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Body odors play a subtle, but crucial role in many social situations. They are influenced by genetic connections, hormonal changes, current inflammatory processes, and diet, among other factors. Because the apocrine sweat glands are adrenaline sensitive, physiological and emotional arousal also alter body odor. Therefore, body odors enable the recognition and discrimination between different body states, emotions or diseases in our fellow human beings. Although this often happens unconsciously, piloting survey data show marked differences in the way, we describe body odors; e.g., a body odor that originates from exercise is most often described as "sweaty," whereas a body odor from a sick person is referred to as "biting." The goal of this study is to develop a valid and reliable matrix that captures how people perceive and describe different body odors. To this end, an online survey will be conducted including a minimum of n=1000 participants from different countries within and beyond Europe. Each country or language with at least n=100 participants will be included in the sample. Each participant is asked, in their respective language, to name three or more words or phrases that describe body odors in four different states (healthy, sick, stressed, after exercise) and from five body parts (from armpit, mouth, feet, male and female genitalia). The resulting body odor vocabulary from each language will be compared and the most often named words in each language will be used to generate a body odor description matrix. The study is part of the EU-funded project “Smart Electronic Olfaction for Body Odor Diagnostics (SMELLODI)” with the overall goal to digitize olfaction and make it usable for health applications, e.g. for patients with olfactory disorders.

This project is open access and publicly accessible.

 

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Recent Submissions

  • Intermediate dataset of clustered body odor descriptorsOpen Access Icon 

    Bierling, Antonie Louise; Croy, Ilona (Technische Universität DresdenProf. Dr. Ilona CroyFriedrich-Schiller-Universität Jena, 2023)
    The dataset shows the intermediate results from 1060 participants from nine countries and five languages: German (Germany, Austria, 414 participants), English (United States, Canada, Great Britain, Sweden, 133 participants), ...