Signal and data processing for machine olfaction and chemical sensing: A review

Signal and data processing are essential elements in electronic noses as well as in most chemical sensing instruments. The multivariate responses obtained by chemical sensor arrays require signal and data processing to carry out the fundamental tasks of odor identification (classification), concentration estimation (regression), and grouping of similar odors (clustering). In the last decade, important advances have shown that proper processing can improve the robustness of the instruments against diverse perturbations, namely, environmental variables, background changes, drift, etc. This article reviews the advances made in recent years in signal and data processing for machine olfaction and chemical sensing

Calibration transfer in temperature modulated gas sensor arrays

Shifts in working temperature are an important issue that prevents the successful transfer of calibration models from one chemical instrument to another. This effect is of special relevance when working with gas sensor arrays modulated in temperature. In this paper, we study the use of multivariate techniques to transfer the calibration model from a temperature modulated gas sensor array to another when a global change of temperature occurs. To do so, we built 12 identical master sensor arrays composed of three different types of commercial Figaro sensors and acquired a dataset of sensor responses to three pure substances (ethanol, acetone and butanone) dosed at 7 concentrations. The master arrays are then shifted in temperature (from −50 to 50 °C, ΔT = 10 °C) and considered as slave arrays. Data correction is performed for an increasing number of transfer samples with 4 different calibration transfer techniques: Direct Standardization, Piece-wise Direct Standardization, Orthogonal Signal Correction and Generalized Least Squares Weighting. In order to evaluate the performance of the calibration transfer, we compare the Root Mean Square Error of Prediction (RMSEP) of master and slave arrays, for each instrument correction. Best results are obtained from Piece-wise Direct standardization, which exhibits the lower RMSEP values after correction for the smaller number of transfer samples

Understanding odor information segregation in the olfactory bulb by means of mitral and tufted cells

Odor identification is one of the main tasks of the olfactory system. It is performed almost independently from the concentration of the odor providing a robust recognition. This capacity to ignore concentration information does not preclude the olfactory system from estimating concentration itself. Significant experimental evidence has indicated that the olfactory system is able to infer simultaneously odor identity and intensity. However, it is still unclear at what level or levels of the olfactory pathway this segregation of information occurs. In this work, we study whether this odor information segregation is performed at the input stage of the olfactory bulb: the glomerular layer. To this end, we built a detailed neural model of the glomerular layer based on its known anatomical connections and conducted two simulated odor experiments. In the first experiment, the model was exposed to an odor stimulus dataset composed of six different odorants, each one dosed at six different concentrations. In the second experiment, we conducted an odor morphing experiment where a sequence of binary mixtures going from one odor to another through intermediate mixtures was presented to the model. The results of the experiments were visualized using principal components analysis and analyzed with hierarchical clustering to unveil the structure of the high-dimensional output space. Additionally, Fisher's discriminant ratio and Pearson's correlation coefficient were used to quantify odor identity and odor concentration information respectively. Our results showed that the architecture of the glomerular layer was able to mediate the segregation of odor information obtaining output spiking sequences of the principal neurons, namely the mitral and external tufted cells, strongly correlated with odor identity and concentration, respectively. An important conclusion is also that the morphological difference between the principal neurons is not key to achieve odor information segregation

Calibration transfer and drift counteraction in chemical sensor arrays using Direct Standardization

Inherent variability of chemical sensors makes it necessary to calibrate chemical detection systems individually. This shortcoming has traditionally limited usability of systems based on metal oxide gas sensor arrays and prevented mass-production for some applications. Here, aiming at exploring calibration transfer between chemical sensor arrays, we exposed five twin 8-sensor detection units to different concentration levels of ethanol, ethylene, carbon monoxide, or methane. First, we built calibration models using data acquired with a master unit. Second, to explore the transferability of the calibration models, we used Direct Standardization to map the signals of a slave unit to the space of the master unit in calibration. In particular, we evaluated the transferability of the calibration models to other detection units, and within the same unit measuring days apart. Our results show that signals acquired with one unit can be successfully mapped to the space of a reference unit. Hence, calibration models trained with a master unit can be extended to slave units using a reduced number of transfer samples, diminishing thereby calibration costs. Similarly, signals of a sensing unit can be transformed to match sensor behavior in the past to mitigate drift effects. Therefore, the proposed methodology can reduce calibration costs in mass-production and delay recalibrations due to sensor aging. Acquired dataset is made publicly available

