Staff member


Santiago Marco Colás

Group Leader
Signal and Information Processing for Sensing Systems
smarco@ibecbarcelona.eu
+34 934 039 736
CV Summary

Dr. Santiago Marco is Titular Professor at the Electronics Department in the University of Barcelona (UB) since 1995. He obtained his degree in and his PhD in Physics from the UB in 1988 and 1993 respectively. In 1994 he was a post-doc at the University of Rome "Tor Vergata", working on Data Processing for Artificial Olfaction. In 2004 he was in a sabbatical leave at the EADS-Corporate Research in Munich working in Ion Mobility Spectrometry.

Staff member publications

Pomareda, V., Magrans, R., Jiménez-Soto, J., Martínez, D., Tresánchez, M., Burgués, J., Palacín, J., Marco, S., (2017). Chemical source localization fusing concentration information in the presence of chemical background noise Sensors 17, (4), 904

We present the estimation of a likelihood map for the location of the source of a chemical plume dispersed under atmospheric turbulence under uniform wind conditions. The main contribution of this work is to extend previous proposals based on Bayesian inference with binary detections to the use of concentration information while at the same time being robust against the presence of background chemical noise. For that, the algorithm builds a background model with robust statistics measurements to assess the posterior probability that a given chemical concentration reading comes from the background or from a source emitting at a distance with a specific release rate. In addition, our algorithm allows multiple mobile gas sensors to be used. Ten realistic simulations and ten real data experiments are used for evaluation purposes. For the simulations, we have supposed that sensors are mounted on cars which do not have among its main tasks navigating toward the source. To collect the real dataset, a special arena with induced wind is built, and an autonomous vehicle equipped with several sensors, including a photo ionization detector (PID) for sensing chemical concentration, is used. Simulation results show that our algorithm, provides a better estimation of the source location even for a low background level that benefits the performance of binary version. The improvement is clear for the synthetic data while for real data the estimation is only slightly better, probably because our exploration arena is not able to provide uniform wind conditions. Finally, an estimation of the computational cost of the algorithmic proposal is presented.

Keywords: Machine olfaction, Odor robots, Chemical sensors, Bayesian inference


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


Martínez, D., Moreno, J., Tresanchez, M., Clotet, E., Jiménez-Soto, J.M., Magrans, R., Pardo, A., Marco, S., Palacín, J., (2016). Measuring gas concentration and wind intensity in a turbulent wind tunnel with a mobile robot Journal of Sensors 2016, Article ID 7184980

This paper presents the measurement of gas concentration and wind intensity performed with a mobile robot in a custom turbulent wind tunnel designed for experimentation with customizable wind and gas leak sources. This paper presents the representation in different information layers of the measurements obtained in the turbulent wind tunnel under different controlled environmental conditions in order to describe the plume of the gas and wind intensities inside the experimentation chamber. The information layers have been generated from the measurements gathered by individual onboard gas and wind sensors carried out by an autonomous mobile robot. On the one hand, the assumption was that the size and cost of these specialized sensors do not allow the creation of a net of sensors or other measurement alternatives based on the simultaneous use of several sensors, and on the other hand, the assumption is that the information layers created will have application on the development and test of automatic gas source location procedures based on reactive or nonreactive algorithms.


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


Fonollosa, J., Sheik, S., Huerta, R., Marco, S., (2015). Reservoir computing compensates slow response of chemosensor arrays exposed to fast varying gas concentrations in continuous monitoring Sensors and Actuators B: Chemical 215, 618-629

Metal oxide (MOX) gas sensors arrays are a predominant technological choice to perform fundamental tasks of chemical detection. Yet, their use has been mainly limited to relatively controlled instrument configurations where the sensor array is placed within a closed measurement chamber. Usually, the experimental protocol is defined beforehand and it includes three stages: the array is first exposed to a gas reference, then to the gas sample, and finally to the reference again to recover the initial state. Such sampling procedure requires signal acquisition during the complete experimental protocol and usually delays the output prediction until the predefined measurement duration is complete. Due to the slow time response of chemical sensors, the completion of the measurement typically requires minutes. In this paper we propose the use of reservoir computing (RC) algorithms to overcome the slow temporal dynamics of chemical sensor arrays, allowing identification and quantification of chemicals of interest continuously and reducing measurement delays. We generated two datasets to test the ability of RC algorithms to provide accurate and continuous prediction to fast varying gas concentrations in real time. Both datasets - one generated with synthetic data and the other acquired from actual gas sensors - provide time series of MOX sensors exposed to binary gas mixtures where concentration levels change randomly over time. Our results show that our approach improves the time response of the sensory system and provides accurate predictions in real time, making the system specifically suitable for online monitoring applications. Finally, the collected dataset and developed code are made publicly available to the research community for further studies.

Keywords: Chemical sensors, Continuous gas prediction, Electronic nose, Real-time detection, Reservoir computing


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


Maynou, Joan, Pairo, Erola, Marco, Santiago, Perera, Alexandre, (2015). Sequence information gain based motif analysis BMC Bioinformatics 16, (1), 377

BACKGROUND:The detection of regulatory regions in candidate sequences is essential for the understanding of the regulation of a particular gene and the mechanisms involved. This paper proposes a novel methodology based on information theoretic metrics for finding regulatory sequences in promoter regions.RESULTS:This methodology (SIGMA) has been tested on genomic sequence data for Homo sapiens and Mus musculus. SIGMA has been compared with different publicly available alternatives for motif detection, such as MEME/MAST, Biostrings (Bioconductor package), MotifRegressor, and previous work such Qresiduals projections or information theoretic based detectors. Comparative results, in the form of Receiver Operating Characteristic curves, show how, in 70 % of the studied Transcription Factor Binding Sites, the SIGMA detector has a better performance and behaves more robustly than the methods compared, while having a similar computational time. The performance of SIGMA can be explained by its parametric simplicity in the modelling of the non-linear co-variability in the binding motif positions.CONCLUSIONS:Sequence Information Gain based Motif Analysis is a generalisation of a non-linear model of the cis-regulatory sequences detection based on Information Theory. This generalisation allows us to detect transcription factor binding sites with maximum performance disregarding the covariability observed in the positions of the training set of sequences. SIGMA is freely available to the public at http://b2slab.upc.edu.


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


Oller-Moreno, S., Singla-Buxarrais, G., Jiménez-Soto, J. M., Pardo, Antonio, Garrido-Delgado, R., Arce, L., Marco, Santiago, (2015). Sliding window multi-curve resolution: Application to gas chromatography - Ion Mobility Spectrometry Sensors and Actuators B: Chemical 15th International Meeting on Chemical Sensors , Elsevier (Buenos Aires, Argentina) 217, 13-21

Abstract Blind Source Separation (BSS) techniques aim to extract a set of source signals from a measured mixture in an unsupervised manner. In the chemical instrumentation domain source signals typically refer to time-varying analyte concentrations, while the measured mixture is the set of observed spectra. Several techniques exist to perform BSS on Ion Mobility Spectrometry, being Simple-to-use interactive self-modeling mixture analysis (SIMPLISMA) and Multivariate Curve Resolution (MCR) the most commonly used. The addition of a multi-capillary gas chromatography column using the ion mobility spectrometer as detector has been proposed in the past to increase chemical resolution. Short chromatography times lead to high levels of co-elution, and ion mobility spectra are key to resolve them. For the first time, BSS techniques are used to deconvolve samples of the gas chromatography - ion mobility spectrometry tandem. We propose a method to extract spectra and concentration profiles based on the application of MCR in a sliding window. Our results provide clear concentration profiles and pure spectra, resolving peaks that were not detected by the conventional use of MCR. The proposed technique could also be applied to other hyphenated instruments with similar strong co-elutions.

Keywords: Blind Source Separation, Multivariate Curve Resolution, Ion Mobility Spectrometry, Gas Chromatography, Hyphenated instrumentation, SIMPLISMA, co-elution


Palleja, T., Balsa, R., Tresanchez, M., Moreno, J., Teixido, M., Font, D., Marco, S., Pomareda, V., Palacin, J., (2014). Corridor gas-leak localization using a mobile Robot with a photo ionization detector sensor Sensor Letters 12, (6-7), 974-977

The use of an autonomous mobile robot to locate gas-leaks and air quality monitoring in indoor environments are promising tasks that will avoid risky human operations. However, these are challenging tasks due to the chaotic gas profile propagation originated by uncontrolled air flows. This paper proposes the localization of an acetone gas-leak in a 44 m-length indoor corridor with a mobile robot equipped with a PID sensor. This paper assesses the influence of the mobile robot velocity and the relative height of the PID sensor in the profile of the measurements. The results show weak influence of the robot velocity and strong influence of the relative height of the PID sensor. An estimate of the gas-leak location is also performed by computing the center of mass of the highest gas concentrations.

Keywords: Gas source detection, LIDAR sensor, Mobile robot, PID sensor, SLAM, Acetone, Air quality, Gases, Indoor air pollution, Mobile robots, Robots, Air quality monitoring, Autonomous Mobile Robot, Gas sources, Indoor environment, Leak localization, LIDAR sensors, Profile propagation, SLAM, Ionization of gases


Fonollosa, Jordi, Vergara, Alexander, Huerta, R., Marco, Santiago, (2014). Estimation of the limit of detection using information theory measures Analytica Chimica Acta 810, 1-9

Abstract Definitions of the limit of detection (LOD) based on the probability of false positive and/or false negative errors have been proposed over the past years. Although such definitions are straightforward and valid for any kind of analytical system, proposed methodologies to estimate the LOD are usually simplified to signals with Gaussian noise. Additionally, there is a general misconception that two systems with the same LOD provide the same amount of information on the source regardless of the prior probability of presenting a blank/analyte sample. Based upon an analogy between an analytical system and a binary communication channel, in this paper we show that the amount of information that can be extracted from an analytical system depends on the probability of presenting the two different possible states. We propose a new definition of LOD utilizing information theory tools that deals with noise of any kind and allows the introduction of prior knowledge easily. Unlike most traditional LOD estimation approaches, the proposed definition is based on the amount of information that the chemical instrumentation system provides on the chemical information source. Our findings indicate that the benchmark of analytical systems based on the ability to provide information about the presence/absence of the analyte (our proposed approach) is a more general and proper framework, while converging to the usual values when dealing with Gaussian noise.

