Abstract
There are several disorders that affect the level of attention of people both in their childhood and adulthood. One of the most recognized disorders is attention deficit hyperactivity disorder (ADHD) and is usually diagnosed for the first time in childhood, and the symptoms persist in adolescence and adulthood. Some ways of knowing if a person presents ADHD are: through questionnaires, intellectual tests, types of behavior, medical diagnoses, among others. These tests require a long period of time where an observation and analysis process is performed in order to obtain a reliable diagnosis. This paper presents the development of an experiment for the identification of ADHD, using an electronic system where brain waves are involved as a physiological variable. The comparative analysis is described on a sample of children with diagnosed ADHD, and a sample of children without ADHD. This analysis is performed using statistical tools that graphically demonstrate some differences in the behavior of the level of attention of a child with ADHD with respect to the behavior of the level of attention of a child without ADHD. Finally, the obtained characteristics from a child with ADHD are described and a strategy is proposed for identify reliable patterns based on the user’s level of attention.
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References
Pascual, M.F., Begoña, Z., Buldian, K.M.: Adaptive cognitive rehabilitation interventions based on serious games for children with ADHD using biofeedback techniques: assessment and evaluation. In: COMPUTE 2010 Proceedings of the Third Annual ACM Bangalore Conference, Article 29, Bilbao, España, pp. 1–4 (2010). http://dx.doi.org/10.4108/icst.pervasivehealth.2014.255249
Asiry, O., Shen, H., Calder, P.: Extending attention span of ADHD children through an eye tracker directed adaptive user interface. In: ASWEC 2015 Volume II: Proceedings of the ASWEC 2015 24th Australasian Software Engineering Conference, Australia, vol. 1, pp. 149–152 (2015). http://dx.doi.org/10.1145/2811681.2824997
Weisberg, O., et al.: TangiPlan: designing an assistive technology to enhance executive functioning among children with ADHD. In: IDC 2014 Proceedings of the 2014 Conference on Interaction Design and Children, New York, USA, vol. 1, pp. 293–296 (2014). http://dx.doi.org/10.1145/2593968.2610475
Sonne, T., Jensen, M.M.: Evaluating the ChillFish biofeedback game with children with ADHD. In: IDC 2016 Proceedings of the 15th International Conference on Interaction Design and Children, New York, USA, vol. 1, pp. 529–534 (2016)
Domínguez, C.: Las Ondas Binaurales y sus Efectos. In: Tesis de Investigación Experimental, Ciudad Cooperativa Cruz Azul, vol. 1, pp. 1–22 (2015)
Aballay, L., Aciar, S., Reategui, E.: Propuesta de un Método para Detección de Emociones en E-Learning. In: ASAI 2015, 16º Simposio Argentino de Inteligencia Artificial, Porto Alegre, Brasil, pp. 121–128 (2015). http://dx.doi.org/10.1145/2930674.2935981, ISSN 2451–7585
Sonne, T., Jensen, M.M.: ChillFish: a respiration game for children with ADHD. In: TEI 2016 Proceedings of the TEI ‘16: Tenth International Conference on Tangible, Embedded, and Embodied Interaction, New York, USA, vol. 1, pp. 271–278 (2016). http://dx.doi.org/10.1145/2839462.2839480
Marín, E.J.: Detección de emociones del usuario. In: Tesis Pontificia Universidad Católica de Valparaíso, Chile, vol. 1, pp. 1–67 (2014)
Hernández, A., Vásquez, R., Olivares, B.A., Cortes, G., López, I.: Sistema de detección de emociones para la recomendación de recursos educativos. In: Programación Matemática y Software, Orizaba, México, vol. 8, no. 1, pp. 58–66 (2016). ISSN 2007-3283
Saneiro, M.M.: Apoyo psico-educativo y afectivo en entornos virtuales de aprendizaje. Int. J. Dev. Educ. Psychol. 1(2), 233–241 (2015). http://dx.doi.org/10.17060/ijodaep.2015.n2.v1.338. De INFAD Base de datos, Badajoz, España
Campazzo, E., Martinez, M., Guzmán, A.E., Agüero, A.: Entornos Virtuales de Aprendizaje integrado a tecnología móvil y detección de emociones. In: Secretaría de Ciencia y Tecnología/Departamento de Ciencias Exactas Físicas y Naturales/Universidad Nacional de La Rioja, La Rioja, vol. 1, pp. 1–5 (2014)
Rojas, S., Garzón, J., Martínez, D., Escobar, M., Robayo, C.: Lector de ondas cerebrales para implementar un sistema alternativo y aumentativo de comunicación. In: 10th Latin American and Caribbean Conference for Engineering and Technology, vol. 10, pp. 1–9 (2012)
Campazzo, E., Martínez, M., Guzmán, A., Agüero, A.: Desarrollo de interface de detección de emociones para su utilización en redes sociales y entornos virtuales de aprendizaje. In: XV Workshop de Investigadores en Ciencias de la Computación, Paraná, vol. 1, pp. 1–5 (2013)
García, A.E.: Análisis de ondas cerebrales para determinar emociones a partir de estímulos visuales. In: Universidad Veracruzana Facultad de Estadística e Informática, Xalapa, Veracruz, México, vol. 1, pp. 1–137 (2015)
Torres, F., Sánchez, C., Palacio, B.: Adquisición y análisis de señales cerebrales utilizando el dispositivo MindWave. In: MASKANA, I+D+ingeniería 2014, vol. 1, pp. 1–11 (2014)
Centers for Disease Control and Prevention (CDC). Attention-Deficit/Hyperactivity Disorder (ADHD). https://www.cdc.gov/ncbddd/adhd/facts.html
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Special recognition to teacher “Claudia Gonzalez Calleros” for her valuable collaboration in taking samples with students with ADHD.
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Garcia, A., Gonzalez, J.M., Palomino, A. (2019). Identification of Patterns in Children with ADHD Based on Brain Waves. In: Ruiz, P., Agredo-Delgado, V. (eds) Human-Computer Interaction. HCI-COLLAB 2019. Communications in Computer and Information Science, vol 1114. Springer, Cham. https://doi.org/10.1007/978-3-030-37386-3_19
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DOI: https://doi.org/10.1007/978-3-030-37386-3_19
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