Publications

by Keyword: MOX


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Solórzano, A., Rodríguez-Pérez, R., Padilla, M., Graunke, T., Fernandez, L., Marco, S., Fonollosa, J., (2018). Multi-unit calibration rejects inherent device variability of chemical sensor arrays Sensors and Actuators B: Chemical 265, 142-154

Inherent sensor variability limits mass-production applications for metal oxide (MOX) gas sensor arrays because calibration for replicas of a sensor array needs to be performed individually. Recently, calibration transfer strategies have been proposed to alleviate calibration costs of new replicas, but they still require the acquisition of transfer samples. In this work, we present calibration models that can be extended to uncalibrated replicas of sensor arrays without acquiring new samples, i.e., general or global calibration models. The developed methodology consists in including multiple replicas of a sensor array in the calibration process such that sensor variability is rejected by the general model. Our approach was tested using replicas of a MOX sensor array in the classification task of six gases and synthetic air, presented at different background humidity and concentration levels. Results showed that direct transfer of individual calibration models provides poor classification accuracy. However, we also found that general calibration models kept predictive performance when were applied directly to new copies of the sensor array. Moreover, we explored, through feature selection, whether particular combinations of sensors and operating temperatures can provide predictive performances equivalent to the calibration model with the complete array, favoring thereby the existence of more robust calibration models.

Keywords: Gas sensor array, MOX sensor, Robust calibration, Calibration transfer, Machine olfaction


Fernandez, L., Yan, J., Fonollosa, J., Burgués, J., Gutierrez, A., Marco, S., (2018). A practical method to estimate the resolving power of a chemical sensor array: Application to feature selection Frontiers in Chemistry 6, Article 209

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.

Keywords: Gas sensor array, MOX sensors, Resolving Power, Sensor resolution, Dimensionality reduction, Machine olfaction


Burgues, J., Fonollosa, J., Marco, S., (2017). Discontinuously operated MOX sensors for low power applications IEEE Conference Publications ISOCS/IEEE International Symposium on Olfaction and Electronic Nose (ISOEN) , IEEE (Montreal, Canada) , 1-3

Metal oxide semiconductor sensors are limited by their low selectivity, high power consumption and temporal drift. This paper proposes a novel discontinuous temperature modulation operation mode characterized by on-demand measurements and periodic warm-up cycles. The performance of two sets of FIS SB-500-12 sensors, one group continuously operated and the other group discontinuously operated, was compared in a scenario of carbon monoxide detection at low concentrations for five consecutive days. Results showed that the discontinuous operating mode moderately increased the prediction error and the limit of detection but was advantageous in terms of energy savings (up to 60% with respect to the continuous temperature modulation mode).

Keywords: Discontinuous operation, Duty-cycling, Low power, MOX sensors, Temperature modulation


Fonollosa, J., Fernández, L., Gutiérrez-Gálvez, A., Huerta, R., Marco, S., (2016). Calibration transfer and drift counteraction in chemical sensor arrays using Direct Standardization Sensors and Actuators B: Chemical 236, 1044-1053

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.

Keywords: Calibration transfer, Chemical sensors, Direct Standardization, Electronic nose, MOX sensors, Public dataset


Fernandez, L., Guney, S., Gutierrez-Galvez, A., Marco, S., (2016). Calibration transfer in temperature modulated gas sensor arrays Sensors and Actuators B: Chemical 231, 276-284

Abstract 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.

