The response of a flow-through biosensor is the consequence of complex interrelations between the dilution of the sample in a continuous stream (governed by physical variables) and the phenomena involved in the reactions between enzyme and substrate (governed by diffusion and kinetic processes). These interrelations make it difficult to know in advance the influence of manifold parameters in the biosensor response. If a reliable model of these processes is attainable, it will be possible to test rapidly, by computer, the effect of the variation of different operating variables on the response of the biosensor. This paper presents the results obtained when two models are applied to describe dynamic behaviour of a potentiometric flow-through urea biosensor. One of these models uses an empirical approach based on neural networks, while the other proposes a deterministic approach that takes into account reaction-diffusion equations.
|Journal||Biosensors & Bioelectronics|
|Publication status||Published - 1 Jan 1996|
- Artificial neural networks
- Deterministic model
- Potentiometric flow-through biosensor
- Urea determination