Crowdsourcing Affective Annotations via fNIRS-BCI

Affective annotation refers to the process of labeling media content based on emotions they evoke. Since such experiences are inherently subjective and depend individual differences, central challenge is associating digital with its affective, interindividual experience. Here, we present a first-of-its-kind methodology for affective directly from brain signals by monitoring experience crowd individuals via functional near-infrared spectroscopy (fNIRS). An experiment reported in which fNIRS was recorded 31 participants develop brain-computer interface (BCI) annotation. Brain evoked images were used draw predictions about dimensions that characterize stimuli. By combining annotations, results show responses can accurate performance improving significantly increases size. Our demonstrates proof-of-concept source annotations BCI users without requiring any auxiliary mental or physical interaction.