Inferring Emotional Responses via fNIRS Neuroimaging

Information retrieval (IR) relies on a general notion of relevance, which is used as the principal foundation for ranking and evaluation methods. However, IR does not account for more a nuanced affective experience. In a recent paper we have published, we consider the emotional response decoded directly from the human brain as an alternative dimension of relevance.

We report an experiment covering seven different scenarios in which we measure and predict how users emotionally respond to visual image contents by using functional near-infrared spectroscopy (fNIRS) neuroimaging on two commonly used affective dimensions: valence (negativity and positivity) and arousal (boredness and excitedness). Our results show that affective states can be successfully decoded using fNIRS, and utilized to complement the present notion of relevance in IR studies.

This work will be presented at SIGIR’23 in Taipei, Taiwan. SIGIR is the flagship conference on Information Retrieval.


Tuukka Ruotsalo, Kalle Mäkelä, Michiel Spapé and Luis A. Leiva. Affective Relevance: Inferring Emotional Responses via fNIRS Neuroimaging. Proc. SIGIR’23.

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