Monitoring mental state during real life office work

Anne-Marie Brouwer; Loïs van de Water; Maarten Hogervorst; Wessel Kraaij; Jan Maarten Schraagen; Koen Hogenelst

doi:10.1007/978-3-319-91593-7_3

Monitoring mental state during real life office work

Anne-Marie Brouwer, Loïs van de Water, Maarten Hogervorst, Wessel Kraaij, Jan Maarten Schraagen, Koen Hogenelst

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

5 Citations (Scopus)

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Abstract

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.

Original language	English
Title of host publication	Symbiotic Interaction
Subtitle of host publication	6th International Workshop, Symbiotic 2017 Eindhoven, The Netherlands, December 18-19, 2017. Revised Selected Papers
Editors	Jaap Ham, Anna Spagnolli, Benjamin Blankertz, Luciano Gamberini, Giulio Jacucci
Place of Publication	Cham
Publisher	Springer
Pages	18-29
Number of pages	12
ISBN (Electronic)	978-3-319-91593-7
ISBN (Print)	978-3-319-91592-0
DOIs	https://doi.org/10.1007/978-3-319-91593-7_3
Publication status	Published - 2018
Event	Symbiotic 2017: 6th International Workshop on Symbiotic Interaction - De Zwarte Doos, Eindhoven, Netherlands Duration: 18 Dec 2017 → 19 Dec 2017 Conference number: 6

Publication series

Name	Lecture Notes in Computer Science
Publisher	Springer
Volume	10727
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	Symbiotic 2017
Abbreviated title	Symbiotic 2017
Country/Territory	Netherlands
City	Eindhoven
Period	18/12/17 → 19/12/17

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10.1007/978-3-319-91593-7_3

Cite this

Brouwer, A.-M., van de Water, L., Hogervorst, M., Kraaij, W., Schraagen, J. M., & Hogenelst, K. (2018). Monitoring mental state during real life office work. In J. Ham, A. Spagnolli, B. Blankertz, L. Gamberini, & G. Jacucci (Eds.), Symbiotic Interaction: 6th International Workshop, Symbiotic 2017 Eindhoven, The Netherlands, December 18-19, 2017. Revised Selected Papers (pp. 18-29). (Lecture Notes in Computer Science; Vol. 10727). Springer. https://doi.org/10.1007/978-3-319-91593-7_3

Brouwer, Anne-Marie ; van de Water, Loïs ; Hogervorst, Maarten et al. / Monitoring mental state during real life office work. Symbiotic Interaction: 6th International Workshop, Symbiotic 2017 Eindhoven, The Netherlands, December 18-19, 2017. Revised Selected Papers. editor / Jaap Ham ; Anna Spagnolli ; Benjamin Blankertz ; Luciano Gamberini ; Giulio Jacucci. Cham : Springer, 2018. pp. 18-29 (Lecture Notes in Computer Science).

@inproceedings{e721a808eadb46a5a27b0f11b37fe233,

title = "Monitoring mental state during real life office work",

abstract = "Monitoring an individual{\textquoteright}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 {\textquoteleft}ground truth{\textquoteright} 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.",

author = "Anne-Marie Brouwer and {van de Water}, Lo{\"i}s and Maarten Hogervorst and Wessel Kraaij and Schraagen, {Jan Maarten} and Koen Hogenelst",

note = "Funding Information: Acknowledgements. We would like to thank our TNO colleagues Bart Joosten and Thymen Wabeke for the technical setup; Leon Wiertz from Noldus for help with the face reader data; Jan-Willem Streefkerk (TNO) for project management. This publication was supported by the Dutch national program COMMIT (project P7 SWELL), and TNO Early Research Programs Making Sense of Big Data (Judith Dijk) and Human Enhancement. Publisher Copyright: {\textcopyright} Springer International Publishing AG, part of Springer Nature 2018.; Symbiotic 2017 : 6th International Workshop on Symbiotic Interaction, Symbiotic 2017 ; Conference date: 18-12-2017 Through 19-12-2017",

year = "2018",

doi = "10.1007/978-3-319-91593-7_3",

language = "English",

isbn = "978-3-319-91592-0",

series = "Lecture Notes in Computer Science",

publisher = "Springer",

pages = "18--29",

editor = "Jaap Ham and Anna Spagnolli and Benjamin Blankertz and Luciano Gamberini and Giulio Jacucci",

booktitle = "Symbiotic Interaction",

address = "Germany",

}

Brouwer, A-M, van de Water, L, Hogervorst, M, Kraaij, W, Schraagen, JM & Hogenelst, K 2018, Monitoring mental state during real life office work. in J Ham, A Spagnolli, B Blankertz, L Gamberini & G Jacucci (eds), Symbiotic Interaction: 6th International Workshop, Symbiotic 2017 Eindhoven, The Netherlands, December 18-19, 2017. Revised Selected Papers. Lecture Notes in Computer Science, vol. 10727, Springer, Cham, pp. 18-29, Symbiotic 2017, Eindhoven, Netherlands, 18/12/17. https://doi.org/10.1007/978-3-319-91593-7_3

Monitoring mental state during real life office work. / Brouwer, Anne-Marie; van de Water, Loïs; Hogervorst, Maarten et al.
Symbiotic Interaction: 6th International Workshop, Symbiotic 2017 Eindhoven, The Netherlands, December 18-19, 2017. Revised Selected Papers. ed. / Jaap Ham; Anna Spagnolli; Benjamin Blankertz; Luciano Gamberini; Giulio Jacucci. Cham: Springer, 2018. p. 18-29 (Lecture Notes in Computer Science; Vol. 10727).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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T1 - Monitoring mental state during real life office work

AU - Brouwer, Anne-Marie

AU - van de Water, Loïs

AU - Hogervorst, Maarten

AU - Kraaij, Wessel

AU - Schraagen, Jan Maarten

AU - Hogenelst, Koen

N1 - Conference code: 6

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N2 - 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.

AB - 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.

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BT - Symbiotic Interaction

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A2 - Spagnolli, Anna

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A2 - Jacucci, Giulio

PB - Springer

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ER -

Brouwer AM, van de Water L, Hogervorst M, Kraaij W, Schraagen JM, Hogenelst K. Monitoring mental state during real life office work. In Ham J, Spagnolli A, Blankertz B, Gamberini L, Jacucci G, editors, Symbiotic Interaction: 6th International Workshop, Symbiotic 2017 Eindhoven, The Netherlands, December 18-19, 2017. Revised Selected Papers. Cham: Springer. 2018. p. 18-29. (Lecture Notes in Computer Science). doi: 10.1007/978-3-319-91593-7_3

Monitoring mental state during real life office work

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