of biological particles that have irregular shapes, non-uniform density and uncertain growth behaviour, which are difficult to monitor using the traditional biosensors. The final predicted results reveal that the methodology of a neural-network based algorithm to perform the feature identification of cells from distributive sensory measurement has great potential in biosensing applications.

Publication DOI: https://doi.org/10.1007/s10544-011-9587-6
Divisions: College of Health & Life Sciences
College of Health & Life Sciences > Chronic and Communicable Conditions
College of Engineering & Physical Sciences > School of Infrastructure and Sustainable Engineering > Engineering Systems and Supply Chain Management
College of Health & Life Sciences > School of Biosciences
College of Engineering & Physical Sciences > School of Engineering and Technology > Mechanical, Biomedical & Design
College of Engineering & Physical Sciences
Additional Information: The final publication is available at Springer via http://dx.doi.org/10.1007/s10544-011-9587-6
Uncontrolled Keywords: Biomedical Engineering,Molecular Biology
Publication ISSN: 1572-8781
Last Modified: 31 May 2024 07:08
Date Deposited: 25 May 2012 09:03
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
http://www.spri ... 42kx5j465241m4/ (Publisher URL)
PURE Output Type: Article
Published Date: 2012-02
Published Online Date: 2011-09-14
Authors: Wu, Zhangming
Choudhury, Khujesta
Griffiths, Helen R (ORCID Profile 0000-0002-2666-2147)
Xu, Jinwu
Ma, Xianghong (ORCID Profile 0000-0003-4957-2942)



Version: Accepted Version

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