A practical method to estimate the resolving power of a chemical sensor array: application to feature selection

A methodology to calculate analytical figures of merit is not well established for detection systems that are based on sensor arrays with low sensor selectivity. In this work, we present a practical approach to estimate the Resolving Power of a sensory system, considering non-linear sensors and heteroscedastic sensor noise. We use the definition introduced by Shannon in the field of communication theory to quantify the number of symbols in a noisy environment, and its version adapted by Gardner and Barlett for chemical sensor systems. Our method combines dimensionality reduction and the use of algorithms to compute the convex hull of the empirical data to estimate the data volume in the sensor response space. We validate our methodology with synthetic data and with actual data captured with temperature-modulated MOX gas sensors. Unlike other methodologies, our method does not require the intrinsic dimensionality of the sensor response to be smaller than the dimensionality of the input space. Moreover, our method circumvents the problem to obtain the sensitivity matrix, which usually is not known. Hence, our method is able to successfully compute the Resolving Power of actual chemical sensor arrays. We provide a relevant figure of merit, and a methodology to calculate it, that was missing in the literature to benchmark broad-response gas sensor arrays

Bioinspired Early Detection through gas flow modulation in chemo-sensory systems

The design of bioinspired systems for chemical sensing is an engaging line of research in machine olfaction. Developments in this line could increase the lifetime and sensitivity of artificial chemo-sensory systems. Such approach is based on the sensory systems known in live organisms, and the resulting developed artificial systems are targeted to reproduce the biological mechanisms to some extent. Sniffing behaviour, sampling odours actively, has been studied recently in neuroscience, and it has been suggested that the respiration frequency is an important parameter of the olfactory system, since the odour perception, especially in complex scenarios such as novel odourants exploration, depends on both the stimulus identity and the sampling method. In this work we propose a chemical sensing system based on an array of 16 metal-oxide gas sensors that we combined with an external mechanical ventilator to simulate the biological respiration cycle. The tested gas classes formed a relatively broad combination of two analytes, acetone and ethanol, in binary mixtures. Two sets of low-frequency and high-frequency features were extracted from the acquired signals to show that the high-frequency features contain information related to the gas class. In addition, such information is available at early stages of the measurement, which could make the technique suitable in early detection scenarios. The full data set is made publicly available to the community

Recuperando la ciudad. Estrategia para el diseño y la evaluación de planes programas de regeneración urbana integrada

El presente documento es uno de los resultados obtenidos del proyecto financiado por el Plan Nacional I+D+i para el periodo 2013-2015, titulado Estrategia para el diseño y evaluación de planes y programas de regeneración urbana integrada. La intervención en las periferias españolas a través de las áreas de rehabilitación integral y el programa URBAN (BIA2012-31905), realizado en el Departamento de Urbanística y Ordenación del Territorio de la Escuela Técnica Superior de Arquitectura de Madrid. El objetivo del proyecto fue desarrollar una “herramienta de evaluación” de los planes y programas de Rehabilitación Urbana Integrada y se materializa en un árbol de conceptos que deberían ser analizados tanto antes como después del plan o proyecto. Su intención es facilitar la comunicación entre los distintos actores de la rehabilitación: vecinos, técnicos y administración, que al disponer de un modelo de análisis común (que deberá ser ratificado de forma consensuada desde las fases previas de la operación) puedan llegar a consensos sobre cuáles son los elementos fundamentales y los secundarios de la operación, lo que permitiría determinar (en un marco de recursos limitados), el porqué y las consecuencias de la elección de alguno de los elementos del modelo en detrimento de otros. El modelo se construye en una doble dimensión. La espacial en la que se reflexiona sobre los distintos niveles de integración, desde el área urbana en la que se enclava, al espacio público del barrio sobre el que se pretende actuar, para llegar a la edificación y la vivienda, incluyendo a los propios habitantes. Pero esta estructura tiene la capacidad de garantizar la segunda dimensión, la integralidad de las operaciones, diferenciándose ésta en tres niveles: áreas, categorías e ítems. Se definen cuatro áreas, Marco Urbano y Territorial, Diseño urbano y Medio ambiente local, Edificación y Socio-Económica, que establecen el marco básico de la calidad urbana. Las categorías, en las que se divide cada área, representan un marco conceptual consistente que establece los temas que tienen que ser considerados y analizados en el proceso si queremos garantizar la integralidad de la actuación. Las categorías se dividen en ítems que son los elementos que en cada caso se utilizarán para garantizar la calidad final del plan o programa. Se han considerado los ítems como contextuales porque se conformarán en detalle y con matices diferenciados en función de cada proyecto o acción concreta, por lo que podrán coincidir con los ítems elaborados durante el desarrollo de esta herramienta o ser diferentes por necesidades específicas. El presente documento se completa con dos anexos: Anexo I: Informe de la encuesta sobre experiencias de rehabilitación urbana en las ciudades españolas. Resultados. URL: http://oa.upm.es/43244/ Anexo II: Fichas de los ítems. URL: http://oa.upm.es/43247