Keywords: Limit of detection, Information theory, Mutual information, Heteroscedasticity, False positive/negative errors, Gas discrimination and quantification


Marco, Santiago, (2014). The need for external validation in machine olfaction: emphasis on health-related applications Analytical and Bioanalytical Chemistry Springer Berlin Heidelberg 406, (16), 3941-3956

Over the last two decades, electronic nose research has produced thousands of research works. Many of them were describing the ability of the e-nose technology to solve diverse applications in domains ranging from food technology to safety, security, or health. It is, in fact, in the biomedical field where e-nose technology is finding a research niche in the last years. Although few success stories exist, most described applications never found the road to industrial or clinical exploitation. Most described methodologies were not reliable and were plagued by numerous problems that prevented practical application beyond the lab. This work emphasizes the need of external validation in machine olfaction. I describe some statistical and methodological pitfalls of the e-nose practice and I give some best practice recommendations for researchers in the field.

Keywords: Chemical sensor arrays, Pattern recognition, Chemometrics, Electronic noses, Robustness, Signal and data processing


Polese, Davide, Martinelli, Eugenio, Marco, Santiago, Di Natale, Corrado, Gutierrez-Galvez, Agustin, (2014). Understanding odor information segregation in the olfactory bulb by means of mitral and tufted cells PLoS ONE 9, (10), e109716

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.


Martinez, Dani, Teixidó, Mercè, Font, Davinia, Moreno, Javier, Tresanchez, Marcel, Marco, Santiago, Palacín, Jordi, (2014). Ambient intelligence application based on environmental measurements performed with an assistant mobile robot Sensors 14, (4), 6045-6055

This paper proposes the use of an autonomous assistant mobile robot in order to monitor the environmental conditions of a large indoor area and develop an ambient intelligence application. The mobile robot uses single high performance embedded sensors in order to collect and geo-reference environmental information such as ambient temperature, air velocity and orientation and gas concentration. The data collected with the assistant mobile robot is analyzed in order to detect unusual measurements or discrepancies and develop focused corrective ambient actions. This paper shows an example of the measurements performed in a research facility which have enabled the detection and location of an uncomfortable temperature profile inside an office of the research facility. The ambient intelligent application has been developed by performing some localized ambient measurements that have been analyzed in order to propose some ambient actuations to correct the uncomfortable temperature profile.

Keywords: Ambient intelligence, Human thermal comfort, Robotic exploration


Bennetts, Victor, Schaffernicht, Erik, Pomareda, Victor, Lilienthal, Achim, Marco, Santiago, Trincavelli, Marco, (2014). Combining non selective gas sensors on a mobile robot for identification and mapping of multiple chemical compounds Sensors 14, (9), 17331-17352

In this paper, we address the task of gas distribution modeling in scenarios where multiple heterogeneous compounds are present. Gas distribution modeling is particularly useful in emission monitoring applications where spatial representations of the gaseous patches can be used to identify emission hot spots. In realistic environments, the presence of multiple chemicals is expected and therefore, gas discrimination has to be incorporated in the modeling process. The approach presented in this work addresses the task of gas distribution modeling by combining different non selective gas sensors. Gas discrimination is addressed with an open sampling system, composed by an array of metal oxide sensors and a probabilistic algorithm tailored to uncontrolled environments. For each of the identified compounds, the mapping algorithm generates a calibrated gas distribution model using the classification uncertainty and the concentration readings acquired with a photo ionization detector. The meta parameters of the proposed modeling algorithm are automatically learned from the data. The approach was validated with a gas sensitive robot patrolling outdoor and indoor scenarios, where two different chemicals were released simultaneously. The experimental results show that the generated multi compound maps can be used to accurately predict the location of emitting gas sources.

Keywords: Environmental monitoring, Gas discrimination, Gas distribution mapping, Service robots, Open sampling systems, PID, Metal oxide sensors


Marco, S., Gutiérrez-Gálvez, A., Lansner, A., Martinez, D., Rospars, J. P., Beccherelli, R., Perera, A., Pearce, T. C., Verschure, P. F. M. J., Persaud, K., (2014). A biomimetic approach to machine olfaction, featuring a very large-scale chemical sensor array and embedded neuro-bio-inspired computation Microsystem Technologies 20, (4-5), 729-742

Biological olfaction outperforms chemical instrumentation in specificity, response time, detection limit, coding capacity, time stability, robustness, size, power consumption, and portability. This biological function provides outstanding performance due, in a large extent, to the unique architecture of the olfactory pathway, which combines a high degree of redundancy and efficient combinatorial coding, with unmatched chemical information processing mechanisms. The last decade has seen important advances in the understanding of the computational primitives underlying the functioning of the olfactory system. The EU-funded Project NEUROCHEM (Bio-ICT-FET- 216916) developed novel computing paradigms and biologically motivated artefacts for chemical sensing, taking its inspiration from the biological olfactory pathway. To demonstrate this approach, a biomimetic demonstrator has been built that features a very large-scale sensor array (65,536 elements) using conducting polymer technology which mimics the olfactory receptor neuron layer. It implements derived computational neuroscience algorithms in an embedded system that interfaces the chemical sensors and processes their signals in real-time. This embedded system integrates abstracted computational models of the main anatomic building blocks in the olfactory pathway: the olfactory bulb, and olfactory cortex in vertebrates (respectively, antennal lobe and mushroom bodies in the insect). For implementation in the embedded processor, an abstraction phase has been carried out in which their processing capabilities are captured by algorithmic solutions implemented in software. Finally, the algorithmic models are tested in mixed chemical plumes with an odour robot having navigation capabilities.


Oller-Moreno, S., Pardo, A., Jimenez-Soto, J. M., Samitier, J., Marco, S., (2014). Adaptive Asymmetric Least Squares baseline estimation for analytical instruments SSD 2014 Proceedings 11th International Multi-Conference on Systems, Signals & Devices (SSD) , IEEE (Castelldefels-Barcelona, Spain) , 1569846703

Automated signal processing in analytical instrumentation is today required for the analysis of highly complex biomedical samples. Baseline estimation techniques are often used to correct long term instrument contamination or degradation. They are essential for accurate peak area integration. Some methods approach the baseline estimation iteratively, trying to ignore peaks which do not belong to the baseline. The proposed method in this work consists of a modification of the Asymmetric Least Squares (ALS) baseline removal technique developed by Eilers and Boelens. The ALS technique suffers from bias in the presence of intense peaks (in relation to the noise level). This is typical of diverse instrumental techniques such as Gas Chromatography-Mass Spectrometry (GC-MS) or Gas Chromatography-Ion Mobility Spectrometry (GC-IMS). In this work, we propose a modification (named psalsa) to the asymmetry weights of the original ALS method in order to better reject large peaks above the baseline. Our method will be compared to several versions of the ALS algorithm using synthetic and real GC signals. Results show that our proposal improves previous versions being more robust to parameter variations and providing more accurate peak areas.

Keywords: Gas chromatography, Instruments, Radioactivity measurement, Signal processing, Analytical instrument, Analytical Instrumentation, Asymmetric least squares, Baseline estimation, Baseline removal, Gas chromatography-mass spectrometries (GC-MS), Instrumental techniques, Noise levels, Iterative methods


Fernandez, L., Marco, S., (2014). Calibration transfer between e-noses Signal Processing and Communications Applications Conference (SIU) Signal Processing and Communications Applications Conference (SIU), 2014 22nd , IEEE (Trabzon, Turkey) , 650-653

Electronic nose is an instrument which is composed of gas sensor array and pattern recognition unit. It is generally used for classifying, identifying or quantifying the odors or volatile organic components for these commonly used devices, calibration transfer is an important issue because of differences in each instrument, sensor drift, changes in environmental conditions or background changes. Calibration transfer is a transfer of model between different instruments which have different conditions. In this study, calibration transfer is applied to the e-noses which have different temperature conditions. Also the results of the direct standardization, piecewise direct standardization and orthogonal signal correction which are different calibration methods were compared. The results of the piecewise direct standardization method are more successful than the other methods for the dataset which is used in this study.

Keywords: Calibration, Conferences, Electronic noses, Ethanol, Instruments, Signal processing, Standardization


Sheik, S., Marco, S., Huerta, R., Fonollosa, J., (2014). Continuous prediction in chemoresisitive gas sensors using reservoir computing Procedia Engineering 28th European Conference on Solid-State Transducers (EUROSENSORS 2014) , Eurosensors (Brescia, Italy) 87, 843-846

Although Metal Oxide (MOX) sensors are predominant choices to perform fundamental tasks of chemical detection, their use has been mainly limited to relatively controlled scenarios where a gas sensor array is first exposed to a reference, then to the gas sample, and finally to the reference again to recover the initial state. In this paper we propose the use of MOX sensors along with Reservoir Computing algorithms to identify chemicals of interest. Our approach allows continuous gas monitoring in simple experimental setups without the requirement of acquiring recovery transient of the sensors, thereby making the system specifically suitable for online monitoring applications.

