Rapid Analyte Recognition in a Device Based on Optical Sensors and the Olfactory System

Abstract

We report here the development of a new vapor sensing device that is designed as an array of optically based chemosensors providing input to a pattern recognition system incorporating artificial neural networks. Distributed sensors providing inputs to an integrative circuit is a principle derived from studies of the vertebrate olfactory system. In the present device, primary chemosensing input is provided by an array of fiber-optic sensors. The individual fiber sensors, which are broadly yet differentially responsive, were constructed by immobilizing molecules of the fluorescent indicator dye Nile Red in polymer matrices of varying polarity, hydrophobicity, pore size, elasticity, and swelling tendency, creating unique sensing regions that interact differently with vapor molecules. The fluorescent signals obtained from each fiber sensor in response to 2-s applications of different analyte vapors have unique temporal characteristics. Using signals from the fiber array as inputs, artificial neural networks were trained to identify both single analytes and binary mixtures, as well as relative concentrations. Networks trained with integrated response data from the array or with temporal data from a single fiber made numerous errors in analyte identification across concentrations. However, when trained with temporal information from the fiber array, networks using "name" or "characteristic" output codes performed well in identifying test analytes.

Exploitation of spatiotemporal information and geometric optimization of signal/noise performance using arrays of carbon black-polymer composite vapor detectors

“…Detector types of interest include carbon black-insulating polymer composites [1], conducting organic polymers [2][3][4], polymer-coated quartz crystal microbalances (QCM) [5], polymer-coated surface acoustic wave (SAW) devices [6,7], polymer-coated capacitors [8], and arrays of dye-impregnated polymeric beads or coated optical fibers [9][10][11]. The responses of such sorption-based detectors depend primarily on the partition coefficient of the gaseous analyte into the polymer [12].…”

“…In most studies to date, the detectors in such an array are placed in nominally spatially equivalent positions relative to the analyte flow path [1,11,14]. In such a configuration, any spatiotemporal differences between detectors are minimized, and the array response pattern is determined by the differing physicochemical responses of the various detectors towards the analyte of interest.…”

Temporal coding of sensory information in the brain

“…sensor activation patterns [72]. Intrinsic temporal patterns of neural response potentially encode a number of visual attributes: texture, contrast, pattern, and color.…”

Microsystems for optical gas sensing incorporating the solvatochromic dye Nile Red

“…The field of artificial olfaction and gas determination is one of the fastest growing areas of sensing both commercially and within academic research areas [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15]. Much of the work in this field to date concentrates on identification and quantification of multiple analyte species by employing miniaturised sensors.…”

“…One way to achieve this is to have a multitude of specific receptors with high binding coefficients, such as the "smell-seeing" colorimetric sensor array for odour visualisation reported by Rakow and Suslick [14]. Alternatively, an array of less specific sensors may be used, employing a training protocol and pattern recognition technique, in a method similar to that developed by nature in the mammalian olfaction system [13,[16][17][18]. Within the context of the application of sensor arrays, ideally every vapour will cause some or all of the sensing elements to respond differently, producing a unique response pattern for each analyte.…”