Anexo II. Fichas de los ítems

El presente documento contiene uno de los anexos a la publicación impresa titulada "Recuperando la ciudad. Estrategia para el diseño y la evaluación de planes y programas de regeneración urbana integrada" —ISBN: 978-84-9728-5585-1— libro que es uno de los resultados obtenidos del proyecto financiado por el Plan Nacional I+D+i para el periodo 2013-2015, titulado "Estrategia para el diseño y evaluación de planes y programas de regeneración urbana integrada. La intervención en las periferias españolas a través de las áreas de rehabilitación integral y el programa URBAN" (BIA2012-31905). Dicho proyecto se ha realizado en el Departamento de Urbanística y Ordenación del Territorio de la Escuela Técnica Superior de Arquitectura de Madrid, mediante la financiación del Ministerio de Economía y Competitividad, a través del Plan Nacional de I+D+i 2008-2011 (Subprograma de Proyectos de Investigación Fundamental no Orientada). En este segundo anexo se realiza una caracterización y descripción de cada uno de los ítems que forman parte cada una de las categorías pertenecientes a las cuatro áreas principales, facilitando así el uso de la herramienta en los casos en los que se requiera de un mayor nivel de detalle

Continuous spatial representations in the olfactory bulb may reflect perceptual categories

In sensory processing of odors, the olfactory bulb is an important relay station, where odor representations are noise-filtered, sharpened, and possibly re-organized. An organization by perceptual qualities has been found previously in the piriform cortex, however several recent studies indicate that the olfactory bulb code reflects behaviorally relevant dimensions spatially as well as at the population level. We apply a statistical analysis on 2-deoxyglucose images, taken over the entire bulb of glomerular layer of the rat, in order to see how the recognition of odors in the nose is translated into a map of odor quality in the brain. We first confirm previous studies that the first principal component could be related to pleasantness, however the next higher principal components are not directly clear. We then find mostly continuous spatial representations for perceptual categories. We compare the space spanned by spatial and population codes to human reports of perceptual similarity between odors and our results suggest that perceptual categories could be already embedded in glomerular activations and that spatial representations give a better match than population codes. This suggests that human and rat perceptual dimensions of odorant coding are related and indicates that perceptual qualities could be represented as continuous spatial codes of the olfactory bulb glomerulus populatio

Statistical analysis of coding for molecular properties in the olfactory bulb

The relationship between molecular properties of odorants and neural activities is arguably one of the most important issues in olfaction and the rules governing this relationship are still not clear. In the olfactory bulb (OB), glomeruli relay olfactory information to second-order neurons which in turn project to cortical areas. We investigate relevance of odorant properties, spatial localization of glomerular coding sites, and size of coding zones in a dataset of [14C] 2-deoxyglucose images of glomeruli over the entire OB of the rat. We relate molecular properties to activation of glomeruli in the OB using a non-parametric statistical test and a support-vector machine classification study. Our method permits to systematically map the topographic representation of various classes of odorants in the OB. Our results suggest many localized coding sites for particular molecular properties and some molecular properties that could form the basis for a spatial map of olfactory information. We found that alkynes, alkanes, alkenes, and amines affect activation maps very strongly as compared to other properties and that amines, sulfur-containing compounds, and alkynes have small zones and high relevance to activation changes, while aromatics, alkanes, and carboxylics acid recruit very big zones in the dataset. Results suggest a local spatial encoding for molecular properties