Keywords: Chemical sensing, Reservoir computing, Gas sensors, Dynamic gas mixtures, Electronic nose


Martínez, D., Moreno, J., Tresanchez, M., Teixidó, M., Font, D., Pardo, A., Marco, S., Palacín, J., (2014). Experimental application of an autonomous mobile robot for gas leak detection in indoor environments 17th International Conference on Information Fusion (FUSION) , IEEE (Salamanca, Spain) , 1-6

This paper presents the experimental application of an autonomous mobile robot for gas leak detection in indoor environments. The application is focused to automatize a human-risky operation in indoor areas. The goal of the autonomous mobile robot is the localization of a toxic gas leak source. So, the mobile robot has to explore the whole area and perform an auto-localization procedure based on a SLAM method and a LIDAR sensor. The mobile robot measures gas concentration by using a photoionization detector. The experimentation was realized in a large indoor environment in a university facility with a simulated gas leak source. The combination of the results from the auto-localization procedure with the information of the sensors allows the estimation of the gas leak source location.


Martínez, D., Moreno, J., Tresanchez, M., Teixidó, M., Palací, J., Marco, S., (2014). Preliminary results on measuring gas and wind intensity with a mobile robot in an indoor area ETFA 2014 19th IEEE International Conference on Emerging Technologies and Factory Automation , IEEE (Barcelona, Spain) , 1-5

This paper presents the preliminary results obtained when using a mobile robot to measure gas and wind intensity in an indoor area by means of several attached sensors such as a LIDAR, an e-nose, and an anemometer. The robot navigation was performed by means of a random path planning and the robot self location was performed by means of an SLAM procedure. This paper presents the first preliminary results obtained in a set of measurement experiments. In all cases, the indoor area has a fixed artificial simulated airflow and an induced gas leak source placed in different locations of the experimentation area. Results have shown different gas diffusion profiles in the different experiments performed.


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.


Martínez, Dani, Pallejà, T., Moreno, Javier, Tresanchez, Marcel, Teixidó, M., Font, Davinia, Pardo, Antonio, Marco, Santiago, Palacín, Jordi, (2014). A mobile robot agent for gas leak source detection Advances in Intelligent Systems and Computing Trends in Practical Applications of Heterogeneous Multi-Agent Systems. The PAAMS Collection (ed. Bajo Perez, Javier, Corchado Rodríguez, Juan M., Mathieu, Philippe, Campbell, Andrew, Ortega, Alfonso, Adam, Emmanuel, Navarro, Elena M., Ahrndt, Sebastian, Moreno, Maríaa N., Julián, Vicente), Springer International Publishing 293, 19-25

This paper presents an autonomous agent for gas leak source detection. The main objective of the robot is to estimate the localization of the gas leak source in an indoor environment without any human intervention. The agent implements an SLAM procedure to scan and map the indoor area. The mobile robot samples gas concentrations with a gas and a wind sensor in order to estimate the source of the gas leak. The mobile robot agent will use the information obtained from the onboard sensors in order to define an efficient scanning path. This paper describes the measurement results obtained in a long corridor with a gas leak source placed close to a wall.

Keywords: Gas detection, Mobile robot agent, Laser sensor, Self-localization


Karpas, Z., Guamán, A. V., Pardo, A., Marco, S., (2013). Comparison of the performance of three ion mobility spectrometers for measurement of biogenic amines Analytica Chimica Acta 758, (3), 122-129

The performance of three different types of ion mobility spectrometer (IMS) devices: GDA2 with a radioactive ion source (Airsense, Germany), UV-IMS with a photo-ionization source (G.A.S. Germany) and VG-Test with a corona discharge source (3QBD, Israel) was studied. The gas-phase ion chemistry in the IMS devices affected the species formed and their measured reduced mobility values. The sensitivity and limit of detection for trimethylamine (TMA), putrescine and cadaverine were compared by continuous monitoring of a stream of air with a given concentration of the analyte and by measurement of headspace vapors of TMA in a sealed vial. Preprocessing of the mobility spectra and the effectiveness of multivariate curve resolution techniques (MCR-LASSO) improved the accuracy of the measurements by correcting baseline effects and adjusting for variations in drift time as well as enhancing the signal to noise ratio and deconvolution of the complex data matrix to their pure components. The limit of detection for measurement of the biogenic amines by the three IMS devices was between 0.1 and 1.2 ppm (for TMA with the VG-Test and GDA, respectively) and between 0.2 and 0.7 ppm for putrescine and cadaverine with all three devices. Considering the uncertainty in the LOD determination there is almost no statistically significant difference between the three devices although they differ in their operating temperature, ionization method, drift tube design and dopant chemistry. This finding may have general implications on the achievable performance of classic IMS devices.

Keywords: Biogenic amines, Comparison of performance, Ion mobility spectrometry, Sensitivity, Signal processing, Vapor concentration


Pomareda, Victor, Lopez-Vidal, Silvia, Calvo, Daniel, Pardo, Antonio, Marco, Santiago, (2013). A novel differential mobility analyzer as VOCs detector and multivariate techniques for identification and quantification Analyst 138, (12), 3512-3521

A Differential Mobility Analyser (DMA) is a specific configuration of an Ion Mobility Spectrometer (IMS) where ions with different electrical mobilities are separated in space, instead of in time of drift, as in classical drift-time IMS. This work presents an instrument developed by the company Ioner, a parallel plate DMA instrument, but with crucial differences in the sheath flow and detection system when compared to other instruments in the market. These differences improve the resolving powers and sensitivities of the instrument. Additionally, datasets from IMS or DMA instruments are typically processed with univariate techniques when only qualitative detection is of interest. However, good performance in quantitative measurements can be achieved using multivariate data processing. This work presents for the first time, measurements with a stand alone DMA instrument and the multivariate data processing related for VOCs and environmental interesting samples.


Ziyatdinov, A., Diaz, E. Fernández, Chaudry, A., Marco, S., Persaud, K., Perera, A., (2013). A software tool for large-scale synthetic experiments based on polymeric sensor arrays Sensors and Actuators B: Chemical 177, 596-604

This manuscript introduces a software tool that allows for the design of synthetic experiments in machine olfaction. The proposed software package includes both, a virtual sensor array that reproduces the diversity and response of a polymer array and tools for data generation. The synthetic array of sensors allows for the generation of chemosensor data with a variety of characteristics: unlimited number of sensors, support of multicomponent gas mixtures and full parametric control of the noise in the system. The artificial sensor array is inspired from a reference database of seventeen polymeric sensors with concentration profiles for three analytes. The main features in the sensor data, like sensitivity, diversity, drift and sensor noise, are captured by a set of models under simplified assumptions. The generator of sensor signals can be used in applications related to test and benchmarking of signal processing methods, neuromorphic simulations in machine olfaction and educational tools. The software is implemented in R language and can be freely accessed.

Keywords: Gas Sensor Array, Conducting Polymers, Electronic Nose, Sensor Simulation, Synthetic Dataset, Benchmark, Educational Tool


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


Marco, S., Gutiérrez-Gálvez, A., Lansner, A., Martinez, D., Rospars, J. P., Beccherelli, R., Perera, A., Pearce, T., Vershure, P., Persaud, K., (2013). Biologically inspired large scale chemical sensor arrays and embedded data processing Proceedings of SPIE - The International Society for Optical Engineering Smart Sensors, Actuators, and MEMS VI , SPIE Digital Library (Grenoble, France) 8763, 1-15

Biological olfaction outperforms chemical instrumentation in specificity, response time, detection limit, coding capacity, time stability, robustness, size, power consumption, and portability. This biological function provides outstanding performance due, to a large extent, to the unique architecture of the olfactory pathway, which combines a high degree of redundancy, an efficient combinatorial coding along with unmatched chemical information processing mechanisms. The last decade has witnessed important advances in the understanding of the computational primitives underlying the functioning of the olfactory system. EU Funded Project NEUROCHEM (Bio-ICT-FET- 216916) has developed novel computing paradigms and biologically motivated artefacts for chemical sensing taking inspiration from the biological olfactory pathway. To demonstrate this approach, a biomimetic demonstrator has been built featuring a large scale sensor array (65K elements) in conducting polymer technology mimicking the olfactory receptor neuron layer, and abstracted biomimetic algorithms have been implemented in an embedded system that interfaces the chemical sensors. The embedded system integrates computational models of the main anatomic building blocks in the olfactory pathway: The olfactory bulb, and olfactory cortex in vertebrates (alternatively, antennal lobe and mushroom bodies in the insect). For implementation in the embedded processor an abstraction phase has been carried out in which their processing capabilities are captured by algorithmic solutions. Finally, the algorithmic models are tested with an odour robot with navigation capabilities in mixed chemical plumes.

Keywords: Antennal lobes, Artificial olfaction, Computational neuroscience, Olfactory bulbs, Plume tracking, Abstracting, Actuators, Algorithms, Biomimetic processes, Chemical sensors, Conducting polymers, Data processing, Flavors, Odors, Robots, Smart sensors, Embedded systems


Santano-Martínez, R., Leiva-González, R., Avazbeigi, M., Gutiérrez-Gálvez, A., Marco, S., (2013). Identification of molecular properties coding areas in rat's olfactory bulb by rank products Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing BIOSIGNALS 2013 , SciTePress (Barcelona, Spain) , 383-387

Neural coding of chemical information is still under strong debate. It is clear that, in vertebrates, neural representation in the olfactory bulb is a key for understanding a putative odour code. To explore this code, in this work we have studied a public dataset of radio images of 2-Deoxyglucose uptake (2-DG) in the olfactory bulb of rats in response to diverse odorants using univariate pixel selection algorithms: rank-products and Mann-Whitney U (MWU) test. Initial results indicate that some chemical properties of odorants preferentially activate certain areas of the rat olfactory bulb. While non-parametric test (MWU) has difficulties to detect these regions, rank-product provides a higher power of detection.

