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A biomimetic approach to machine olfaction, featuring a very large-scale chemical sensor array and embedded neuro-bio-inspired computation
KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.ORCID iD: 0000-0002-2358-7815
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2014 (English)In: Microsystem Technologies: Micro- and Nanosystems Information Storage and Processing Systems, ISSN 0946-7076, E-ISSN 1432-1858, Vol. 20, no 4-5, 729-742 p.Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2014. Vol. 20, no 4-5, 729-742 p.
Keyword [en]
Abstracting, Algorithms, Chemical sensors, Conducting polymers, Data processing, Embedded systems, Robots algorithmic solutions, Biomimetic approaches, Chemical information, Chemical instrumentation, Computational neuroscience, Large-scale chemical sensor arrays, Olfactory receptor neurons, Processing capability
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:kth:diva-145278DOI: 10.1007/s00542-013-2020-8ISI: 000334076600023Scopus ID: 2-s2.0-84897554856OAI: oai:DiVA.org:kth-145278DiVA: diva2:717445
Conference
Conference on Smart Sensors, Actuators and MEMS within the SPIE Europe Symposium on Microtechnologies, April 24-26, 2013, Grenoble, France
Note

QC 20140515

Available from: 2014-05-15 Created: 2014-05-15 Last updated: 2017-12-05Bibliographically approved

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