Keywords: Calibration transfer, Gas sensor array, MOX, Temperature modulation


Huerta, R., Mosqueiro, T., Fonollosa, J., Rulkov, N.F., Rodríguez-Lujan, I., (2016). Online decorrelation of humidity and temperature in chemical sensors for continuous monitoring Chemometrics and Intelligent Laboratory Systems 157, 169-176

A method for online decorrelation of chemical sensor signals from the effects of environmental humidity and temperature variations is proposed. The goal is to improve the accuracy of electronic nose measurements for continuous monitoring by processing data from simultaneous readings of environmental humidity and temperature. The electronic nose setup built for this study included eight metal-oxide sensors, temperature and humidity sensors with a wireless communication link to external computer. This wireless electronic nose was used to monitor the air for two years in the residence of one of the authors and it collected data continuously during 537 days with a sampling rate of 1 sample per second. To estimate the effects of variations in air humidity and temperature on the chemical sensors' signals, we used a standard energy band model for an n-type metal-oxide (MOX) gas sensor. The main assumption of the model is that variations in sensor conductivity can be expressed as a nonlinear function of changes in the semiconductor energy bands in the presence of external humidity and temperature variations. Fitting this model to the collected data, we confirmed that the most statistically significant factors are humidity changes and correlated changes of temperature and humidity. This simple model achieves excellent accuracy with a coefficient of determination R2 close to 1. To show how the humidity–temperature correction model works for gas discrimination, we constructed a model for online discrimination among banana, wine and baseline response. This shows that pattern recognition algorithms improve performance and reliability by including the filtered signal of the chemical sensors.

Keywords: Electronic nose, Chemical sensors, Humidity, Temperature, Decorrelation, Wireless e-nose, MOX sensors, Energy band model, Home monitoring


Ziyatdinov, Andrey, Fonollosa, Jordi, Fernández, Luis, Gutiérrez-Gálvez, Agustín, Marco, Santiago, Perera, Alexandre, (2015). Data set from gas sensor array under flow modulation Data in Brief 3, 131-136

Abstract Recent studies in neuroscience suggest that sniffing, namely sampling odors actively, plays an important role in olfactory system, especially in certain scenarios such as novel odorant detection. While the computational advantages of high frequency sampling have not been yet elucidated, here, in order to motivate further investigation in active sampling strategies, we share the data from an artificial olfactory system made of 16 MOX gas sensors under gas flow modulation. The data were acquired on a custom set up featured by an external mechanical ventilator that emulates the biological respiration cycle. 58 samples were recorded in response to a relatively broad set of 12 gas classes, defined from different binary mixtures of acetone and ethanol in air. The acquired time series show two dominant frequency bands: the low-frequency signal corresponds to a conventional response curve of a sensor in response to a gas pulse, and the high-frequency signal has a clear principal harmonic at the respiration frequency. The data are related to the study in [1], and the data analysis results reported there should be considered as a reference point.

Keywords: Gas sensor array, MOX sensor, Flow modulation, Early detection, Biomimetics, Respiration, Sniffing


Ziyatdinov, Andrey, Fonollosa, Jordi, Fernánndez, Luis, Gutierrez-Gálvez, Agustín, Marco, Santiago, Perera, Alexandre, (2015). Bioinspired early detection through gas flow modulation in chemo-sensory systems Sensors and Actuators B: Chemical 206, 538-547

Abstract 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.11 http://archive.ics.uci.edu/ml/datasets/Gas+sensor+array+under+flow+modulation.

Keywords: Gas sensor array, MOX sensor, Flow modulation, Early detection, Biomimetics, Sniffing


Fernandez, L., Marco, S., Gutierrez-Galvez, A., (2015). Robustness to sensor damage of a highly redundant gas sensor array Sensors and Actuators B: Chemical 218, 296-302