Keywords: 2-Deoxyglucose uptake, Chemotopy, Feature selection, Odour coding, Olfaction, Olfactory bulb


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


Gutiérrez-Gálvez, A., Marco, S., (2013). Study of the coding efficiency of populations of olfactory receptor neurons and olfactory glomeruli Frontiers in Neuroengineering Series Neuromorphic Olfaction (ed. Persaud, K. , Marco, S., Gutiérrez-Gálvez, A.), CRC Press (London, UK) , 59-82

Persaud, K. , Marco, S., Gutiérrez-Gálvez, A., (2013). Neuromorphic Olfaction Frontiers in Neuroengineering Series Neuromorphic Olfaction , CRC Press (London, UK)

Pairó, Erola, Maynou, Joan, Marco, Santiago, Perera, Alexandre, (2012). A subspace method for the detection of transcription factor binding sites Bioinformatics 28, (10), 1328-1335

Motivation: The identification of the sites at which transcription factors (TF) bind to DNA is an important problem in molecular biology. Many computational methods have been developed for motif finding, most of them based on position-specific scoring matrices (PSSM) which assume the independence of positions within a binding site. However, some experimental and computational studies demonstrate that interdependences within the positions exist.Results: In this paper, we introduce a novel motif finding method which constructs a subspace based on the covariance of numerical DNA sequences. When a candidate sequence is projected into the modelled subspace, a threshold in the Q-residuals confidence allows us to predict whether this sequence is a binding site. Using the TRANSFAC and JASPAR databases, we compared our Q-residuals detector with existing PSSM methods. In most of the studied transcription factor binding sites, the Q-residuals detector performs significantly better and faster than MATCH and MAST. As compared to Motifscan, a method which takes into account inter-dependences, the performance of the Q-residuals detector is better when the number of available sequences is small.Availability: http://r-forge.r-project.org/projects/meetContact: epairo@ibecbarcelona.euSupplementary information: Supplementary data (1,2,3,4) are available at Bioinformatics On-line.


Fonollosa, Jordi, Gutierrez-Galvez, Agustin, Marco, Santiago, (2012). Quality coding by neural populations in the early olfactory pathway: Analysis using information theory and lessons for artificial olfactory systems PLoS ONE 7, (6), e37809

In this article, we analyze the ability of the early olfactory system to detect and discriminate different odors by means of information theory measurements applied to olfactory bulb activity images. We have studied the role that the diversity and number of receptor neuron types play in encoding chemical information. Our results show that the olfactory receptors of the biological system are low correlated and present good coverage of the input space. The coding capacity of ensembles of olfactory receptors with the same receptive range is maximized when the receptors cover half of the odor input space - a configuration that corresponds to receptors that are not particularly selective. However, the ensemble’s performance slightly increases when mixing uncorrelated receptors of different receptive ranges. Our results confirm that the low correlation between sensors could be more significant than the sensor selectivity for general purpose chemo-sensory systems, whether these are biological or biomimetic.


Udina, S., Carmona, M., Pardo, A., Calaza, C., Santander, J., Fonseca, L., Marco, S., (2012). A micromachined thermoelectric sensor for natural gas analysis: Multivariate calibration results Sensors and Actuators B: Chemical 166-167, 338-348

The potential use of a micromachined thermopile based sensor device for analyzing natural gas is explored. The sensor consists of a thermally isolated hotplate which is heated by the application of a sequence of programmed voltages to an integrated heater. Once the hotplate reaches a stationary temperature, the thermopile provides a signal proportional to the hotplate temperature. These signals are processed in order to determine different natural gas properties. Sensor response is mainly dependent on the thermal conductivity of the surrounding gas at different temperatures. Seven predicted properties (normal density, Superior Heating Value, Wobbe index and the concentrations of methane, ethane, carbon dioxide and nitrogen) are calibrated against sensor signals by using multivariate regression, in particular Partial Least Squares. Experimental data have been used for calibration and validation. Results show property prediction capability with reasonable accuracy except for prediction of carbon dioxide concentration. A detailed uncertainty analysis is provided to better understand the metrological limits of the system. These results imply for the first time the possibility of designing unprecedented low-cost natural gas analyzers. The concept may be extended to other constrained gas mixtures (e.g. of a known number of components) to enable low-cost multicomponent gas analyzers.

Keywords: Gas sensor, Natural gas, MEMS, Superior Heating Value, density, PLS


Karpas, Zeev, Guamán, Ana V., Calvo, Daniel, Pardo, Antonio, Marco, Santiago, (2012). The potential of ion mobility spectrometry (IMS) for detection of 2,4,6-trichloroanisole (2,4,6-TCA) in wine Talanta 93, 200-205

The off-flavor of “tainted wine” is attributed mainly to the presence of 2,4,6-trichloroanisole (2,4,6-TCA) in the wine. In the present study the atmospheric pressure gas-phase ion chemistry, pertaining to ion mobility spectrometry, of 2,4,6-trichloroanisole was investigated. In positive ion mode the dominant species is a monomer ion with a lower intensity dimer species with reduced mobility values (K0) of 1.58 and 1.20 cm2 V−1 s−1, respectively. In negative mode the ion with K0 = 1.64 cm2 V−1 s−1 is ascribed to a trichlorophenoxide species while the ions with K0 = 1.48 and 1.13 cm2 V−1 s−1 are attributed to chloride attachment adducts of a TCA monomer and dimer, respectively. The limit of detection of the system for 2,4,6-TCA dissolved in dichloromethane deposited on a filter paper was 2.1 ug and 1.7 ppm in the gas phase. In ethanol and in wine the limit of detection is higher implying that pre-concentration and pre-separation are required before IMS can be used to monitor the level of TCA in wine.

Keywords: 2,4,6-Trichloroanisole, Gas phase ion chemistry, Ion mobility spectrometry, "Tainted wine"


Falasconi, Matteo, Gutierrez-Galvez, Agustin, Leon, Michael, Johnson, Brett A., Marco, Santiago, (2012). Cluster analysis of rat olfactory bulb responses to diverse odorants Chemical Senses 37, (7), 639-653

In an effort to deepen our understanding of mammalian olfactory coding, we have used an objective method to analyze a large set of odorant-evoked activity maps collected systematically across the rat olfactory bulb to determine whether such an approach could identify specific glomerular regions that are activated by related odorants. To that end, we combined fuzzy c-means clustering methods with a novel validity approach based on cluster stability to evaluate the significance of the fuzzy partitions on a data set of glomerular layer responses to a large diverse group of odorants. Our results confirm the existence of glomerular response clusters to similar odorants. They further indicate a partial hierarchical chemotopic organization wherein larger glomerular regions can be subdivided into smaller areas that are rather specific in their responses to particular functional groups of odorants. These clusters bear many similarities to, as well as some differences from, response domains previously proposed for the glomerular layer of the bulb. These data also provide additional support for the concept of an identity code in the mammalian olfactory system.


Guamán, Ana V., Carreras, Alba, Calvo, Daniel, Agudo, Idoya, Navajas, Daniel, Pardo, Antonio, Marco, Santiago, Farré, Ramon, (2012). Rapid detection of sepsis in rats through volatile organic compounds in breath Journal of Chromatography B 881-882, 76-82

Background: Sepsis is one of the main causes of death in adult intensive care units. The major drawbacks of the different methods used for its diagnosis and monitoring are their inability to provide fast responses and unsuitability for bedside use. In this study, performed using a rat sepsis model, we evaluate breath analysis with Ion Mobility Spectrometry (IMS) as a fast, portable and non-invasive strategy. Methods: This study was carried out on 20 Sprague-Dawley rats. Ten rats were injected with lipopolysaccharide from Escherichia coli and ten rats were IP injected with regular saline. After a 24-h period, the rats were anaesthetized and their exhaled breaths were collected and measured with IMS and SPME-gas chromatography/mass spectrometry (SPME-GC/MS) and the data were analyzed with multivariate data processing techniques. Results: The SPME-GC/MS dataset processing showed 92% accuracy in the discrimination between the two groups, with a confidence interval of between 90.9% and 92.9%. Percentages for sensitivity and specificity were 98% (97.5–98.5%) and 85% (84.6–87.6%), respectively. The IMS database processing generated an accuracy of 99.8% (99.7–99.9%), a specificity of 99.6% (99.5–99.7%) and a sensitivity of 99.9% (99.8–100%). Conclusions: IMS involving fast analysis times, minimum sample handling and portable instrumentation can be an alternative for continuous bedside monitoring. IMS spectra require data processing with proper statistical models for the technique to be used as an alternative to other methods. These animal model results suggest that exhaled breath can be used as a point-of-care tool for the diagnosis and monitoring of sepsis.

Keywords: Sepsis, Volatile organic compounds, Ion mobility spectrometer, Rat model, Bedside patient systems, Non-invasive detection


Pomareda, Víctor, Guamán, Ana V., Mohammadnejad, Masoumeh, Calvo, Daniel, Pardo, Antonio, Marco, Santiago, (2012). Multivariate curve resolution of nonlinear ion mobility spectra followed by multivariate nonlinear calibration for quantitative prediction Chemometrics and Intelligent Laboratory Systems 118, 219-229

In this work, a new methodology to analyze spectra time-series obtained from ion mobility spectrometry (IMS) has been investigated. The proposed method combines the advantages of multivariate curve resolution-alternating least squares (MCR-ALS) for an optimal physical and chemical interpretation of the system (qualitative information) and a multivariate calibration technique such as polynomial partial least squares (poly-PLS) for an improved quantification (quantitative information) of new samples. Ten different concentrations of 2-butanone and ethanol were generated using a volatile generator based on permeation tubes. The different concentrations were measured with IMS. These data present a non-linear behaviour as substance concentration increases. Although MCR-ALS is based on a bilinear decomposition, non-linear behaviour can be modelled adding new components to the model. After spectral pre-processing, MCR-ALS was applied aiming to get information about the ionic species that appear in the drift tube and their evolution with the analyte concentration. By resolving the IMS data matrix, concentration profiles and pure spectra of the different ionic species have been obtained for both analytes. Finally, poly-PLS was used in order to build a calibration model using concentration profiles obtained from MCR-ALS for ethanol and 2-butanone. The results, with more than 99% of explained variance for both substances, show the feasibility of using MCR-ALS to resolve IMS datasets. Furthermore, similar or better prediction accuracy is achieved when concentration profiles from MCR-ALS are used to build a calibration model (using poly-PLS) compared to other standard univariate and multivariate calibration methodologies.

