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Affective Assessment by Digital Processing of the Pupil Diameter
Jan.-March 2013 (vol. 4 no. 1)
pp. 2-14
Peng Ren, Florida International University, Miami
Armando Barreto, Florida International University, Miami
Ying Gao, University of Wisconsin- Platteville, Platteville
Malek Adjouadi, Florida International University, Miami
Previous research found that the pupil diameter (PD) can be an indication of affective state, but this approach to the detection of the affective state of a computer user has not been investigated fully. We propose a new affective sensing approach to evaluate the computer user's affective states as they transition from "relaxation” to "stress,” through processing the PD signal. Wavelet denoising and Kalman filtering were used to preprocess the PD signal. Then, three features were extracted from it and five classification algorithms were used to evaluate the overall performance of the identification of "stress” states in the computer users, achieving an average accuracy of 83.16 percent, with the highest accuracy of 84.21 percent reached with a Multilayer Perceptron and a Naive Bayes classifier. The Galvanic Skin Response (GSR) signal was also analyzed to study the comparative efficiency of affective sensing through the PD signal. We compared the discriminating power of the three features derived from the preprocessed PD signal to three features derived from the preprocessed GSR signal in terms of their Receiver Operating Characteristic curves. The results confirm that the PD signal should be considered a powerful physiological factor to involve in future automated affective classification systems for human-computer interaction.
Index Terms:
Human computer interaction,Multiresolution analysis,Low pass filters,Noise reduction,Kalman filters,Physiology,Receivers,Walsh transform,Human computer interaction,Multiresolution analysis,Low pass filters,Noise reduction,Kalman filters,Physiology,Receivers,receiver operating characteristic (ROC) curves,Affective computing,human-computer interaction (HCI),pupil diameter (PD),wavelet denoising,Kalman filter
Citation:
Peng Ren, Armando Barreto, Ying Gao, Malek Adjouadi, "Affective Assessment by Digital Processing of the Pupil Diameter," IEEE Transactions on Affective Computing, vol. 4, no. 1, pp. 2-14, Jan.-March 2013, doi:10.1109/T-AFFC.2012.25
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