Abstract In this paper we study the role of redundant sensory information to prevent the performance degradation of a chemical sensor array for different distributions of sensor failures across sensor types. The large amount of sensing conditions with two different types of redundancy provided by our sensor array makes possible a comprehensive experimental study. Particularly, our sensor array is composed of 8 different types of commercial MOX sensors modulated in temperature with two redundancy levels: (1) 12 replicates of each sensor type for a total of 96 sensors and (2) measurements using 16 load resistors per sensors for a total of 1536 redundant measures per second. We perform two experiments to determine the performance degradation of the array with increasing number of damaged sensors in two different scenarios of sensor faults distributions across sensor types. In the first experiment, we characterize the diversity and redundancy of the array for increasing number of damaged sensors. To measure diversity and redundancy, we proposed a functional definition based on clustering of sensor features. The second experiment is devoted to determine the performance degradation of the array for the effect of faulty sensors. To this end, the system is trained to separate ethanol, acetone and butanone at different concentrations using a PCA–LDA model. Test set samples are corrupted by means of three different simulated types of faults. To evaluate the performance of the array we used the Fisher score as a measure of odour separability. Our results show that to exploit to the utmost the redundancy of the sensor array faulty sensory units have to be distributed uniformly across the different sensor types.

Keywords: Gas sensor arrays, Sensor redundancy, Sensor diversity, Sensor faults aging, Sensor damage, MOX sensors, Large sensor arrays


Fonollosa, J., Neftci, E., Huerta, R., Marco, S., (2015). Evaluation of calibration transfer strategies between Metal Oxide gas sensor arrays Procedia Engineering EUROSENSORS 2015 , Elsevier (Freiburg, Germany) 120, 261-264

Abstract Inherent variability of chemical sensors makes necessary individual calibration of chemical detection systems. This shortcoming has traditionally limited usability of systems based on Metal Oxide (MOX) sensor arrays and prevented mass-production for some applications. Here, aiming at exploring transfer calibration between electronic nose systems, we exposed five identical 8-sensor detection units to controlled gas conditions. Our results show that a calibration model provides more accurate predictions when the tested board is included in the calibration dataset. However, we show that previously built calibration models can be extended to other units using a reduced number of measurements. While baseline correction seems imperative for successful baseline correction, among the different tested strategies, piecewise direct standardization provides more accurate predictions.

Keywords: Electronic nose, Calibration, MOX sensor, Machine Olfaction


Fernandez, L., Gutierrez-Galvez, A., Marco, S., (2014). Robustness to sensor damage of a highly redundant gas sensor array Procedia Engineering 28th European Conference on Solid-State Transducers (EUROSENSORS 2014) , Eurosensors (Brescia, Italy) 87, 851-854

Abstract In this paper we study the role of redundant sensory information to prevent the performance degradation of a chemical sensor array as the number of faulty sensors increases. The large amount of sensing conditions with two different types of redundancy provided by our sensor array makes possible a comprehensive experimental study. Particularly, our sensor array is composed of 8 different types of commercial MOX sensors modulated in temperature with two redundancy levels: 1) 12 replicates of each sensor type for a total of 96 sensors, and 2) measurements using 16 load resistors per sensors for a total of 1536 redundant measures per second. The system is trained to identify ethanol, acetone and butanone using a PCA-LDA model. Test set samples are corrupted by means of three different simulated types of faults. To evaluate the tolerance of the array against sensor failure, the Fisher Score is used as a figure of merit for the corrupted test set samples projected on the PCA-LDA model.

Keywords: Gas ensor arrays, sensor redundancy, MOX sensors, large sensor arrays.


Fonollosa, Jordi, Fernérndez, Luis, Huerta, Ramón, Gutiérrez-Gálvez, Agustín, Marco, Santiago, (2013). Temperature optimization of metal oxide sensor arrays using Mutual Information Sensors and Actuators B: Chemical Elsevier 187, (0), 331-339

