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Efficient autism spectrum disorder prediction with eye movement: A machine learning framework

Publication ,  Conference
Liu, W; Yi, L; Yu, Z; Zou, X; Raj, B; Li, M
Published in: 2015 International Conference on Affective Computing and Intelligent Interaction, ACII 2015
December 2, 2015

We propose an autism spectrum disorder (ASD) prediction system based on machine learning techniques. Our work features the novel development and application of machine learning methods over traditional ASD evaluation protocols. Specifically, we are interested in discovering the latent patterns that possibly indicate the symptom of ASD underneath the observations of eye movement. A group of subjects (either ASD or non-ASD) are shown with a set of aligned human face images, with eye gaze locations on each image recorded sequentially. An image-level feature is then extracted from the recorded eye gaze locations on each face image. Such feature extraction process is expected to capture discriminative eye movement patterns related to ASD. In this work, we propose a variety of feature extraction methods, seeking to evaluate their prediction performance comprehensively. We further propose an ASD prediction framework in which the prediction model is learned on the labeled features. At testing stage, a test subject is also asked to view the face images with eye gaze locations recorded. The learned model predicts the image-level labels and a threshold is set to determine whether the test subject potentially has ASD or not. Despite the inherent difficulty of ASD prediction, experimental results indicates statistical significance of the predicted results, showing promising perspective of this framework.

Duke Scholars

Published In

2015 International Conference on Affective Computing and Intelligent Interaction, ACII 2015

DOI

Publication Date

December 2, 2015

Start / End Page

649 / 655
 

Citation

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Liu, W., Yi, L., Yu, Z., Zou, X., Raj, B., & Li, M. (2015). Efficient autism spectrum disorder prediction with eye movement: A machine learning framework. In 2015 International Conference on Affective Computing and Intelligent Interaction, ACII 2015 (pp. 649–655). https://doi.org/10.1109/ACII.2015.7344638
Liu, W., L. Yi, Z. Yu, X. Zou, B. Raj, and M. Li. “Efficient autism spectrum disorder prediction with eye movement: A machine learning framework.” In 2015 International Conference on Affective Computing and Intelligent Interaction, ACII 2015, 649–55, 2015. https://doi.org/10.1109/ACII.2015.7344638.
Liu W, Yi L, Yu Z, Zou X, Raj B, Li M. Efficient autism spectrum disorder prediction with eye movement: A machine learning framework. In: 2015 International Conference on Affective Computing and Intelligent Interaction, ACII 2015. 2015. p. 649–55.
Liu, W., et al. “Efficient autism spectrum disorder prediction with eye movement: A machine learning framework.” 2015 International Conference on Affective Computing and Intelligent Interaction, ACII 2015, 2015, pp. 649–55. Scopus, doi:10.1109/ACII.2015.7344638.
Liu W, Yi L, Yu Z, Zou X, Raj B, Li M. Efficient autism spectrum disorder prediction with eye movement: A machine learning framework. 2015 International Conference on Affective Computing and Intelligent Interaction, ACII 2015. 2015. p. 649–655.

Published In

2015 International Conference on Affective Computing and Intelligent Interaction, ACII 2015

DOI

Publication Date

December 2, 2015

Start / End Page

649 / 655