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Towards cognitive awareness: a mobile context modeling- and notification-based approach

Published: 11 September 2017 Publication History

Abstract

Awareness about one's own cognitive state is a critical first step towards better physical, physiological, psychological, behavioral, and social health. When users are aware of their mental states - particularly those which might be detrimental to their health (e.g. high stress, low excitement) - they can take the necessary steps to either alter their behavior, or find ways to effectively cope with it. From a technology viewpoint, it is thus important to find ways to detect a user's cognitive state as unobtrusively as possible, and thereafter either inform or assist the users in coping with it. Through this position paper, we wish to discuss the potential of using mobile context data gathered from a user's smartphone to infer the user's cognitive state, and thereafter using mobile notifications to deliver timely intervention messages.

References

[1]
Campbell, Andrew, and Tanzeem Choudhury. "From smart to cognitive phones." IEEE Pervasive Computing 3.11 (2012): 7--11.
[2]
Emotiv Insight EEG headset. https://www.emotiv.com/insight/
[3]
Mashhadi A., Mathur A., Broeck M., Vanderhulst G., Kawsar F. Understanding the Impact of Personal Feedback on Face-to-Face Interactions in the Workplace. In Proceedings of ICMI '16.
[4]
Picard R., Vyzas E., and Healey J. Toward machine emotional intelligence: Analysis of affective physiological state. Pattern Analysis and Machine Intelligence, IEEE Transactions on 23, 10 (2001).
[5]
Pielot M et al. When attention is not scarcedetecting boredom from mobile phone usage. In Proceedings of UbiComp '15. ACM.
[6]
LiKamWa R. et al. Moodscope: Building a mood sensor from smartphone usage patterns. In Proceeding of MobiSys '13. ACM.
[7]
Bixler R., D'Mello S. Detecting boredom and engagement during writing with keystroke analysis, task appraisals, and stable traits. In Proceedings of IUI '13.
[8]
Bogomolov A. et al. Happiness recognition from mobile phone data. In Social Computing (SocialCom), 2013
[9]
Mathur, A., Lane, N.D. and Kawsar, F. Engagement-aware computing: Modelling user engagement from mobile contexts. In Proceedings of UbiComp '16. ACM.

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  1. Towards cognitive awareness: a mobile context modeling- and notification-based approach

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    cover image ACM Conferences
    UbiComp '17: Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers
    September 2017
    1089 pages
    ISBN:9781450351904
    DOI:10.1145/3123024
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    New York, NY, United States

    Publication History

    Published: 11 September 2017

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    Author Tags

    1. EEG headsets
    2. cognitive awareness
    3. context modeling
    4. intervention design
    5. mobile notifications

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    UbiComp '17

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    Overall Acceptance Rate 764 of 2,912 submissions, 26%

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