Witchel_text_features_engagement_ECCE_15june2014.pdf (1.71 MB)
A time series feature of variability to detect two types of boredom from motion capture of the head and shoulders
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posted on 2023-06-08, 17:40 authored by Harry WitchelHarry Witchel, Carina E I Westling, Julian Tee, Rob Needham, Aoife Healy, Nachiappan ChockalingamBoredom and disengagement metrics are crucial to the correctly timed implementation of adaptive interventions in interactive systems. psychological research suggests that boredom (which other HCI teams have been able to partially quantify with pressure-sensing chair mats) is actually a composite: lethargy and restlessness. Here we present an innovative approach to the measurement and recognition of these two kinds of boredom, based on motion capture and video analysis of changes in head and shoulder positions. Discrete, three-minute, computer-presented stimuli (games, quizzes, films and music) covering a spectrum from engaging to boring/disengaging were used to elicit changes in cognitive/emotional states in seated, healthy volunteers. Interaction with the stimuli occurred with a handheld trackball instead of a mouse, so movements were assumed to be non-instrumental. Our results include a feature (standard deviation of windowed ranges) that may be more specific to boredom than mean speed of head movement, and that could be implemented in computer vision algorithms for disengagement detection.
History
Publication status
- Published
File Version
- Accepted version
Presentation Type
- paper
Event name
ECCE 2014 European Conference on Cognitive ErgonomicsEvent location
ViennaEvent type
conferenceEvent date
1-3 September 2014Department affiliated with
- BSMS Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2014-06-27First Open Access (FOA) Date
2014-06-27First Compliant Deposit (FCD) Date
2014-06-26Usage metrics
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