Keywords: Ion Mobility Spectrometry, Multivariate Curve Resolution, Gas phase ion chemistry, Multivariate calibration


Marco, S., Gutierrez-Galvez, A., (2012). Signal and data processing for machine olfaction and chemical sensing: A review IEEE Sensors Journal 12, (11), 3189-3214

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.

Keywords: Chemical sensors, Electronic nose, Intelligent sensors, Measurement techniques, Sensor arrays, Sensor systems


Bartra, A., Meca, P., Guamán, A., Pardo, A., Marco, S., Montesi, A., (2012). A feasability study of drowsiness detection using driving behaviour parameters IEEE Conference Publications IEEE Intelligent Vehicles Symposium (2012) , IEEE (Alcala de Henares, Spain) , 111-116

One of the main causes of car accidents is drowsiness. There have been many studies regarding driving monitoring systems in the past few years, although most of them are focused in simulator environments. This paper presents a system to detect drowsiness patterns in real driving environments, where many external conditions need to be taken into account. Initial tests were done in simulator, followed by tests in real vehicles. Although two different approaches have been developed, this paper is focused in the inadequate driving identification based on the steering movements. Its sub-modules are also presented, with a special focus on the active driving detector.

Keywords: -----


Auffarth, Benjamin, Gutierrez-Galvez, Agustín, Marco, Santiago, (2011). Continuous spatial representations in the olfactory bulb may reflect perceptual categories Frontiers in Systems Neuroscience 5, (82), 1-8

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 population.

Keywords: Glomeruli, Memory organization, Odor quality, Olfaction, Olfactory bulb, Perceptual categories, Population coding, Spatial coding


Auffarth, Benjamin, Gutierrez, Agustin, Marco, Santiago, (2011). Statistical analysis of coding for molecular properties in the olfactory bulb Frontiers in Systems Neuroscience 5, (62), 1-8

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 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 nonparametric 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.

Keywords: Molecular-receptive range, Odor, Olfactory bulb, Olfactory coding, Property-activity relationship, Structure-odor relationship


Calvo, Daniel, Tort, Nuria, Pablo Salvador, J., Marco, M. Pilar, Centi, Fabiana, Marco, Santiago, (2011). Preliminary study for simultaneous detection and quantification of androgenic anabolic steroids using ELISA and pattern recognition techniques Analyst 136, (-----), 4045-4052

A first step towards the multidetection, identification and quantification of anabolic androgenic steroids by enzyme-linked immunosorbent assay (ELISA) has been performed in this study. This proposal combines multiple competitive ELISA assays with different cross-reactivity profiles and multivariate data analysis techniques. Data have been analyzed by principal component analysis in conjunction with a novel K-nearest line classifier. This proposal allows simultaneous detection of up to four different steroids in the range of concentration from 0.1 to 316.2 nM with a total rate of 90.6% of correct detection, even in the presence of cross-reactivities. A methodology for concentration prediction is also presented with satisfactory results.

Keywords: -----


Garrido-Delgado, R., Arce, L., Guaman, A. V., Pardo, A., Marco, S., Valcárcel, M., (2011). Direct coupling of a gas-liquid separator to an Ion Mobility Spectrometer for the classification of different white wines using chemometrics tools Talanta 84, (2), 471-479

The potential of a vanguard technique as is the Ion Mobility Spectrometry with Ultraviolet ionization (UV-IMS) coupled to a Continuous Flow System (CFS) have been demonstrated in this work by using a Gas Phase Separator (GPS). This vanguard system (CFS-GPS-UV-IMS) has been used for the analysis of different types of white wines to obtain a characteristic profile for each type of wine and their posterior classification using different chemometric tools. Precision of the method was 3.1% expressed as relative standard deviation. A deep chemometric study was carried out for the classification of the four types of wines selected. The best classification performance was obtained by first reducing the data dimensionality by Principal Component Analysis (PCA) followed by Linear Discriminant Analysis (LDA) and finally using a K-Nearest Neighbour (kNN) classifier. The classification rate in an independent validation set were 92.0% classification rate value with confidence interval [89.0%, 95.0%] at P = 0.05 confidence level. The same white wines analyzed by using CFS-GPS-UV-IMS were analyzed by using Gas Chromatography with a Flame Detector (GC-FID) as conventional technique. The chromatographic method used for the determination of superior alcohols in wine samples shown in the Regulation CEE 1238/1992 was selected to carry out the analysis of the same samples set and later the classification using appropriate chemometric tools. In this case, strategies PCA-LDA and kNN classifier were also used for the correct classification of the wine samples. This combination showed similar results to the ones obtained with the proposed method.

Keywords: Classification, White wines, Ultraviolet-Ion Mobility Spectrometry, Gas Phase Separate, Vanguard method, Continuous Flow System, Chemometric analysis.


Pomareda, Victor, Marco, Santiago, (2011). Chemical plume source localization with multiple mobile sensors using bayesian inference under background signals Olfaction and Electronic Nose: Proceedings of the 14th International Symposium on Olfaction and Electronic Nose AIP Conference Proceedings (ed. Perena Gouma, SUNY Stony Brook), AIP (New York City, USA) 1362, (1), 149-150

This work presents the estimation of a likelihood map for the location of a source of chemical plume using multiple mobile sensors and Bayesian Inference. Previously described methods use a single sensor and just binary detections (concentrations above or below a certain threshold). The main contribution of this work is to extend previous proposals to use concentration information while at the same time being robust against the presence of background signals. The algorithm has two parts. The first part, concerning Adaptive Background Estimation, uses robust statistics measurements to estimate the background level despite the intermittent presence of high concentrations due to plume statistics. The second part of the algorithm estimates likelihood functions for background and for condition plus plume. Then, the algorithm sequentially builds a likelihood probability map for the location of the source. The algorithm allows the use of multiple mobile sensors. The simulation results demonstrate that our algorithm estimates better the source location and is much more robust in the presence of false alarms.

Keywords: Sensors, Inference mechanisms, Probability, Simulation


Ziyatdinov, Andrey, Fernandez-Diaz, Eduard, Chaudry, A., Marco, Santiago, Persaud, Krishna, Perera, Alexandre, (2011). A large scale virtual gas sensor array Olfaction and Electronic Nose: Proceedings of the 14th International Symposium on Olfaction and Electronic Nose AIP Conference Proceedings (ed. Perena Gouma, SUNY Stony Brook), AIP (New York City, USA) 1362, (1), 151-152

This paper depicts a virtual sensor array that allows the user to generate gas sensor synthetic data while controlling a wide variety of the characteristics of the sensor array response: arbitrary number of sensors, support for multi-component gas mixtures and full control of the noise in the system such as sensor drift or sensor aging. The artificial sensor array response is inspired on the response of 17 polymeric sensors for three analytes during 7 month. The main trends in the synthetic gas sensor array, such as sensitivity, diversity, drift and sensor noise, are user controlled. Sensor sensitivity is modeled by an optionally linear or nonlinear method (spline based). The toolbox on data generation is implemented in open source R language for statistical computing and can be freely accessed as an educational resource or benchmarking reference. The software package permits the design of scenarios with a very large number of sensors (over 10000 sensels), which are employed in the test and benchmarking of neuromorphic models in the Bio-ICT European project NEUROCHEM.

Keywords: Data analysis, Circuit noise, Data acquisition, Signal processing


Pairo, Erola, Maynou, Joan, Vallverdu, Montserrat, Caminal, Pere, Marco, Santiago, Perera, Alexandre, (2011). MEET: Motif elements estimation toolkit Engineering in Medicine and Biology Society (EMBC) 33rd Annual International Conference of the IEEE , IEEE (Boston, USA) , 6483-6486

MEET is an R package that integrates a set of algorithms for the detection of transcription factor binding sites (TFBS). The MEET R package includes five motif searching algorithms: MEME/MAST(Multiple Expectation-Maximization for Motif Elicitation), Q-residuals, MDscan (Motif Discovery scan), ITEME (Information Theory Elements for Motif Estimation) and MATCH. In addition MEET allows the user to work with different alignment algorithms: MUSCLE (Multiple Sequence Comparison by Log-Expectation), ClustalW and MEME. The package can work in two modes, training and detection. The training mode allows the user to choose the best parameters of a detector. Once the parameters are chosen, the detection mode allows to analyze a genome looking for binding sites. Both modes can combine the different alignment and detection methods, offering multiple possibilities. Combining the alignments and the detection algorithms makes possible the comparison between detection models at the same level, without having to care about the differences produced during the alignment process. The MEET R package can be downloaded from http://sisbio.recerca.upc.edu/R/MEET_1.0. tar.gz

Keywords: -----


Ziyatdinov, Andrey, Calvo, Jose Maria Blanco, Lechon, Miguel, Bermudez i Badia, Sergi, Verschure, Paul F. M. J., Marco, Santiago, Perera, Alexandre, (2011). Odour mapping under strong backgrounds with a metal oxide sensor array Olfaction and Electronic Nose: Proceedings of the 14th International Symposium on Olfaction and Electronic Nose AIP Conference Proceedings (ed. Perena Gouma, SUNY Stony Brook), AIP (New York City, USA) 1362, (1), 232-233

This work describes the data from navigation experiments with the mobile robot, equipped with the sensor array of three MOX gas sensors. Performed four series of measurements aim to explore the capabilities of sensor array to build the odour map with one or two odour sources in the wind tunnel space. It was demonstrated that the method based on Independent Component Analysis (ICA) is able to discriminate two odour sources, that in future can be used in the surge-and-cast robot navigation algorithm.

