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EngageMeter: A System for Implicit Audience Engagement Sensing Using Electroencephalography

Published: 02 May 2017 Publication History

Abstract

Obtaining information about audience engagement in presentations is a valuable asset for presenters in many domains. Prior literature mostly utilized explicit methods of collecting feedback which induce distractions, add workload on audience and do not provide objective information to presenters. We present EngageMeter - a system that allows fine-grained information on audience engagement to be obtained implicitly from multiple brain-computer interfaces (BCI) and to be fed back to presenters for real time and post-hoc access. Through evaluation during an HCI conference (Naudience=11, Npresenters=3) we found that EngageMeter provides value to presenters (a) in real-time, since it allows reacting to current engagement scores by changing tone or adding pauses, and (b) in post-hoc, since presenters can adjust their slides and embed extra elements. We discuss how EngageMeter can be used in collocated and distributed audience sensing as well as how it can aid presenters in long term use.

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    cover image ACM Conferences
    CHI '17: Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems
    May 2017
    7138 pages
    ISBN:9781450346559
    DOI:10.1145/3025453
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    Published: 02 May 2017

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    Author Tags

    1. audience feedback
    2. bci
    3. eeg
    4. physiological sensing

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    Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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    Cited By

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    • (2024)Gamified SuccessEnhancing Engagement With Gamification10.4018/979-8-3693-8322-3.ch007(157-176)Online publication date: 27-Dec-2024
    • (2024)EduLive: Re-Creating Cues for Instructor-Learners Interaction in Educational Live Streams with Learners' Transcript-Based AnnotationsProceedings of the ACM on Human-Computer Interaction10.1145/36869608:CSCW2(1-33)Online publication date: 8-Nov-2024
    • (2024)Toward Understanding the Impact of Visualized Focus Levels in Virtual Reality on User Presence and ExperienceProceedings of the ACM on Human-Computer Interaction10.1145/36765278:MHCI(1-30)Online publication date: 24-Sep-2024
    • (2024)Co-Here: an expressive videoconferencing module for implicit affective interactionProceedings of the 50th Graphics Interface Conference10.1145/3670947.3670975(1-13)Online publication date: 3-Jun-2024
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    • (2024)Investigating the Effects of Real-time Student Monitoring Interface on Instructors’ Monitoring Practices in Online TeachingProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642845(1-11)Online publication date: 11-May-2024
    • (2024)Exploring Depth-based Perception Conflicts in Virtual Reality through Error-Related Potentials2024 IEEE Conference Virtual Reality and 3D User Interfaces (VR)10.1109/VR58804.2024.00097(774-784)Online publication date: 16-Mar-2024
    • (2024)Neurocognitive Approach for Assessing Visual Engagement in Neuromarketing2024 Horizons of Information Technology and Engineering (HITE)10.1109/HITE63532.2024.10777255(1-6)Online publication date: 15-Oct-2024
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