Document Type

Conference Paper

Publication Date

2023

DOI

10.1117/12.2682724

Publication Title

Proc. SPIE 12675, Applications of Machine Learning 2023

Pages

126750P (6 pp.)

Conference Name

SPIE Optical Engineering + Applications, August 20-25, 2023, San Diego, California

Abstract

Alexithymia describes a psychological state where individuals struggle with feeling and expressing their emotions. Individuals with alexithymia may also have a more difficult time understanding the emotions of others and may express atypical attention to the eyes when recognizing emotions. This is known to affect individuals with Autism Spectrum Disorder (ASD) differently than neurotypical (NT) individuals. Using a public data set of eye-tracking data from seventy individuals with and without autism who have been assessed for alexithymia, we train multiple traditional machine learning models for alexithymia classification including support vector machines, logistic regression, decision trees, random forest, and multilayer perceptron. To correct for class imbalance, we evaluate four different oversampling strategies: no oversampling, random oversampling, SMOTE, and ADASYN. We consider three different groups of data: ASD, NT, and combined ASD+NT. We use a nested leave-one-out cross validation strategy to perform hyperparameter selection and evaluate model performance. We achieve F1 scores of 90.00% and 51.85% using decision trees for ASD and NT groups, respectively, and 72.41% using SVM for the combined ASD+NT group. Splitting the data into ASD and NT groups improves recall for both groups compared to the combined model.

Rights

Copyright 2023 Society of Photo‑Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited.

Original Publication Citation

Furkan Ilgin, Megan A. Witherow, and Khan M. Iftekharuddin "Comparison of machine learning methods for classification of alexithymia in individuals with and without autism from eye-tracking data", Proc. SPIE 12675, Applications of Machine Learning 2023, 126750P (October 4, 2023). https://doi.org/10.1117/12.2682724

ORCID

0000-0002-6578-4657 (Witherow), 0000-0001-8316-4163 (Iftekharuddin)

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