Keywords: Mobile robots, Data acquisition, MIS devices, Chemioception


Marco, Santiago, (2011). Signal processing for chemical sensing: Statistics or biological inspiration Olfaction and Electronic Nose: Proceedings of the 14th International Symposium on Olfaction and Electronic Nose AIP Conference Proceedings (ed. Perena Gouma, SUNY Stony Brook), AIP (New York City, USA) 1362, (1), 145-146

Current analytical instrumentation and continuous sensing can provide huge amounts of data. Automatic signal processing and information evaluation is needed to overcome drowning in data. Today, statistical techniques are typically used to analyse and extract information from continuous signals. However, it is very interesting to note that biology (insects and vertebrates) has found alternative solutions for chemical sensing and information processing. This is a brief introduction to the developments in the European Project: Bio-ICT NEUROCHEM: Biologically Inspired Computation for Chemical Sensing (grant no. 216916) Fp7 project devoted to biomimetic olfactory systems.

Keywords: Signal processing, Chemioception, Neural nets, Computational complexity


Gutierrez-Galvez, Agustin, Fernandez, Luis, Marco, Santiago, (2011). Study of sensory diversity and redundancy to encode for chemical mixtures Olfaction and Electronic Nose: Proceedings of the 14th International Symposium on Olfaction and Electronic Nose AIP Conference Proceedings (ed. Perena Gouma, SUNY Stony Brook), AIP (New York City, USA) 1362, (1), 147-148

Inspired by sensory diversity and redundancy at the olfactory epithelium, we have built a large chemical sensor array based on commercial MOX sensors. Different sensor families along with temperature modulation accounts for sensory diversity, whereas sensors of the same family combined with different load resistors provide redundancy to the system. To study the encoding of odor mixtures, a data collection consisting on the response of the array to 3 binary mixtures of ethanol, acetone, and butanone with 18 different concentration ratios is obtained.

Keywords: Chemioception, Sensors, Data acquisition, Temperature measurement


Ziyatdinov, A., Marco, S., Chaudry, A., Persaud, K., Caminal, P., Perera, A., (2010). Drift compensation of gas sensor array data by common principal component analysis Sensors and Actuators B: Chemical 146, (2), 460-465

A new drift compensation method based on Common Principal Component Analysis (CPCA) is proposed. The drift variance in data is found as the principal components computed by CPCA. This method finds components that are common for all gasses in feature space. The method is compared in classification task with respect to the other approaches published where the drift direction is estimated through a Principal Component Analysis (PCA) of a reference gas. The proposed new method - employing no specific reference gas, but information from all gases -has shown the same performance as the traditional approach with the best-fitted reference gas. Results are shown with data lasting 7-months including three gases at different concentrations for an array of 17 polymeric sensors.

Keywords: Gas sensor array, Drift, Common principal component, Analysis, Component correction, Electronic nose


Perera, A., Pardo, A., Barrettino, D., Hierlermann, A., Marco, S., (2010). Evaluation of fish spoilage by means of a single metal oxide sensor under temperature modulation Sensors and Actuators B: Chemical 146, (2), 477-482

In this paper the feasibility of using metal oxide gas sensor technology for evaluating spoilage process for sea bream (Sparus aurata) is explored. It is shown that a single sensor under temperature modulation is able to find a correlation with the fish spoilage process. Results are obtained in real frigorific storage conditions: that is, at low measurement temperatures with variations of relative humidity.

Keywords: Gas sensors, Electronic nose, Spoilage process, Temperature modulation, Bream sparus-aurata, Electronic nose, Freshness, Quality, Sardines, Storage


Montoliu, I., Tauler, R., Padilla, M., Pardo, A., Marco, S., (2010). Multivariate curve resolution applied to temperature modulated metal oxide gas sensors Sensors and Actuators B: Chemical 145, (1), 464-473

Metal oxide (MOX) gas sensors have been widely used for years. Temperature modulation of gas sensors is as an alternative to increase their sensitivity and selectivity to different gas species. In order to enhance the extraction of useful information from this kind of signals, data processing techniques are needed. In this work, the use of self-modelling curve resolution techniques, in particular multivariate curve resolution-alternating least squares (MCR-ALS), is presented for the analysis of these signals. First, the performance of MCR in a synthetic dataset generated from temperature-modulated gas sensor response models has been evaluated, showing good results both in the resolution of gas mixtures and in the determination of concentration/sensitivity profiles. Secondly, experimental confirmation of previously obtained conclusions is attempted using temperature-modulated MOX sensors together with MCR-ALS for the analysis of carbon monoxide (CO) and methane (CH4) gas mixtures in dry air. Results allow confirming the possibility of using the proposed approach as a quantitative technique for gas mixtures analysis, and also reveal some limitations.

Keywords: Temperature modulation, Multivariate curve resolution, MCR-ALS, Metal oxide sensors


Falasconi, M., Gutierrez, A., Pardo, M., Sberveglieri, G., Marco, S., (2010). A stability based validity method for fuzzy clustering Pattern Recognition 43, (4), 1292-1305

An important goal in cluster analysis is the internal validation of results using an objective criterion. Of particular relevance in this respect is the estimation of the optimum number of clusters capturing the intrinsic structure of your data. This paper proposes a method to determine this optimum number based on the evaluation of fuzzy partition stability under bootstrap resampling. The method is first characterized on synthetic data with respect to hyper-parameters, like the fuzzifier, and spatial clustering parameters, such as feature space dimensionality, clusters degree of overlap, and number of clusters. The method is then validated on experimental datasets. Furthermore, the performance of the proposed method is compared to that obtained using a number of traditional fuzzy validity rules based on the cluster compactness-to-separation criteria. The proposed method provides accurate and reliable results, and offers better generalization capabilities than the classical approaches.

Keywords: Fuzzy c-means, Cluster validity, Number of clusters, Cluster stability


Padilla, M., Perera, A., Montoliu, I., Chaudry, A., Persaud, K., Marco, S., (2010). Drift compensation of gas sensor array data by orthogonal signal correction Chemometrics and Intelligent Laboratory Systems 100, (1), 28-35

Drift is an important issue that impairs the reliability of gas sensing systems. Sensor aging, memory effects and environmental disturbances produce shifts in sensor responses that make initial statistical models for gas or odor recognition useless after a relatively short period (typically few weeks). Frequent recalibrations are needed to preserve system accuracy. However, when recalibrations involve numerous samples they become expensive and laborious. An interesting and lower cost alternative is drift counteraction by signal processing techniques. Orthogonal Signal Correction (OSC) is proposed for drift compensation in chemical sensor arrays. The performance of OSC is also compared with Component Correction (CC). A simple classification algorithm has been employed for assessing the performance of the algorithms on a dataset composed by measurements of three analytes using an array of seventeen conductive polymer gas sensors over a ten month period.

Keywords: Gas sensor array, Drift, Orthogonal signal correction, Component correction, Cross-validation, Electronic nose, Data shift


Pomareda, V., Calvo, D., Pardo, A., Marco, S., (2010). Hard modeling multivariate curve resolution using LASSO: Application to ion mobility spectra Chemometrics and Intelligent Laboratory Systems 104, (2), 318-332

Multivariate Curve Resolution (MCR) aims to blindly recover the concentration profile and the source spectra without any prior supervised calibration step. It is well known that imposing additional constraints like positiveness, closure and others may improve the quality of the solution. When a physico-chemical model of the process is known, this can be also introduced constraining even more the solution. In this paper, we apply MCR to Ion Mobility Spectra. Since instrumental models suggest that peaks are of Gaussian shape with a width depending on the instrument resolution, we introduce that each source is characterized by a linear superposition of Gaussian peaks of fixed spread. We also prove that this model is able to fit wider peaks departing from pure Gaussian shape. Instead of introducing a non-linear Gaussian peak fitting, we use a very dense model and rely on a least square solver with L1-norm regularization to obtain a sparse solution. This is accomplished via Least Absolute Shrinkage and Selection Operator (LASSO). Results provide nicely resolved concentration profiles and spectra improving the results of the basic MCR solution.

Keywords: Blind source separation, Ion mobility spectrometry, Multivariate curve resolution, Sparse solution, Non negative matrix factorization


Salleras, M., Carmona, M., Marco, S., (2010). Issues in the use of thermal transients to achieve accurate time-constant spectrums and differential structure functions IEEE Transactions on Advanced Packaging 33, (4), 918-923

An analysis of accuracy of time-constant spectrum extraction from thermal transients has been performed. Numerical calculations based on analytical models and finite element method simulations have been used in order to obtain the thermal transients. Simple geometries have been used such that analytical expressions for their time-constant spectrums are known. Results show that a large error in the time-constant spectrum is obtained for very small rms error ( 1 mK) in the thermal transient. The estimation problem is ill-conditioned. Moreover, the differential structure function shows a low accuracy identifying stacked structures. The initial part of the differential structure function shows numerical oscillations and the final part has an asymptotic behavior to infinity that has been identified as an artifact related to errors in the time-constant spectrum estimation. Peak identification from the differential structure function heavily depends on an accurate determination of the time-constant spectrum. The limited spectral resolution and dynamic range of the differential structure function are a direct consequence of the time-constant spectrum imprecision.

Keywords: Finite element analysis, Spectral analysis


Tarzan-Lorente, M., Gutierrez-Galvez, A., Martinez, D., Marco, S., (2010). A biologically inspired associative memory for artificial olfaction Practica 2010 International Joint Conference on Neural Networks (IJCNN 2010) , IEEE, Piscataway, NJ, USA (Barcelona, Spain) , 6 pp.

In this paper, we propose a biologically inspired architecture for a Hopfield-like associative memory applied to artificial olfaction. The proposed algorithm captures the projection between two neural layers of the insect olfactory system (Antennal Lobe and Mushroom Body) with a kernel based projection. We have tested its classification performance as a function of the size of the training set and the time elapsed since training and compared it with that obtained with a Support Vector Machine.

