A Bayesian Nonlinear Source Separation Method for Smart Ion-Selective Electrode Arrays

Potentiometry with ion-selective electrodes (ISEs) provides a simple and cheap approach for estimating ionic activities. However, a well-known shortcoming of ISEs regards their lack of selectivity. Recent works have suggested that smart sensor arrays equipped with a blind source separation (BSS) algorithm offer a promising solution to the interference problem. In fact, the use of blind methods eases the time-demanding calibration stages needed in the typical approaches. In this work, we develop a Bayesian source separation method for processing the outputs of an ISE array. The major benefit brought by the Bayesian framework is the possibility of taking into account some prior information, which can result in more realistic solutions. Concerning the inference stage, it is conducted by means of Markov chain Monte Carlo (MCMC) methods. The validity of our approach is supported by experiments with artificial data and also in a scenario with real data.

[1]  Kiyoshi Toko,et al.  Evaluation of water quality and pollution using multichannel sensors , 2000 .

[2]  E. Oja,et al.  Independent Component Analysis , 2001 .

[3]  Sailes K. Sengijpta.  Fundamentals of Statistical Signal Processing: Estimation Theory , 1995 .

[4]  Juha Karhunen,et al.  Advances in blind source separation (BSS) and independent component analysis (ICA) for nonlinear mixtures , 2004, Int. J. Neural Syst..

[5]  Y. Vlasov,et al.  Electronic tongue: Chemical sensor systems for analysis of aquatic media , 2008 .

[6]  W. Simon,et al.  Ion-selective membrane electrodes for clinical use. , 1986, Clinical chemistry.

[7]  Dermot Diamond,et al.  Potentiometric Nonlinear Multivariate Calibration with Genetic Algorithm and Simplex Optimization , 1997 .

[8]  Simon J. Godsill,et al.  A Bayesian Approach for Blind Separation of Sparse Sources , 2006, IEEE Transactions on Audio, Speech, and Language Processing.

[9]  C. Jutten,et al.  Improving semiconductor-based chemical sensor arrays using advanced algorithms for blind source separation , 2004, ISA/IEEE Sensors for Industry Conference, 2004. Proceedings the.

[10]  E. Pretsch,et al.  Modern potentiometry. , 2007, Angewandte Chemie.

[11]  M. Yasuzawa,et al.  Properties of glucose sensors prepared by the electropolymerization of pyrroles containing phosphatidylcholine (II) , 2000 .

[12]  Yoshio Umezawa,et al.  Potentiometric Selectivity Coefficients of Ion-Selective Electrodes. Part I. Inorganic Cations (Technical Report) , 2000 .

[13]  Christian Jutten,et al.  ISFET Source Separation: Foundations and Techniques , 2006 .

[14]  Martin L Yarmush,et al.  Development of an array of ion-selective microelectrodes aimed for the monitoring of extracellular ionic activities. , 2006, Analytical chemistry.

[15]  C. Jutten,et al.  A Mutual Information Minimization Approach for a Class of Nonlinear Recurrent Separating Systems , 2007, 2007 IEEE Workshop on Machine Learning for Signal Processing.

[16]  João Marcos Travassos Romano,et al.  Blind Source Separation of Post-nonlinear Mixtures Using Evolutionary Computation and Order Statistics , 2006, ICA.

[17]  Jiri Janata,et al.  Chemical Sensors: An Introduction for Scientists and Engineers , 2007 .

[18]  Pierre Comon,et al.  Séparation de sources 1. Concepts de base et analyse en composantes indépendantes , 2007 .

[19]  D. Brie,et al.  Separation of Non-Negative Mixture of Non-Negative Sources Using a Bayesian Approach and MCMC Sampling , 2006, IEEE Transactions on Signal Processing.

[20]  Xiaodong Wang,et al.  Monte Carlo methods for signal processing: a review in the statistical signal processing context , 2005, IEEE Signal Processing Magazine.

[21]  Vasile Coman,et al.  Computer-controlled system for ISEs automatic calibration , 2005 .

[22]  Christian P. Robert,et al.  The Bayesian choice , 1994 .

[23]  Saïd Moussaoui,et al.  Ion-Selective Electrode Array Based on a Bayesian Nonlinear Source Separation Method , 2009, ICA.

[24]  Xiaodong Wang,et al.  Monte Carlo methods for signal processing , 2005 .