Alcañiz Mariano, Chicchi Giglioli Irene A, Sirera Marian, Minissi Eleonora, 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). 2020;80 Suppl 2:31-36.
It has been observed that the stratification of Autism Spectrum Disorders (ASD) generated by the current scales is not effective for the personalization of early treatments. The clinical evaluation of ASD requires its consideration as a continuum of deficits, and there is a need to identify biologically significant parameters (biomarkers) that have the power to automatically characterize each individual at different stages of neurological development. The emerging field of computational psychiatry (CP) attempts to meet the needs of precision diagnosis by developing powerful computational and mathematical techniques. A growing scientific activity proposes the use of implicit measures based on biosignals for the classification of ASD. Virtual reality (VR) technologies have demonstrated potential for ASD interventions, but most of the work has used virtual reality for the learning / objective of interventions. Very few studies have used biological signals for recording and detailed analysis of behavioral responses that can be used to monitor or produce changes over time. In this paper the concept of behavioral biomarkers based on VR or VRBB is introduced. VRBB will allow the classification of ASD using a paradigm of computational psychiatry based on implicit brain processes measured through psychophysiological signals and the behavior of subjects exposed to complex replicas of social conditions using virtual reality interfaces.
据观察，当前量表所产生的自闭症谱系障碍（ASD）分层对于早期治疗的个性化并不有效。ASD的临床评估需要将其视为一系列连续的缺陷，并且有必要识别出具有在神经发育的不同阶段自动表征每个个体能力的生物学上有意义的参数（生物标志物）。新兴的计算精神病学（CP）领域试图通过开发强大的计算和数学技术来满足精准诊断的需求。越来越多的科学活动提议使用基于生物信号的隐式测量方法来对ASD进行分类。虚拟现实（VR）技术已展现出对ASD干预的潜力，但大多数工作都将虚拟现实用于干预的学习/目标。极少有研究使用生物信号来记录和详细分析行为反应，而这些行为反应可用于监测或随时间产生变化。本文引入了基于虚拟现实的行为生物标志物（VRBB）的概念。VRBB将允许使用一种基于计算精神病学的范式对ASD进行分类，该范式基于通过心理生理信号测量的隐式大脑过程以及使用虚拟现实界面暴露于复杂社会情境复制品下的受试者的行为。
