Preprint Open Access

Estimation of olfactory sensitivity using a Bayesian adaptive method

Höchenberger, Richard; Ohla, Kathrin

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 exhibited considerable overlap with QUEST displaying slightly higher test-retest correlations, less variability between measurements, and reduced testing duration. Notably, participants were more frequently presented with the highest concentration during the QUEST which may foster adaptation  and habituation effects. We conclude that further research is required to better understand and optimize the procedure for assessment of olfactory performance.

Files (6.9 MB)
Name Size
Hoechenberger & Ohla - Estimation of Olfactory Sensitivity Using a Bayesian Adaptive Method - Preprint - Rev 2.pdf
2.3 MB Download
20.2 kB Download
4.6 MB Download
All versions This version
Views 225103
Downloads 23489
Data volume 438.8 MB199.7 MB
Unique views 20795
Unique downloads 18872


Cite as