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Estimation of Olfactory Sensitivity Using a Bayesian Adaptive Method

A peer-reviewed article of this preprint also exists.

Submitted:

24 April 2019

Posted:

26 April 2019

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Abstract
The ability to smell is crucial for most species as it enables the detection of environmental threats like smoke, fosters social interactions, and contributes to the sensory evaluation of food and eating behavior. The high prevalence of smell disturbances throughout the life span calls for a continuous effort to improve tools for quick and reliable assessment of olfactory function. Odor-dispensing pens, called Sniffin' Sticks, are an established method to deliver olfactory stimuli during diagnostic evaluation. We tested the suitability of a Bayesian adaptive algorithm (QUEST) to estimate olfactory sensitivity using Sniffin' Sticks by comparing QUEST sensitivity thresholds with those obtained using a procedure based on an established standard staircase protocol. Thresholds were measured twice with both procedures in two sessions (Test and Retest). Overall, both procedures performed similarly, with QUEST showing slightly less variability between measurements. Notably, participants were more frequently presented with the highest concentration during the QUEST procedure, potentially inducing measurement confounds due to adaptation and habituation effects. We conclude that the QUEST procedure might offer reduced testing time in some situations, and that further research is required to better understand and optimize the procedure for assessment of olfactory performance.
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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