Monitoring mental state during real life office work
conference paper
Monitoring an individual’s mental state using unobtrusively measured signals is regarded as an essential element in symbiotic human-machine systems. However, it is not straightforward to model the relation between mental state and such signals in real life, without resorting to (unnatural) emotion induction. We recorded heart rate, facial expression and computer activity of nineteen participants while working at the computer for ten days. In order to obtain ‘ground truth’ emotional state, participants indicated their current emotion using a valence-arousal affect grid every 15 min. We found associations between valence/arousal and the unobtrusively measured variables. There was some first success to predict subjective valence/arousal using personal classification models. Thus, real-life office emotions appear to vary enough, and can be reported well enough, to uncover relations with unobtrusively measured variables. This is required to be able to monitor individuals in real life more fine-grained than the frequency with which emotion is probed.
Topics
TNO Identifier
789885
ISBN
978-3-319-91592-0
Publisher
Springer
Source title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
6th International Workshop on Symbiotic Interaction, SYMBIOTIC 2017. 18 December 2017 through 19 December 2017
6th International Workshop on Symbiotic Interaction, SYMBIOTIC 2017. 18 December 2017 through 19 December 2017
Editor(s)
Ham, J.
Spagnolli, A.
Blankertz, B.
Gamberini, L.
Jacucci, G.
Spagnolli, A.
Blankertz, B.
Gamberini, L.
Jacucci, G.
Pages
18–29
Files
To receive the publication files, please send an e-mail request to TNO Repository.