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Article

Attention Measurement of an Autism Spectrum Disorder User Using EEG Signals: A Case Study

by
José Jaime Esqueda-Elizondo
1,2,
Reyes Juárez-Ramírez
2,
Oscar Roberto López-Bonilla
1,
Enrique Efrén García-Guerrero
1,
Gilberto Manuel Galindo-Aldana
3,
Laura Jiménez-Beristáin
2,
Alejandra Serrano-Trujillo
2,
Esteban Tlelo-Cuautle
4 and
Everardo Inzunza-González
1,*
1
Facultad de Ingeniería, Arquitectura y Diseño, Universidad Autónoma de Baja California, Carretera Transpeninsular Ensenada-Tijuana No. 3917, Ensenada C.P. 22860, Baja California, Mexico
2
Facultad de Ciencias Químicas e Ingeniería, Universidad Autónoma de Baja California, Calzada Universidad No. 14418, Parque Industrial Internacional, Tijuana C.P. 22390, Baja California, Mexico
3
Facultad de Ciencias de la Ingeniería y Tecnología, Universidad Autónoma de Baja California, Carretera Estatal No. 3, Gutiérrez, Mexicali C.P. 21720, Baja California, Mexico
4
Departamento de Electrónica, Instituto Nacional de Astrofísica, Óptica y Electrónica, Luis Enrique Erro No. 1, Santa María Tonanzintla, Puebla C.P. 72840, San Andrés Cholula, Mexico
*
Author to whom correspondence should be addressed.
Math. Comput. Appl. 2022, 27(2), 21; https://doi.org/10.3390/mca27020021
Submission received: 30 December 2021 / Revised: 23 February 2022 / Accepted: 24 February 2022 / Published: 2 March 2022
(This article belongs to the Special Issue Numerical and Evolutionary Optimization 2021)
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Abstract

Autism Spectrum Disorder (ASD) is a neurodevelopmental life condition characterized by problems with social interaction, low verbal and non-verbal communication skills, and repetitive and restricted behavior. People with ASD usually have variable attention levels because they have hypersensitivity and large amounts of environmental information are a problem for them. Attention is a process that occurs at the cognitive level and allows us to orient ourselves towards relevant stimuli, ignoring those that are not, and act accordingly. This paper presents a methodology based on electroencephalographic (EEG) signals for attention measurement in a 13-year-old boy diagnosed with ASD. The EEG signals are acquired with an Epoc+ Brain–Computer Interface (BCI) via the Emotiv Pro platform while developing several learning activities and using Matlab 2019a for signal processing. For this article, we propose to use electrodes F3, F4, P7, and P8. Then, we calculate the band power spectrum density to detect the Theta Relative Power (TRP), Alpha Relative Power (ARP), Beta Relative Power (BRP), Theta–Beta Ratio (TBR), Theta–Alpha Ratio (TAR), and Theta/(Alpha+Beta), which are features related to attention detection and neurofeedback. We train and evaluate several machine learning (ML) models with these features. In this study, the multi-layer perceptron neural network model (MLP-NN) has the best performance, with an AUC of 0.9299, Cohen’s Kappa coefficient of 0.8597, Matthews correlation coefficient of 0.8602, and Hamming loss of 0.0701. These findings make it possible to develop better learning scenarios according to the person’s needs with ASD. Moreover, it makes it possible to obtain quantifiable information on their progress to reinforce the perception of the teacher or therapist.
Keywords: autism; attention; ASD; learning activities; EEG; BCI; features; artificial intelligence; machine learning autism; attention; ASD; learning activities; EEG; BCI; features; artificial intelligence; machine learning

Share and Cite

MDPI and ACS Style

Esqueda-Elizondo, J.J.; Juárez-Ramírez, R.; López-Bonilla, O.R.; García-Guerrero, E.E.; Galindo-Aldana, G.M.; Jiménez-Beristáin, L.; Serrano-Trujillo, A.; Tlelo-Cuautle, E.; Inzunza-González, E. Attention Measurement of an Autism Spectrum Disorder User Using EEG Signals: A Case Study. Math. Comput. Appl. 2022, 27, 21. https://doi.org/10.3390/mca27020021

AMA Style

Esqueda-Elizondo JJ, Juárez-Ramírez R, López-Bonilla OR, García-Guerrero EE, Galindo-Aldana GM, Jiménez-Beristáin L, Serrano-Trujillo A, Tlelo-Cuautle E, Inzunza-González E. Attention Measurement of an Autism Spectrum Disorder User Using EEG Signals: A Case Study. Mathematical and Computational Applications. 2022; 27(2):21. https://doi.org/10.3390/mca27020021

Chicago/Turabian Style

Esqueda-Elizondo, José Jaime, Reyes Juárez-Ramírez, Oscar Roberto López-Bonilla, Enrique Efrén García-Guerrero, Gilberto Manuel Galindo-Aldana, Laura Jiménez-Beristáin, Alejandra Serrano-Trujillo, Esteban Tlelo-Cuautle, and Everardo Inzunza-González. 2022. "Attention Measurement of an Autism Spectrum Disorder User Using EEG Signals: A Case Study" Mathematical and Computational Applications 27, no. 2: 21. https://doi.org/10.3390/mca27020021

APA Style

Esqueda-Elizondo, J. J., Juárez-Ramírez, R., López-Bonilla, O. R., García-Guerrero, E. E., Galindo-Aldana, G. M., Jiménez-Beristáin, L., Serrano-Trujillo, A., Tlelo-Cuautle, E., & Inzunza-González, E. (2022). Attention Measurement of an Autism Spectrum Disorder User Using EEG Signals: A Case Study. Mathematical and Computational Applications, 27(2), 21. https://doi.org/10.3390/mca27020021

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