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Reading Emotion From Mouse Cursor Motions: Affective Computing Approach.

Takashi Yamauchi1, Kunchen Xiao1

  • 1Department of Psychological and Brain Science, Texas A&M University.

Cognitive Science
|November 14, 2017
PubMed
Summary
This summary is machine-generated.

Computer cursor movements can reveal user emotions. This study shows cursor motion analysis effectively infers positive affect and attentiveness, offering a practical approach to emotion recognition.

Keywords:
Affective computingChoice reaching trajectoryEmotion and motor controlMouse cursor motion analysis

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Area of Science:

  • Affective computing
  • Human-computer interaction
  • Emotion recognition technology

Background:

  • Current emotion recognition systems (facial, vocal, physiological) are often impractical for real-world applications.
  • Affective computing aims to develop systems that can understand and respond to human emotions.
  • Investigating novel, non-intrusive methods for emotion detection is crucial.

Purpose of the Study:

  • To integrate mouse cursor motion analysis into affective computing.
  • To investigate if computer cursor movements can provide insights into a user's emotional state.
  • To establish a link between cursor motion patterns and user emotions.

Main Methods:

  • Extraction of 16-26 trajectory features from mouse cursor movements during a choice-reaching task.
  • Induction of positive and negative emotions in participants using music, film clips, and emotional images.
  • Self-reported emotion ratings via questionnaires.
  • 10-fold cross-validation analysis to test predictive accuracy.

Main Results:

  • Statistical models trained on 'known' participants predicted 10%-20% of the variance in positive affect and attentiveness ratings for 'unknown' participants.
  • Specific cursor movement patterns, including area under the curve and direction change, were identified as significant predictors.
  • Demonstrated a quantifiable relationship between mouse cursor kinematics and user emotional states.

Conclusions:

  • Mouse cursor motion analysis is a viable and practical method for inferring user emotions within affective computing.
  • Cursor movement patterns offer valuable, non-intrusive data for emotion recognition systems.
  • This approach enhances the potential for developing more sensitive and responsive human-computer interactions.