Keywords: Biocomputing, Chemioception, Content-addressable storage, Hopfield neural nets, Support vector machines


Padilla, M., Perera, A., Montoliu, I., Chaudry, A., Persaud, K., Marco, S., (2010). Fault detection, identification, and reconstruction of faulty chemical gas sensors under drift conditions, using Principal Component Analysis and Multiscale-PCA Theoretical or Mathematical; Experimental The 2010 International Joint Conference on Neural Networks (IJCNN 2010) , IEEE, Piscataway, NJ, USA (Barcelona, Spain) , 7 pp.

Statistical methods like Principal Components Analysis (PCA) or Partial Least Squares (PLS) and multiscale approaches, have been reported to be very useful in the task of fault diagnosis of malfunctioning sensors for several types of faults. In this work, we compare the performance of PCA and Multiscale-PCA on a fault based on a change of sensor sensitivity. This type of fault affects chemical gas sensors and it is one of the effects of the sensor poisoning. These two methods will be applied on a dataset composed by the signals of 17 conductive polymer gas sensors, measuring three analytes at several concentration levels during 10 months. Therefore, additionally to performance's comparison, both method's stability along the time will be tested. The comparison between both techniques will be made regarding three aspects; detection, identification of the faulty sensors and correction of faulty sensors response.

Keywords: Fault diagnosis, Gas sensors, Principal component analysis


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


Auffarth, B., Gutierrez-Galvez, A., Marco, S., (2010). Relevance and LOCI of odorant features in the rat olfactory bulb: Statistical methods for understanding olfactory codes in glomerular images BIOSIGNALS 2010 - Proceedings of the 3rd International Conference on Bio-inpsired Systems and Signal Processing, Proceedings 3rd International Conference on Bio-inspired Systems and Signal Processing, BIOSIGNALS 2010 (ed. Fred, A., Filipe, J., Gamboa, H.), Springer-Verlag (Valencia, Spain) , 37-44

The relationship between physicochemical properties of odor molecules and perceived odor quality is arguably one of the most important issues in olfaction and the rules governing this relationship remain unknown. Any given odor molecule will stimulate more than one type of receptor in the nose, perhaps hundreds, and this stimulation reflects itself in the neural code of the olfactory nervous system. We present a method to investigate neural coding at the glomerular level of the olfactory bulb, the first relay for olfactory processing in the brain. Our results give insights into localization of coding sites, relevance of odorant properties for information processing, and the size of coding zones.

Keywords: Classification, Glomeruli, Non-parametric statistics, Odorants, Olfactory bulb, Olfactory coding, Property-activity relationship


Pairo, E., Marco, S., Perera, A., (2010). A subspace method for the detection of transcription factor binding sites BIOINFORMATICS 2010. Proceedings of the First International Conference on Bioinformatics BIOINFORMATICS 2010. First International Conference on Bioinformatics (ed. Fred, A., Filipe, J., Gamboa, H.), INSTICC Press (Valencia, Spain) , 102-107

Transcription Factor binding sites are short and degenerate sequences, located mostly at the promoter of the gene, where some proteins bind in order to regulate transcription. Locating these sequences is an important issue, and many experimental and computational methods have been developed. Algorithms to search binding sites are usually based on Position Specific Scoring Matrices (PSSM), where each position is treated independently. Mapping symbolical DNA to numerical sequences, a detector has been built with a Principal Component Analysis of the numerical sequences, taking into account covariances between positions. When a treatment of missing values is incorporated the Q-residuals detector, based on PCA, performs better than a PSSM algorithm. The performance on the detector depends on the estimation of missing values and the percentage of missing values considered in the model.

Keywords: Binding sites, BPCA, Missing values, Numerical DNA, Principal components analysis, Transcription factors


Fonollosa, J., Halford, B., Fonseca, L., Santander, J., Udina, S., Moreno, M., Hildenbrand, J., Wöllenstein, J., Marco, S., (2009). Ethylene optical spectrometer for apple ripening monitoring in controlled atmosphere store-houses Sensors and Actuators B: Chemical 136, (2), 546-554

In today's store-houses the ripening of fruit is controlled by managing the ethylene concentration in the ambient atmosphere. Precise and continuous ethylene monitoring is very advantageous since low ethylene concentrations are produced by the fruit itself and are indicative of its ripeness, and on other occasions, ethylene is externally added when ripeness or degreening of the product must be promoted. In this work, a multichannel mid-infrared spectrometer for ethylene measurement is built and characterized. The instrument contains additional channels to reject potential cross-interferences like ammonia and ethanol. Additionally, these channels are useful for monitoring a potential malfunction of the cooling system and possible fouling of the fruit, respectively. The complete spectrometer contains a silicon-based macroporous infrared (IR) emitter, a miniaturized long path cell (white cell), a four-channel detector module, low-noise analog amplification and filtering, and a microcontroller-based lock-in amplifier. The new inner architecture of the detector module features a fourfold thermopile array with narrow band optical filters attached by flip-chip technology, and a Fresnel lens array attached on the lid of the package. Laboratory tests show that the system is able to distinguish between ammonia and ethylene, featuring a detection limit of 30 ppm and 160 ppm (95% confidence) for ethylene and ammonia, respectively. Field tests show that the spectrometer is suitable as an ethylene alarm to detect fruit ripening and prevent fruit to decline into senescence. Simulation results show that system selectivity could be improved by setting ammonia channel to another absorption wavelength.

Keywords: IR spectrometer, Ethylene, Fruit storage, Fresnel lens, White cell, Lock-in amplifier


Fonollosa, J., Carmona, M., Santander, J., Fonseca, L., Moreno, M., Marco, S., (2009). Limits to the integration of filters and lenses on thermoelectric IR detectors by flip-chip techniques Sensors and Actuators A: Physical 149, (1), 65-73

In the trend towards miniaturization, a detector module containing multiple IR sensor channels is being built and characterized. In its final form it contains thermopiles, narrow band filters and Fresnel lenses. An important feature of such module is the assembly by flip-chip of the IR filters on top of the thermopiles. The performance of the filter-thermopile ensemble has been assessed by physical simulation and experiments and it has been optimized by the use of an empirically validated model. It has been found that integration of filters (or lenses) too close to the IR detector may lead to degraded performance due to thermal coupling. The impact and extent of this degradation has been thoroughly explored, being the main parameter the distance between the IR sensor and the filter. To avoid such detrimental effects a possibility is to set the device in vacuum conditions, obtaining an improved output response and avoiding the influence of the filters. Another way is to increase the solder joint height. Beyond a certain height, the filter is considered to be isolated from the thermopile.

Keywords: Assembly, Infrared sensor, Infrared filter, Fresnel lenses, FEM simulation, Optimization


Marco, S., Pomareda, V., Pardo, A., Kessler, M., Goebel, J., Mueller, G., (2009). Blind source separation for ion mobility spectra Olfaction and Electronic Nose: Proceedings of the 13th International Symposium on Olfaction and Electronic Nose 13th International Symposium on Olfaction and the Electronic Nose (ed. Pardo, M., Sberveglieri, G.), Amer Inst Physics (Brescia, Italy) 1137, 551-553

Miniaturization is a powerful trend for smart chemical instrumentation in a diversity of applications.. It is know that miniaturization in IMS leads to a degradation of the system characteristics. For the present work, we are interested in signal processing solutions to mitigate limitations introduced by limited drift tube length that basically involve a loss of chemical selectivity. While blind source separation techniques (BSS) are popular in other domains, their application for smart chemical instrumentation is limited. However, in some conditions, basically linearity, BSS may fully recover the concentration time evolution and the pure spectra with few underlying hypothesis. This is extremely helpful in conditions where non-expected chemical interferents may appear, or unwanted perturbations may pollute the spectra. SIMPLISMA has been advocated by Harrington et al. in several papers. However, more modem methods of BSS for bilinear decomposition with the restriction of positiveness have appeared in the last decade. In order to explore and compare the performances of those methods a series of experiments were performed.

Keywords: Ion Mobility Spectrometry (IMS), Blind Source Separation (BSS), Multivariate Analysis, SIMPLISMA, MCR, Non-Negative Matrix Factorization (NMF)


Falasconi, M., Gutierrez, A., Auffarth, B., Sberveglieri, G., Marco, S., (2009). Cluster analysis of the rat olfactory bulb activity in response to different odorants Olfaction and Electronic Nose: Proceedings of the 13th International Symposium on Olfaction and Electronic Nose 13th International Symposium on Olfaction and the Electronic Nose (ed. Pardo, M., Sberveglieri, G.), Amer Inst Physics (Brescia, Italy) 1137, 169-172

With the goal of deepen in the understanding of coding of chemical information in the olfactory system, a large data set consisting of rat's olfactory bulb activity values in response to several different volatile compounds has been analyzed by fuzzy c-means clustering methods. Clustering should help to discover groups of glomeruli that are similary activated according to their response profiles across the odorants. To investigate the significance of the achieved fuzzy partitions we developed and applied a novel validity approach based on cluster stability. Our results show certain level of glomerular clustering in the olfactory bulb and indicate that exist a main chemo-topic subdivision of the glomerular layer in few macro-area which are rather specific to particular functional groups of the volatile molecules.

