Abstract
A primary goal for artificial nose (eNose) technology is to report perceptual qualities of novel odors. Currently, however, eNoses primarily detect and discriminate between odorants they previously “learned”. We tuned an eNose to human odor pleasantness estimates. We then used the eNose to predict the pleasantness of novel odorants, and tested these predictions in naïve subjects who had not participated in the tuning procedure. We found that our apparatus generated odorant pleasantness ratings with above 80% similarity to average human ratings, and with above 90% accuracy at discriminating between categorically pleasant or unpleasant odorants. Similar results were obtained in two cultures, native Israeli and native Ethiopian, without retuning of the apparatus. These findings suggest that unlike in vision and audition, in olfaction there is a systematic predictable link between stimulus structure and stimulus pleasantness. This goes in contrast to the popular notion that odorant pleasantness is completely subjective, and may provide a new method for odor screening and environmental monitoring, as well as a critical building block for digital transmission of smell.
Highlights
Dravnieks envisioned an artificial nose as ‘‘an instrument that would inspect samples of odorous air and report the intensity and quality of an odor without the intervention of a human nose’’ [1]
Electronic noses are devices aimed at mimicking animal noses
ENoses have been tested in applications ranging from disease diagnosis to space-ship interior environmental monitoring
Summary
Dravnieks envisioned an artificial (or electronic) nose as ‘‘an instrument that would inspect samples of odorous air and report the intensity and quality of an odor without the intervention of a human nose’’ [1]. ENoses have since been developed [2,3,4,5,6,7,8,9,10], and serve in tasks of odor detection and discrimination [7,11,12,13], they are rarely used for reporting odor quality. The sensors inside eNoses can be made of a variety of technologies, but in all cases a certain physical property is measured and a set of signals is generated. The set of activated sensors and their signals characterize the odor (sometimes refered as an odor fingerprint). An important difference between eNoses and analyte detectors such as gas chromatographs, is that whereas the latter are aimed at identifying the components that contribute to an odor, eNoses can be used to identify, as a whole, the mixture of components that together form an odor
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