Tecnologías Emergentes en el Diagnóstico y Tratamiento del TDAH

Jerónimo Aparicio-Juárez; Omar Arturo  Domínguez-Ramírez; Eduardo Alejandro  Escotto-Córdova

doi:10.29057/icbi.v12i23.12081

Jerónimo Aparicio-Juárez Universidad Autónoma del Estado de Hidalgo https://orcid.org/0000-0001-8858-5733
Omar Arturo Domínguez-Ramírez Universidad Autónoma del Estado de Hidalgo https://orcid.org/0000-0002-9663-8089
Eduardo Alejandro Escotto-Córdova National Autonomous University of Mexico https://orcid.org/0000-0002-1104-8195

DOI: https://doi.org/10.29057/icbi.v12i23.12081

Keywords: ADHD, Biofeedback, Artificial Intelligence, HRpI, BCI

Abstract

Attention Deficit Hyperactivity Disorder (ADHD) poses a significant concern in both the United States and Mexico, impacting academic performance and the quality of life for those affected. Limitations in traditional diagnostic and treatment methods, particularly in early detection and intervention, prompt the exploration of new procedures and technological proposals. This article reviews advancements in the diagnosis and treatment of ADHD, highlighting innovative platforms and methodologies. The research considers pupillometry as a diagnostic tool and delves into neurofeedback and biofeedback as promising treatment protocols. The use of Human-Robot Interaction Systems (HRpI) and Brain-Computer Interfaces (BCI) is discussed as emerging avenues to enhance the quality of life for patients. Emphasis is placed on the importance of utilizing robust metrics, signal analysis, and data; thus, incorporating assessments such as the D2 Attention Test, the Go/No-Go Test, Continuous Performance Tasks (CPT), and the Test of Variables of Attention (TOVA). Finally, the application of Artificial Intelligence (AI) algorithms as diagnostic support tools is addressed. These progressive developments represent a promising future for ADHD management and underscore the need for interdisciplinary collaboration among psychology, neuroscience, engineering, and medicine.

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