TY - GEN
T1 - Signal processing for silicon ion-channel sensors
AU - Spanias, Andreas
AU - Goodnick, Stephen
AU - Thornton, Trevor
AU - Phillips, Stephen
AU - Wilk, Seth
AU - Kwon, Homin
N1 - Publisher Copyright:
© 2007 IEEE.
PY - 2007
Y1 - 2007
N2 - 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 a-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.
AB - 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 a-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.
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M3 - Conference contribution
AN - SCOPUS:84969132723
T3 - Proceedings - SAFE 2007: Workshop on Signal Processing Applications for Public Security and Forensics
BT - Proceedings - SAFE 2007
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - Workshop on Signal Processing Applications for Public Security and Forensics, SAFE 2007
Y2 - 11 April 2007 through 13 April 2007
ER -