Blind source separation for solid-state chemical Sensors Arrays

Abstract

Electronic noses and tongues are two recent examples in chemical sensing that employ statistical array techniques in order to overcome the intrinsic limitations of current solid-state chemical sensors like ion-selective field transistors (ISFET). In particular, ISFETs are sensitive to the concentration of a particular ion in a solution to be measured, but it can be also strongly affected by several interfering ions found in the solution. Hence, they must be employed in regions in which the effect of interferences is negligible thus limiting their range of operation. However, since ISFETs behave as non-linear mixers of main ion activities and interfering ones, an attempt to separate the original main ion activity and interferences from the mixed response is suitable with blind source separation (BSS) techniques and related methods like independent component analysis (ICA) methods. In this direction, several experiments with real ISFET measurements demonstrate the interest of employing BSS for dealing with the separation in ISFET responses, and further reconstruction, of ion activities in those operating regions in which interferences notably affect their response.