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Demo: Towards Recognition of Rich Non-Negative Emotions Using Daily Wearable Devices

Published: 01 November 2015 Publication History

Abstract

Recognizing user emotional states while running entertainment applications such as playing game or watching video is very important to understand and improve user experience. In this work, we designed a practical system using wearable physiological sensors including skin electrical conductivity and photoplethysmography (PPG) to recognize popular non-negative emotions that people experience when they watch videos or play games on their mobile devices. We demonstrates how our system recognizes emotional states in two phases: (1) classifying the levels of arousal (high or low) and valence (positive or neutral) at the accuracy of 94.74% and 78.95% respectively; (2) recognizing three non-negative emotions: excitement, contentment, amusement by mapping arousal and valence levels using Russel circumplex model of affect.

References

[1]
C. L. Lisetti and F. Nasoz, "Using noninvasive wearable computers to recognize human emotions from physiological signals," EURASIP journal on applied signal processing, vol. 2004, pp. 1672{1687, 2004.
[2]
J. A. Russell, "A circumplex model of affect.," Journal of personality and social psychology, vol. 39, no. 6, p. 1161, 1980.
[3]
A. Burns, B. R. Greene, M. J. McGrath, T. J. O'Shea, B. Kuris, S. M. Ayer, F. Stroiescu, and V. Cionca, "Shimmer-a wireless sensor platform for noninvasive biomedical research," Sensors Journal, IEEE, vol. 10, no. 9, pp. 1527--1534, 2010.

Cited By

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  • (2020)VIMESProceedings of the 28th ACM International Conference on Multimedia10.1145/3394171.3413663(3191-3200)Online publication date: 12-Oct-2020
  • (2018)EngageMonProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/31917452:1(1-27)Online publication date: 26-Mar-2018

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  1. Demo: Towards Recognition of Rich Non-Negative Emotions Using Daily Wearable Devices

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    Published In

    cover image ACM Conferences
    SenSys '15: Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems
    November 2015
    526 pages
    ISBN:9781450336314
    DOI:10.1145/2809695
    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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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 01 November 2015

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    Author Tags

    1. arousal
    2. emotion recognition
    3. physiological
    4. sensor

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    • Demonstration

    Funding Sources

    • National Research Foundation Singapore Interactive Digital Media (IDM) Strategic Research Programme

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    Acceptance Rates

    SenSys '15 Paper Acceptance Rate 27 of 132 submissions, 20%;
    Overall Acceptance Rate 174 of 867 submissions, 20%

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    Cited By

    View all
    • (2020)VIMESProceedings of the 28th ACM International Conference on Multimedia10.1145/3394171.3413663(3191-3200)Online publication date: 12-Oct-2020
    • (2018)EngageMonProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/31917452:1(1-27)Online publication date: 26-Mar-2018

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