Bioinspired early detection through gas flow modulation in chemo-sensory systems
| Autor: | A. Gutierrez-Galvez, Jordi Fonollosa, Andrey Ziyatdinov, Luis Fernandez, Alexandre Perera, Santiago Marco |
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| Přispěvatelé: | Universitat Politècnica de Catalunya. Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya. SISBIO - Senyals i Sistemes Biomèdics, Universitat de Barcelona |
| Jazyk: | angličtina |
| Rok vydání: | 2015 |
| Předmět: |
Optimization
Flow modulation Computer science Odors Chemical detectors Olfacte Sniffing Early detection Nanotechnology Sensory system Stimulus (physiology) Nas electrònic Electronic nose Sensors químics Olors Biomimetics Gas sensor array Materials Chemistry Electrical and Electronic Engineering Machine olfaction Instrumentation Detectors químics Transient Metals and Alloys Array Sampling (statistics) Gas detectors Condensed Matter Physics Detectors de gasos Regression Surfaces Coatings and Films Electronic Optical and Magnetic Materials Enginyeria química::Biotecnologia [Àrees temàtiques de la UPC] Smell MOX sensor Informàtica::Intel·ligència artificial [Àrees temàtiques de la UPC] Biological system |
| Zdroj: | Recercat. Dipósit de la Recerca de Catalunya instname Dipòsit Digital de la UB Universidad de Barcelona UPCommons. Portal del coneixement obert de la UPC Universitat Politècnica de Catalunya (UPC) |
| Popis: | 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. (C) 2014 Elsevier B.V. All rights reserved. |
| Databáze: | OpenAIRE |
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