The sensitivity and selectivity of metal oxide (MOX) gas sensors change significantly when the sensors operate at different temperatures. While previous investigations have presented systematic approaches to optimize the operating temperature of a single MOX sensor, in this paper we present a methodology to select the optimal operating temperature of all the MOX sensors constituent of a gas sensor array based on the multivariate response of all the sensing elements. Our approach estimates a widely used Information Theory measure, the so-called Mutual Information (MI), which quantifies the amount of information that the state of one random variable (response of the gas sensor array) can provide from the state of another random variable representing the gas quality. More specifically, our methodology builds sensor models from experimental data to solve the technical problem of populating the joint probability distribution for the MI estimation. We demonstrate the relevance of our approach by maximizing the MI and selecting the best operating temperatures of a four-sensor array sampled at 94 different temperatures to optimize the discrimination task of ethanol, acetic acid, 2-butanone, and acetone. In addition to being applicable in principle to sensor arrays of any size, our approach gives precise information on the ability of the system to discriminate odors according to the temperature of the MOX sensors, for either the optimal set of temperatures or the temperatures that may render inefficient operation of the system itself.

Keywords: MOX gas sensor, Temperature optimization, Limit of detection, Mutual Information, E-nose, Sensor array, Information Theory, Chemical sensing


Fernandez, L., Gutierrez-Galvez, A., Marco, S., (2013). Multi-way analysis of diversity and redundancy factors in large MOX gas sensor data Metal Oxide-based Sensors 14th International Meeting on Chemical Sensors - IMCS 2012 , AMA Science Portal (Nuremberg, Germany) P2.07, 1279-1280

We propose the use of multi-way methods to analyze the contribution of diversity and redundancy to odor identification and concentration estimation in a large chemical sensor array. We use a chemical sensing system based on a large array of metal oxide sensors (MOX) and inspired on the diversity and redundancy of the olfactory epithelium. In order to analyze the role of diversity (different sensor type and temperature modulation) and redundancy (replicates of sensors and different load resistors) in odor quantification and discrimination tasks, we have acquired two datasets and modeled the data using multi-way techniques.

Keywords: Artificial Olfaction, Large array, MOX gas sensor, Multi-way methods


Fernandez, L., Gutierrez-Galvez, A., Marco, S., (2010). Gas sensor array system inspired on the sensory diversity and redundancy of the olfactory epithelium Procedia Engineering Eurosensor XXIV Conference (ed. Jakoby, B., Vellekoop, M.J.), Elsevier Science BV (Linz, Austria) 5, (0), 25-28

This paper presents a chemical sensing system that takes inspiration from the combination of sensory diversity and redundancy at the olfactory epithelium to enhance the chemical information obtained from the odorants. The system is based on commercial MOS sensors and achieves, first, diversity trough different types of MOS along with modulation of their temperatures, and second redundancy including 12 MOS sensors for each type (12×8) combined with a high-speed multiplexing system that allows connecting 16 load resistors with each and every one of the 96 sensors in about two seconds. Exposition of the system to ethanol, ammonia, and acetone at different concentrations shows how the system is able to capture a large amount of information of the identity and the concentration of the odorant.

Keywords: Gas sensor array, Biologically inspired system, Redundancy, Diversity, MOX sensors, Temperature modulation


Díez-Pérez, Ismael, Guell, Aleix Garcia, Sanz, Fausto, Gorostiza, Pau, (2006). Conductance maps by electrochemical tunneling spectroscopy to fingerprint the electrode electronic structure Analytical Chemistry 78, (20), 7325-7329

We describe a methodology to perform reliable tunneling spectroscopy in electrochemical media. Sequential in situ tunneling spectra are recorded while the electrochemical potential of the electrode is scanned. Spectroscopic data are presented as conductance maps or conductograms that show the in situ electronic structure of an electrode surface while it undergoes an electrochemical reaction. The conductance map or conductogram represents the redox fingerprint of an electrode/liquid interface in a specific medium and can serve to predict its electrochemical behavior in a quantitative energy scale. The methodology is validated studying the reversible oxidation and passivity of an iron electrode in borate buffer, and we describe the main quantitative information that can be extracted concerning the semiconducting properties of the Fe passive film. This methodology is useful to study heterogeneous catalysis, electrochemical sensing and bioelectronic systems.

Keywords: Passive film, Oxide-film, Stainless-steel, Iron, Microscope, Surfaces, STM, Probes