Maelle Moranges

In Basic protocols on emotions, senses, and foods

Abstract In the field of food, as in other fields, the measurement of emotional responses to food and their sensory properties is a major challenge. In the present protocol, we propose a step-by-step procedure that allows a physiological description of odors, aromas, and their hedonic properties. The method rooted in subgroup discovery belongs to the field of data science and especially data mining. It is still little used in the field of food and is based on a descriptive modeling of emotions on the basis of human physiological responses.

Using subgroup discovery to relate odor pleasantness and intensity to peripheral nervous system reactions

By Maelle Moranges, Marc Plantevit, Moustafa Bensafi

2022-07-24

In IEEE Transactions on Affective Computing

Abstract Activation of the autonomic nervous system is a primary characteristic of human hedonic responses to sensory stimuli. For smells, general tendencies of physiological reactions have been described using classical statistics. However, these physiological variations are generally not quantified precisely; each psychophysiological parameter has very often been studied separately and individual variability was not systematically considered. The current study presents an innovative approach based on data mining, whose goal is to extract knowledge from a dataset.

Peripheral nervous system responses to food stimuli: Analysis using data science approaches

Using subgroup discovery to relate odor pleasantness and intensity to peripheral nervous system reactions

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