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Published on: November 26, 2019
Affective assessment of computer users based on processing the pupil diameter signal
Peng Ren1, Armando Barreto, Ying Gao
1Biomedical Engineering Department, Florida International University, Miami, FL 33174, USA
Summary
This study shows pupil diameter variations can detect user stress or relaxation with 86.78% accuracy. Pupil diameter is a more promising indicator than eye blink frequency for affective computing.
Area of Science:
- Biomedical Engineering
- Human-Computer Interaction
- Affective Computing
Background:
- Detecting user affective states is a key challenge in human-computer interaction.
- Biomedical engineering offers tools for monitoring physiological responses.
- Sympathetic activation influences physiological signals like pupil diameter.
Purpose of the Study:
- To develop a method for recognizing user affective states (stress vs. relaxation).
- To investigate the utility of pupil diameter variations for affective state detection.
- To compare pupil diameter with eye blink frequency for affective assessment.
Main Methods:
- Applied wavelet denoising and Kalman filtering to raw pupil diameter (PD) signals.
- Extracted three features from the preprocessed PD signal.
- Utilized a random tree classifier for affective state classification.
Main Results:
- Achieved an accuracy of 86.78% in classifying affective states using PD.
- Eye Blink Frequency (EBF) was also used but yielded less promising results.
- Pupil diameter variations proved to be a more effective physiological signal for affective assessment.
Conclusions:
- Pupil diameter analysis offers a viable method for detecting user stress and relaxation.
- This approach has significant potential for enhancing human-computer interaction systems.
- Further research into PD-based affective computing is warranted.
