Computational parallels between the biological olfactory pathway and its analogue `The Electronic Nose':

Pearce, Timothy Charles

doi:10.1016/s0303-2647(96)01661-9

Cited by 71 publications

(44 citation statements)

References 60 publications

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“…ART is a plausible model of human information processing but, unfortunately, has a tendency to over-fit, which result in a proliferation of categories in the presence of noisy data [70]. Finally, the study of signal-processing mechanisms in the biological olfactory system constitutes a promising direction for future work [67], [112]. The wealth of computational models of the olfactory pathway developed in biological cybernetics and computational neuroscience [113]- [116] can serve as a starting point to mimic biological olfactory processes including (i) receptor-glomerular convergence for improved sensitivity and fault tolerance in large sensor arrays, (ii) bulbar excitatory-inhibitory dynamics for odor contrast enhancement and normalization, (iii) cortical associative memory functions for pattern completion, and (iv) centrifugal modulation of the olfactory bulb for chemosensory adaptation.…”

Section: Discussionmentioning

confidence: 99%

Pattern analysis for machine olfaction: a review

2002

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Abstract-Pattern analysis constitutes a critical building block in the development of gas sensor array instruments capable of detecting, identifying, and measuring volatile compounds, a technology that has been proposed as an artificial substitute of the human olfactory system. The successful design of a pattern analysis system for machine olfaction requires a careful consideration of the various issues involved in processing multivariate data: signal-preprocessing, feature extraction, feature selection, classification, regression, clustering, and validation. A considerable number of methods from statistical pattern recognition, neural networks, chemometrics, machine learning, and biological cybernetics has been used to process electronic nose data. The objective of this review paper is to provide a summary and guidelines for using the most widely used pattern analysis techniques, as well as to identify research directions that are at the frontier of sensor-based machine olfaction.

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Section: Discussionmentioning

confidence: 99%

Pattern analysis for machine olfaction: a review

2002

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“…Although several commercial E-Nose products are available on the market, many of them are bulky, having complex odor sensing system and user interface software, which makes them unsuitable for portable applications [1][2][3][4][5][6][7]. There are number of modern small electronic noses, such as the "Diagnose" from C-it of the Netherlands (11 × 18 × 7 cm) and the Artinose from SYSCA AG Germany (17 × 26 × 14 cm), but they are still too expensive for widespread adoption [1].…”

Section: Introductionmentioning

confidence: 99%

“…In addition, existing electronic noses are still unable to perform particularly well because the most commonly used sensors are inadequate for the discriminating tasks required of them [1][2][3]. As such, E-Nose products are still difficult to commercialize and the quest for a small, lightweight, and inexpensive E-Nose system has continued in recent years [1][2][3][4][5][6].…”

Section: Introductionmentioning

confidence: 99%

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Development of an E-Nose Using Metal Oxide Semiconductor Sensors for the Classification of Climacteric Fruits

Kanade¹,

Shaligram²

2014

IJSER

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Abstract-The present work deals with the development of an artificial olfactory system as a nondestructive instrument to be used for classification of different fruits and exploration of its application in measurement of fruit ripening stages. The fruits chosen for this study are Guava, Orange and Banana. The developed system comprises of an array of eight metal oxide semiconductor gas sensors, odor delivery system, interface circuit board, data acquisition card and self programmed Data acquisition as well as analysis software using LabVIEW. The design of this tool focused on studying the response of a sensor array to various VOC vapors released by fruit during ripening and optimizing the data acquisition, signal preprocessing, storage, feature extraction parameters using principle component analysis. It was found that developed e-nose can discriminate the patterns of volatile organic compounds (VOCs) from three fruits taken for experimentation. These three fruits, as analysed by the principal component analysis (PCA). With further validation and development, this e-nose may become very useful for monitoring the exhaled as a screening device for discriminating the fruits. This e-nose can also be used for classification and grading of different climacteric fruits on the basis of their ripening stages.

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“…These signals are subsequently analyzed by pattern recognition software. The pattern recognition software corresponds to the cerebral cortex of the brain and is able to classify and memorize odors (3,42,43).…”

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confidence: 99%

Use of an Electronic Nose To DiagnoseMycobacterium bovisInfection in Badgers and Cattle

et al. 2005

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It is estimated that more than 50 million cattle are infected with Mycobacterium bovis worldwide, resulting in severe economic losses. Current diagnosis of tuberculosis (TB) in cattle relies on tuberculin skin testing, and when combined with the slaughter of test-positive animals, it has significantly reduced the incidence of bovine TB. The failure to eradicate bovine TB in Great Britain has been attributed in part to a reservoir of the infection in badgers (Meles meles). Accurate and reliable diagnosis of infection is the cornerstone of TB control. Bacteriological diagnosis has these characteristics, but only with samples collected postmortem. Unlike significant wild animal reservoirs of M. bovis that are considered pests in other countries, such as the brushtail possum (Trichosurus vulpecula) in New Zealand, the badger and its sett are protected under United Kingdom legislation (The Protection of Badgers Act 1992). Therefore, an accurate in vitro test for badgers is needed urgently to determine the extent of the reservoir of infection cheaply and without destroying badgers. For cattle, a rapid on-farm test to complement the existing tests (the skin test and gamma interferon assay) would be highly desirable. To this end, we have investigated the potential of an electronic nose (EN) to diagnose infection of cattle or badgers with M. bovis, using a serum sample. Samples were obtained from both experimentally infected badgers and cattle, as well as naturally infected badgers. Without exception, the EN was able to discriminate infected animals from controls as early as 3 weeks after infection with M. bovis, the earliest time point examined postchallenge. The EN approach described here is a straightforward alternative to conventional methods of TB diagnosis, and it offers considerable potential as a sensitive, rapid, and cost-effective means of diagnosing M. bovis infection in cattle and badgers.

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Computational parallels between the biological olfactory pathway and its analogue `The Electronic Nose':

Cited by 71 publications

References 60 publications

Pattern analysis for machine olfaction: a review

Pattern analysis for machine olfaction: a review

Development of an E-Nose Using Metal Oxide Semiconductor Sensors for the Classification of Climacteric Fruits

Use of an Electronic Nose To DiagnoseMycobacterium bovisInfection in Badgers and Cattle

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