Current smart instrumentation using multi-sensors and/or spectrometers provides a wealth of data that requires sophisticated signal and data processing approaches to extract the hidden information.
Our group develops algorithmic solutions for the automatic processing of Gas Sensor Array, Gas Chromatography – Ion Mobility Spectrometry (IMS), Nuclear Magnetic Resonance, and Mass Spectrometry (GC/LC-MS, MSI) data for metabolomics, food, and environmental samples.
In this context, we are interested in intelligent chemical instruments for the detection of gases, volatile compounds, and smells. These systems can be based on an array of nonspecific chemical sensors with a pattern recognition engine, taking inspiration from the olfactory system. Some spectrometries, e.g. Ion Mobility Spectrometry, are capable of very fast analysis with good detection limits but poor selectivity. These technologies have been proposed for the fast determination of the volatolome (volatile fraction of the metabolome), instead of the reference technique of gas chromatography – mass spectrometry.
During 2019 our research has been focused on:
- Development of drones and terrestrial robots with bioinspired machine olfaction capabilities for gas source localization and mapping. Our results have shown that nanodrones with proper signal processing are able to locate sources in indoor scenarios particularly for chemical sources located above the drone.
- Development of signal processing approaches to improve the time dynamics of chemical sensors and extract bioinspired chemical features from turbulent plumes. Proper deconvolution methods based on inverse filters are able to improve the sensor bandwidth an order of magnitude, reaching time dynamics able to detect with subsecond events.
- Development of data processing methods to resolve molecular heterogeneity in mass spectrometry images of colorectal cancer tissues. The developed methods can discriminate resistant and sensitive areas of tissue to chemotherapy after proper training with homogeneous tissue images.
- Development of full workflows including signal processing and machine learning tools for the analysis of untargeted nuclear magnetic resonance data. We have developed and released to the public a package developed in R for the analysis of NMR data: AlpsNMR.
- Development of methods for the analysis of flatus and their relationship with food intake.
- Development of signal processing methods for the analysis of Ham and Olive Oil flavour data using GC-IMS and their potential use in fraud detection.
- Development of methods for the analysis of urine using GC-IMS
- Development of techniques to reduce the power consumption of chemical sensor based on metal oxides.
|TENSOMICS · Development of tensorial signal processing and machine learning tools tailored to the analysis of urine metabolomics (2019-2022)||Ministerio de Ciencia, Innovación y Universidades||Santiago Marco|
|PRIVATELY FUNDED PROJECTS||FINANCER||PI|
|Anticipation of respiratory outcomes in ICU COVID-19 patients by metabolic signatures (2021-2023)||Fundació La Marató de TV3||Santiago Marco|
|SNIFFDRONE · Drone-based Environmental Odor Monitoring (2019-2020)||EU Commission · Attract Projects||Santiago Marco|
|Analisis de tapones de corcho por espectroscopia de movilidad de iones (2015-2016)||M3C INDUSTRIAL AUTOMATION & VISION, S.L.||Santiago Marco|
|Sensor test for indoor air quality and safety applications (2015-2016)||BSH Electrodomesticos España S.A.||Santiago Marco|
|Preparació i realització d’un curs de processat de senyal per sensors químics de dos dies a BSH Zaragoza (2016-2017)||BSH Electrodomesticos España S.A.||Santiago Marco|
|SMART-IMS Procesado de Señal para Espectroscopia de Movilidad de Iones: Análisis de Fluidos Biomédicos y Detección de Sustancias Tóxicas (2012-2015)||MINECO, I+D-Investigación fundamental no orientada||Santiago Marco|
|Transducción biomimética para olfacción artificial||MINECO, EUROPA EXCELENCIA||Agustín Gutiérrez|
|BIOENCODE Estudio comparativo de la capacidad de codificación de información química de sistemas biológicos y artificiales||MINECO, I+D-Investigación fundamental no orientada||Agustín Gutiérrez|
|SENSIBLE Sensores inteligentes para edificios más seguros (2014-2016)||MINECO, Acciones de Programación Conjunta Internacional||Santiago Marco|
|SAFESENS Sensor Technologies for Enhanced Safety and Security of Buildings and its Occupants (2014-2017)||ENIAC Joint Undertaking||Santiago Marco|
|SIGVOL Mejora de la señal para instrumentación química: aplicaciones en metabolómica de volátiles y en olfacción (2015-2017)||MINECO, Retos investigación: Proyectos I+D||Santiago Marco|
|Computational Metabolomics (2017-2019)||Industrial Project with Nestlé Institute of Health Sciences, Switzerland||Santiago Marco|
|Development of Data Processing Algorithms for Temperature Modulated Sensors||Industrial Project with BSH Electrodomesticos, Spain||Santiago Marco|
- Gas chromatograph/mass spectrometer (Thermoscientific) with robotic head-space sampler
