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    dc.contributor.authorRamos-Galarza, Carlos-
    dc.contributor.authorAcosta-Rodas, Mónica-
    dc.contributor.authorAcosta-Vargas, Patricia-
    dc.contributor.authorSalvador-Ullauri, Luis-
    dc.date.accessioned2022-06-20T19:28:50Z-
    dc.date.available2022-06-20T19:28:50Z-
    dc.date.issued2021-
    dc.identifier.urihttps://link.springer.com/chapter/10.1007/978-3-030-51041-1_11-
    dc.identifier.urihttp://repositorio.uti.edu.ec//handle/123456789/3316-
    dc.description.abstractThe development of a neuropsychological assessment procedure through a technological platform for children with ADHD. This platform is based on Python programming language, where stimuli have been inserted and, to which, children evaluated must respond freely (letters P), and others to which must inhibit his/her responses (letters R), using an adapted button box (greater attraction for children with ADHD). Variables of interest to the clinician are (a) number of responses to impulse control stimuli, (b) total time of execution of the task, (c) time in milliseconds from the moment when the stimulus is presented until getting a response from the child, and (d) total answers made. This study was applied in children with ADHD versus children without the disorder, finding that children with ADHD presented a mean error of M = 5.05 while children without ADHD M = 3.42.es
    dc.language.isoenges
    dc.publisherAdvances in Intelligent Systems and Computing. Volume 1201 AISC, Pages 76 - 822. AHFE Virtual Conferences on Neuroergonomics and Cognitive Engineering, and Industrial Cognitive Ergonomics and Engineering Psychology, 2020. San Diego. 16 July 2020 through 20 July 2020es
    dc.rightsopenAccesses
    dc.rights.urihttps://creativecommons.org/licenses/by/4.0/es
    dc.titleTechnological Innovation to Assess Cognitive Functions in Attention Deficit Hyperactivity Disorderes
    dc.typearticlees
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