Signal Processing for Silicon Ion-Channel Sensors

The use of ion channels as sensing elements for biological and chemical agents is a rapidly developing area. A silicon-based ion-channel platform has been developed and the feasibility for stochastic sensing based on changes in the stochastic gating due to the external environment has been demonstrated. The distinct signatures of the ion-channel currents lend themselves to statistical signal analysis based on the frequency of their occurrence and other features. Although current fluctuations can be used for classification, the presence of noise from fast blocking events can be ambiguous. Signal processing techniques can be applied to the analysis of stochastic ion-channel signals. In this paper, we present advanced signal processing algorithms to study the stochastic response of porin OmpF and ¿-hemolysin to a variety of different analytes. A silicon-based ion-channel is presented. Core problems addressed in the paper include: the identification of unique stochastic current signatures, spectral estimation, reduction of noise and classification using state-based models.