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Quantifying emotional states based on body language data using non invasive sensors
Ishan Behoora
, Conrad S. Tucker
School of Engineering Design and Innovation
Research output
:
Chapter in Book/Report/Conference proceeding
›
Conference contribution
5
Scopus citations
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Dive into the research topics of 'Quantifying emotional states based on body language data using non invasive sensors'. Together they form a unique fingerprint.
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Keyphrases
Body Language
100%
Boredom
25%
Classroom Learning
25%
Continuous Observation
25%
Driven Approach
25%
Emotional State
100%
Engagement Levels
25%
Entertainment
25%
Human Body Motion
25%
Human Participants
25%
Language Data
100%
Language Patterns
25%
Machine Learning Techniques
25%
Non-invasive Sensors
100%
Participant Engagement
75%
Position Data
25%
State-based
100%
Computer Science
Case Study
100%
Data Mining
100%
Driven Approach
100%
Emotional State
100%
Human Participant
100%
Machine Learning Technique
100%
Pattern Languages
100%
Psychology
Case Study
100%
Gaming
100%