Alcañiz Mariano L, Olmos-Raya Elena, Abad Luis
Instituto de Investigación e Innovación en Bioingeniería (i3), Universidad Politécnica de Valencia, España. E-mail:
Instituto de Investigación e Innovación en Bioingeniería (i3), Universidad Politécnica de Valencia, España.
Medicina (B Aires). 2019;79(Suppl 1):77-81.
To date, the diagnostic tools for autism spectrum disorder (ASD) have been mostly based on qualitative criteria from observational information in contexts with low ecological validity. We are witnessing a growing scientific activity that proposes the use of implicit measures for the evaluation and diagnosis of ASD. These measures are based on processes of a biological and unconscious nature, underlying the capacity of human cognition, and are obtained through the acquisition and treatment of brain, physiological and behavioral responses in order to obtain the behavioral structure of the ASD patient facing a stimulus. The complex relationship between physiological responses and the behavioral structure of the ASD patient requires the use of advanced techniques of signal processing based on cognitive computation. Artificial intelligence (AI) techniques, such as machine learning and neurocomputing applied to the analysis of psychophysiological signals, have demonstrated their robustness for the classification of complex cognitive constructs. Virtual reality (VR) is a tool that allows recreating real-life situations with high sensory fidelity, but at the same time individually controlling each of the situations and stimuli that influence human behavior. It also allows the measurement in real time of human reactions to such stimuli. This document analyzes the latest scientific and technological advances relevant to its applications in the diagnosis of ASD. We conclude that VR is a very valuable tool for ASD research, especially for the evaluation and diagnosis of complex skills and competencies.
迄今为止，自闭症谱系障碍（ASD）的诊断工具大多基于低生态效度背景下观察信息的定性标准。我们正在见证一场日益活跃的科学活动，该活动提议使用内隐测量方法来评估和诊断ASD。这些测量方法基于具有生物学和无意识性质的过程，这些过程是人类认知能力的基础，并且是通过获取和处理大脑、生理及行为反应来获得ASD患者面对刺激时的行为结构。ASD患者生理反应与行为结构之间的复杂关系需要使用基于认知计算的先进信号处理技术。人工智能（AI）技术，如应用于心理生理信号分析的机器学习和神经计算，已证明其在复杂认知结构分类方面的稳健性。虚拟现实（VR）是一种工具，它能够以高感官保真度重现现实生活场景，但同时又能单独控制影响人类行为的每种情况和刺激。它还允许实时测量人类对这些刺激的反应。本文分析了与VR在ASD诊断中的应用相关的最新科技进展。我们得出结论，VR是ASD研究中非常有价值的工具，尤其对于复杂技能和能力的评估与诊断。
