Conference Paper

Reconfigurable Ion-Channel based Biosensor: Input Excitation Design and Analyte Classification

DOI: 10.1109/CDC.2009.5400762 Conference: Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on
Source: IEEE Xplore


This paper considers modeling and signal processing of a biosensor incorporating gramicidin A (gA) ion channels. The gA ion channel based biosensor provides improved sensitivity in rapid detection of biological analytes and is easily adaptable to detect a wide range of analytes. In this paper, the electrical dynamics of the biosensor are modeled by an equivalent second order linear system. The chemical dynamics of the biosensor response to analyte concentration are modeled by a two-time scale nonlinear system of differential equations. An optimal input excitation is designed for the biosensor to minimize the covariance of the channel conductance estimate. By using the theory of singular perturbation, we show that the channel conductance varies according to one of three possible modes depending on the concentration of the analyte present. A multi-hypothesis testing algorithm is developed to classify the analyte concentration in the system as null, medium or high. Finally experimental data collected from the biosensor in response to various analyte concentrations are used to verify the modeling of the biosensor as well as the performance of the multi-hypothesis testing algorithm.

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    ABSTRACT: This paper deals with the construction and analysis of distributed dynamical models for a novel biosensor that exploits the molecular switching mechanism of biological ion channels. The rate of change of the concentration of the chemical species in the biosensor are given by a system of nonlinear ordinary differential equations in the reaction-rate limited region of operation. When the transport rate of analyte to the biosensor surface is comparable to the intrinsic reaction rates, the dynamics of the biosensor are explained accurately using a two dimensional advection diffusion parabolic partial differential equation. When the rate of transport of analyte to the biosensor surface is much slower than the intrinsic reaction rates the biosensor is said to be operating under mass transport limited conditions. Under these conditions a system of coupled ordinary differential equations and the mass transport coefficient model the dynamics of the biosensor accurately. The equivalent mathematical models are shown to produce accurate data under the required operating conditions by comparison with experimental data.
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