- Gas Chromatograph/ Thermal Conductivity Detector (Thermoscientific) with robotic head-space sampler
- 2 Infusion pumps K-systems
- Gas Chromatography-Ion Mobility Spectrometry FlavourspecTM (Gas Dortmund)
- 6 channel vapor generator plus humidity control (Owlstone, UK)
- Ion Mobility Spectrometer: Gas Detector Array (Airsense Analytics GmbH)
- Computing and General Purpose Electronic Instrumentation
- Field Asymmetric Ion Mobility Spectrometer (Owlstone, UK)
- Corona Discharge Ion Mobility Spectrometer (3QBD, Israel)
- Ultraviolet Ion Mobility Spectrometer (Gas Dortmund, Germany)
- Fast Photo Ionization Detector (Aurora Scientific, Canada)
- Dr. Lourdes Arce
Dept. Química Analítica, Universidad de Córdoba, Spain
- Prof. J. W. Gardner
Microsensors and Bioelectronics Lab, Dept. of Electric and Electronic Engineering, University of Warwick, UK
- Prof. Achim Lilienthal
Mobile Robotics and Olfaction Lab, University of Örebro, Sweden
- Dr. Ivan Montoliu and Dra. Sofia Moço
Nestlé Institute of Health Sciences, Laussane, Switzerland
- Dr. Jordi Palacín
Robotics Lab, Universitat de Lleida, Spain
- Dra. Cristina Castro
Sensors Technology, BSH-Zaragoza, Spain
- Dr. Jens Eichman
MINIMAX, Bad Oldesloe, Germany
- Dr. Ulf Struckmeier
AMS sensors, Reutlingen, Germany
- Dr. Fernando Azpiroz
Dept. Digestive Diseases, Vall d’Hebron, Barcelona, Spain
- Dra. Anna de Juan
Dept. Química Analítica i Enginyeria Química, Universitat de Barcelona, Spain
- Dra. Sofia Moço
Nestlé Research, Laussane, Switzerland
- Dra. Silvia Mas
IRSTEA; Montpellier, France.
- Dr. Dominique Martinez
LORIA-INRIA, Nancy, France
- Dr. Oriol Sibila & Dr. Àlvar Agustí
Inflamación y reparación en enfermedades respiratorias, Hospital Clínic de Barcelona
The SNIFFIRDRONE project, in which researchers from the Institute for Bioengineering of Catalonia (IBEC) participate, appears in the media with the main objective of developing a drone-based system that generates real-time pollution and odor maps, as well as instant reports and alarms.
Researchers from the Institute for Bioengineering of Catalonia, led by Santi Marco, appear in the media to validate, together with the Hospital Clínic of Barcelona, a new technology that analyses the breath of patients and diagnoses with a high degree of precision who suffer from pulmonary infections by P. aeruginosa.
Santiago Marco, group leader at the Institute for Bioengineering of Catalonia (IBEC), appears in the newspaper “El Español” exploring the scientific reasons why snow can smell.
IBEC researchers, together with clinicians from Sant Pau Hospital and Hospital Clinic in Barcelona, use “electronic noses” and machine learning to analyse the breath of patients, identifying with high accuracy those with lung infections of P. aeruginosa, a multidrug resistant pathogen. This method could represent a non-invasive and efficient tool to diagnose and monitor patients with a bacterial lung infection, offering a faster alternative to standard sputum cultures.
Researchers from the Institute for Bioengineering of Catalonia (IBEC) lead by Santiago Marco, appear in the media for the new method they have designed to sniff out the stench of sewage treatment plants.
Researchers from Spain have engineered a portable electronic nose (e-nose) that’s almost as sharp as a human nose at sniffing out wastewater treatment plants’ stink. Coupled with a drone, the lightweight e-nose can measure the concentration of different smells, predict odor intensity and produce a real-time odor map of the plant for management. The method developed was published November 16 in the journal iScience.
Researchers from IBEC, in collaboration with the University of Cordoba, recently published a study where they develop protocols that optimize the use of a technique capable of analysing, at the molecular level, substances present in the aroma of food, managing to differentiate samples of ham from Iberian pigs fed with acorn or feed. This new approach, which uses artificial intelligence to analyse the data, will simplify the analysis of aromas, and can be very useful to determine the traceability and quality of food, and fight against fraud.
Three projects of the Institute for Bioengineering of Catalonia (IBEC) will receive funding from “La Marató de TV3” to investigate different aspects of COVID-19. Thanks to the contributions received, the experts will deepen their understanding of the disease and its possible therapeutic solutions, study improvements in patient care processes, develop a system to predict the evolution of the respiratory system, and advance in the treatment of patients with pneumonia derived from COVID19.
The company Depuración de Aguas del Mediterráneo (DAM) and the Institute for Bioengineering of Catalonia (IBEC) develop a system equipped with chemical sensors that provides information, in real time, on the intensity and location of odor sources in the Waste Water Treatment Plants (WWTP). The system has been calibrated and validated under real operating conditions through several measurement campaigns at the Molina de Segura WWTP (Murcia).