Keywords: Olfactory bulb, 2-deoxyglucose mapping, Olfactory coding, Cluster analysis, Cluster validity


Perera, A., Pardo, A., Barrettino, D., Hierlermann, A., Marco, S., (2009). Evaluation of fish spoilage by means of a single metal oxide sensor under temperature modulation Olfaction and Electronic Nose: Proceedings of the 13th International Symposium on Olfaction and Electronic Nose 13th International Symposium on Olfaction and Electronic Nose (ed. Pardo, M., Sberveglieri, G.), Amer Inst Physics (Brescia, Italy) 1137, 483-486

In this paper the feasibility of using metal oxide gas sensor technology for evaluating spoilage process for sea bream (Sparus Aurata) is explored. It is shown that a single sensor under temperature modulation is able to find a correlation with the fish spoilage process

Keywords: Gas sensors, Electrochemical sensors, Chromatography


Padilla, M., Pereral, A., Montoliu, I., Chaudry, A., Persaud, K., Marco, S., (2009). Improving drift correction by double projection preprocessing in gas sensor arrays Olfaction Electronic Nose: Proceedings of the 13th International Symposium on Olfaction and Electronic Nose 13th International Symposium on Olfaction and the Electronic Nose (ed. Pardo, M., Sberveglieri, G.), Amer Inst Physics (Brescia, Italy) 1137, 101-104

It is well known that gas chemical sensors are strongly affected by drift. Drift consist on changes in sensors responses along the time, which make that initial statistical models for gas or odor recognition become useless after a period of time of about weeks. Gas sensor arrays based instruments periodically need calibrations that are expensive and laborious. Many different statistical methods have been proposed to extend time between recalibrations. In this work, a simple preprocessing technique based on a double projection is proposed as a prior step to a posterior drift correction algorithm (in this particular case, Direct Orthogonal Signal Correction). This method highly improves the time stability of data in relation with the one obtained by using only such drift correction method. The performance of this technique will be evaluated on a dataset composed by measurements of three analytes by a polymer sensor array along ten months.

Keywords: Drift, Direct orthogonal signal correction


Calvo, D., Salvador, J. P., Tort, N., Centi, F., Marco, M. P., Marco, S., (2009). Multidetection of anabolic androgenic steroids using immunoarrays and pattern recognition techniques Olfaction and Electronic Nose: Proceedings of the 13th International Symposium on Olfaction and Electronic Nose 13th International Symposium on Olfaction and the Electronic Nose (ed. Pardo, M., Sberveglieri, G.), Amer Inst Physics (Brescia, Italy) 1137, 547-550

A first step towards the multidetection of anabolic androgenic steroids by Enzyme-linked immunosorbent assays (ELISA) has been performed in this study. This proposal combines an array of classical ELISA assays with different selectivities and multivariate data analysis techniques. Data has been analyzed by principal component analysis in conjunction with a k-nearest line classifier has been used. This proposal allows to detect simultaneously four different compounds in the range of concentration from 10(-1.5) to 10(3) mM with a total rate of 90.6% of correct detection.

Keywords: Immunoarray, Anabolic androgenic steroid, Multidetection, Pattern recognition, K-nearlest line


Pairo, E., Marco, S., Perera, A., (2009). A preliminary study on the detection of transcription factor binding sites Biosignals 2009: Proceedings of the International Conference on Bio-Inspired Systems and Signal Processing 2nd International Conference on Bio-Inspired Systems and Signal Processing (ed. Encarnacao, P., Veloso, A.), Insticc-Inst Syst Technologies Information Control & Communication (Oporto, Portugal) , 506-509

Transcription starts when multiple proteins, known as transcription factors recognize and bind to transcription start site in DNA sequences. Since mutation in transcription factor binding sites are known to underlie diseases it remains a major challenge to identify these binding sites. Conversion from symbolic DNA to numerical sequences and genome data make it possible to construct a detector based on a numerical analysis of DNA binding sites. A subspace model for the TFBS is built. TFBS will show a very small distance to this particular subspace. Using this distance binding sites are distinguished from random sequences and from genome data.

Keywords: Transcription factors, Binding sites, Principal components analysis


Marco, S., Gutierrez-Galvez, A., (2009). Recent developments in the application of biologically inspired computation to chemical sensing Olfaction Electronic Nose: Proceedings of the 13th International Symposium on Olfaction and Electronic Nose 13th International Symposium on Olfaction and the Electronic Nose (ed. Pardo, M., Sberveglieri, G.), Amer Inst Physics (Brescia, Italy) 1137, 151-154

Biological olfaction outperforms chemical instrumentation in specificity, response time, detection limit, coding capacity, time stability, robustness, size, power consumption, and portability. This biological function provides outstanding performance due, to a large extent, to the unique architecture of the olfactory pathway, which combines a high degree of redundancy, an efficient combinatorial coding along with unmatched chemical information processing mechanisms. The last decade has witnessed important advances in the understanding of the computational primitives underlying the functioning of the olfactory system. In this work, the state of the art concerning biologically inspired computation for chemical sensing will be reviewed. Instead of reviewing the whole body of computational neuroscience of olfaction, we restrict this review to the application of models to the processing of real chemical sensor data.

Keywords: Computational Intelligence, Chemical Sensors


Montoliu, I., Pomareda, V., Kalms, A., Pardo, A., Gobel, J., Kessler, M., Muller, G., Marco, S., (2009). Resolution of ion mobility spectra for the detection of hazardous substances in real sampling conditions Olfaction and Electronic Nose: Proceedings of the 13th International Symposium on Olfaction and Electronic Nose 13th International Symposium on Olfaction and the Electronic Nose (ed. Pardo, M., Sberveglieri, G.), Amer Inst Physics (Brescia, Italy) 1137, 576-578

This work presents the possibilities offered by a blind source separation method such Multivariate Curve Resolution- Alternating Least Squares (MCR-ALS) in the analysis of Ion Mobility Spectra (IMS). Two security applications are analyzed in this context: the detection of TNT both in synthetic and real samples. Results obtained show the possibilities offered by the direct analysis of the drift time spectra when an appropriate resolution method is used.

Keywords: Ion Mobility Spectrometry, Multivariate Curve Resolution, Security, LIMS, MCR-ALS


Perera, A., Rock, F., Montoliu, I., Weimar, U., Marco, S., (2009). Total solvent amount and human panel test predictions using gas sensor fast chromatography and multivariate linear and non-linear processing Olfaction and Electronic Nose: Proceedings of the 13th International Symposium on Olfaction and Electronic Nose 13th International Symposium on Olfaction and the Electronic Nose (ed. Pardo, M., Sberveglieri, G.), Amer Inst Physics (Brescia, Italy) 1137, 572-573

Data from a Gas Sensor based Chromatography instrument is used in order to replicate output from a human panel and the estimation of the total solvent amount measured by and FID device in a packaging application. The system is trained on different packaging sample properties and validated with unseen combinations of materials, varnishes and production processes. This contribution will show the difficulties on the prediction of the output of the human panel, and the success on the prediction of the total amount of solvent in the sample

Keywords: Gas sensors, Solvent prediction


Gutierrez, A., Marco, S., (2009). Biologically inspired signal processing for chemical sensing Studies in Computational Intelligence GOSPEL Workshop on Bio-inspired Signal Processing (ed. Gutierrez, A., Marco, S.), Springer (Barcelona, Spain) -----, (188), -----

This 167-page book is volume 188 in the series 'Studies in computational intelligence.' This volume contain 9 extensive chapters written in English. This volume presents a collection of research advances in biologically inspired signal processing for chemical sensing. The olfactory system, and the gustatory system to a minor extent, has been taken in the last decades as a source of inspiration to develop artificial sensing systems. The recognition of odors by the olfactory system entails a number of signal processing functions such as preprocessing, dimensionality reduction, contrast enhancement, and classification. Using mathematical models to mimic the architecture of the olfactory system, these processing functions can be applied to chemical sensor signals. This book provides background on the olfactory system including a review on information processing in the insect olfactory system along with a proposed signal processing architecture based on the mammalian cortex. It also provides some bio-inspired approaches to process chemical sensor signals such as an olfactory mucosa to improve odor separation and a model of olfactory receptor neuron convergence to correlated sensor responses to an odor and his organoleptic properties. This book will useful to those working or studying in the areas of sensory reception and computational biology.

Keywords: Nervous System (Neural Coordination), Computer Applications (Computational Biology), Sense Organs (Sensory Reception)


Udina, S., Carmona, M., Carles, G., Santander, J., Fonseca, L., Marco, S., (2008). A micromachined thermoelectric sensor for natural gas analysis: Thermal model and experimental results Sensors and Actuators B: Chemical 134, (2), 551-558

Natural gas may show significant changes in its chemical composition depending on its origin. Typically, natural gas analysis is carried out using process gas chromatography. However, other methods based on the evaluation of physical properties have recently been reported. Thermal conductivity sensors are currently used in the analysis of binary mixtures of dissimilar gases. In contrast, natural gas is a complex mixture of mainly hydrocarbons, plus other residual gases as carbon dioxide and nitrogen. In this work, the response of a micromachined sensor integrating a heater and a thermopile is studied, regarding its potential use for natural gas analysis. A finite element thermal model of the device is described, and thermal operation simulations as well as a preliminary sensitivity analysis are reported. Experimental data has been collected and compared with simulated data, showing very good agreement. Results show that small variations in the gas mixture composition can be clearly detected. The sensor appears as a good candidate to be included in low-cost natural gas property analysis and quality control systems.

Keywords: Natural gas, Thermopile, MEMS, Thermal conductivity, Modeling, FEM simulation


Udina, S., Pardo, A., Marco, S., Santander, J., Fonseca, L., (2008). Thermoelectric MEMS sensors for natural gas analysis Electronic Proceedings of the Seventh IEEE Sensors Conference 2008 Sensors, 2008 IEEE (ed. Frech, P., Siciliano, P.), IEEE (Lecce, Italy) , 1364-1367

T Multivariate data analysis techniques have been used for the first time in thermoelectric MEMS sensors in order to determine the composition of natural gas mixtures. Experimental measurements with different thermoelectric devices have been performed, the gathered data have been used to calibrate the sensor responses to four main components of natural gas: CH4, C2H6, N2 and CO2. Presence of the three first components was predicted with good accuracy while CO2 prediction was poor. Presented results indicate that thremoelectric sensors operated at different heater temperatures open the possibility of low-cost natural gas analysis.

Keywords: Natural gas, Multivariate calibration, Thermal conductivity, Thermal sensor


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