Data-science based analysis of perceptual spaces of odors in olfactory loss

Abstract Diminished sense of smell impairs the quality of life but olfactorily disabled people are hardly considered in measures of disability inclusion. We aimed to stratify perceptual characteristics and odors according to the extent to which they are perceived differently with reduced sense of sm...

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Autores principales:	Jörn Lötsch, Alfred Ultsch, Antje Hähner, Vivien Willgeroth, Moustafa Bensafi, Andrea Zaliani, Thomas Hummel
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/2e08aa1f2de74251906b82a7ccf1613e
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spelling	oai:doaj.org-article:2e08aa1f2de74251906b82a7ccf1613e2021-12-02T15:45:31ZData-science based analysis of perceptual spaces of odors in olfactory loss10.1038/s41598-021-89969-92045-2322https://doaj.org/article/2e08aa1f2de74251906b82a7ccf1613e2021-05-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-89969-9https://doaj.org/toc/2045-2322Abstract Diminished sense of smell impairs the quality of life but olfactorily disabled people are hardly considered in measures of disability inclusion. We aimed to stratify perceptual characteristics and odors according to the extent to which they are perceived differently with reduced sense of smell, as a possible basis for creating olfactory experiences that are enjoyed in a similar way by subjects with normal or impaired olfactory function. In 146 subjects with normal or reduced olfactory function, perceptual characteristics (edibility, intensity, irritation, temperature, familiarity, hedonics, painfulness) were tested for four sets of 10 different odors each. Data were analyzed with (i) a projection based on principal component analysis and (ii) the training of a machine-learning algorithm in a 1000-fold cross-validated setting to distinguish between olfactory diagnosis based on odor property ratings. Both analytical approaches identified perceived intensity and familiarity with the odor as discriminating characteristics between olfactory diagnoses, while evoked pain sensation and perceived temperature were not discriminating, followed by edibility. Two disjoint sets of odors were identified, i.e., d = 4 “discriminating odors” with respect to olfactory diagnosis, including cis-3-hexenol, methyl salicylate, 1-butanol and cineole, and d = 7 “non-discriminating odors”, including benzyl acetate, heptanal, 4-ethyl-octanoic acid, methional, isobutyric acid, 4-decanolide and p-cresol. Different weightings of the perceptual properties of odors with normal or reduced sense of smell indicate possibilities to create sensory experiences such as food, meals or scents that by emphasizing trigeminal perceptions can be enjoyed by both normosmic and hyposmic individuals.Jörn LötschAlfred UltschAntje HähnerVivien WillgerothMoustafa BensafiAndrea ZalianiThomas HummelNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Jörn Lötsch Alfred Ultsch Antje Hähner Vivien Willgeroth Moustafa Bensafi Andrea Zaliani Thomas Hummel Data-science based analysis of perceptual spaces of odors in olfactory loss
description	Abstract Diminished sense of smell impairs the quality of life but olfactorily disabled people are hardly considered in measures of disability inclusion. We aimed to stratify perceptual characteristics and odors according to the extent to which they are perceived differently with reduced sense of smell, as a possible basis for creating olfactory experiences that are enjoyed in a similar way by subjects with normal or impaired olfactory function. In 146 subjects with normal or reduced olfactory function, perceptual characteristics (edibility, intensity, irritation, temperature, familiarity, hedonics, painfulness) were tested for four sets of 10 different odors each. Data were analyzed with (i) a projection based on principal component analysis and (ii) the training of a machine-learning algorithm in a 1000-fold cross-validated setting to distinguish between olfactory diagnosis based on odor property ratings. Both analytical approaches identified perceived intensity and familiarity with the odor as discriminating characteristics between olfactory diagnoses, while evoked pain sensation and perceived temperature were not discriminating, followed by edibility. Two disjoint sets of odors were identified, i.e., d = 4 “discriminating odors” with respect to olfactory diagnosis, including cis-3-hexenol, methyl salicylate, 1-butanol and cineole, and d = 7 “non-discriminating odors”, including benzyl acetate, heptanal, 4-ethyl-octanoic acid, methional, isobutyric acid, 4-decanolide and p-cresol. Different weightings of the perceptual properties of odors with normal or reduced sense of smell indicate possibilities to create sensory experiences such as food, meals or scents that by emphasizing trigeminal perceptions can be enjoyed by both normosmic and hyposmic individuals.
format	article
author	Jörn Lötsch Alfred Ultsch Antje Hähner Vivien Willgeroth Moustafa Bensafi Andrea Zaliani Thomas Hummel
author_facet	Jörn Lötsch Alfred Ultsch Antje Hähner Vivien Willgeroth Moustafa Bensafi Andrea Zaliani Thomas Hummel
author_sort	Jörn Lötsch
title	Data-science based analysis of perceptual spaces of odors in olfactory loss
title_short	Data-science based analysis of perceptual spaces of odors in olfactory loss
title_full	Data-science based analysis of perceptual spaces of odors in olfactory loss
title_fullStr	Data-science based analysis of perceptual spaces of odors in olfactory loss
title_full_unstemmed	Data-science based analysis of perceptual spaces of odors in olfactory loss
title_sort	data-science based analysis of perceptual spaces of odors in olfactory loss
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/2e08aa1f2de74251906b82a7ccf1613e
work_keys_str_mv	AT jornlotsch datasciencebasedanalysisofperceptualspacesofodorsinolfactoryloss AT alfredultsch datasciencebasedanalysisofperceptualspacesofodorsinolfactoryloss AT antjehahner datasciencebasedanalysisofperceptualspacesofodorsinolfactoryloss AT vivienwillgeroth datasciencebasedanalysisofperceptualspacesofodorsinolfactoryloss AT moustafabensafi datasciencebasedanalysisofperceptualspacesofodorsinolfactoryloss AT andreazaliani datasciencebasedanalysisofperceptualspacesofodorsinolfactoryloss AT thomashummel datasciencebasedanalysisofperceptualspacesofodorsinolfactoryloss
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Data-science based analysis of perceptual spaces of odors in olfactory loss

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