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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 Chockalingam
Boredom 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 Ergonomics

Event location

Vienna

Event type

conference

Event date

1-3 September 2014

Department affiliated with

  • BSMS Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

Legacy Posted Date

2014-06-27

First Open Access (FOA) Date

2014-06-27

First Compliant Deposit (FCD) Date

2014-06-26

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