孤独症谱系障碍外显性数字生物标志物的研究进展

Research progress on explicit digital biomarkers of autism spectrum disorder

摘要

孤独症谱系障碍(ASD)的诊断主要依赖临床观察和量表评估,存在主观性和局限性,因此亟需客观、可量化的生物标志物辅助早期识别。外显性数字生物标志物作为ASD研究的新方向,主要包括运动模式、眼球运动和表情特征,通过智能终端设备采集数据,结合机器学习算法分析,实现对ASD的高精度识别。本文综述了外显性数字生物标志物的研究进展,为ASD的早期筛查、诊断和精准干预提供了新思路,有助于推动临床筛查诊断工具的优化和个性化诊疗的发展。

Abstract

The diagnosis of autism spectrum disorder (ASD) primarily relies on clinical observation and scale assessments, which are subjective and have limitations.Therefore, there is an urgent need for objective and quantifiable biomarkers to assist in early identification.As a new direction in ASD research, explicit digital biomarkers mainly include movement patterns, eye movements, and facial expression characteristics.By collecting data through smart terminal devices and analyzing it with machine learning algorithms, high-precision identification of ASD can be achieved.This article reviews the research progress of explicit digital biomarkers, providing new insights for early screening, diagnosis, and precise intervention of ASD, which will help optimize clinical screening and diagnostic tools and promote the development of personalized treatment.

关键词

孤独症谱系障碍 / 外显性数字生物标志物 / 运动模式 / 眼球运动 / 表情

Key words

autism spectrum disorder / explicit digital biomarkers / movement patterns / eye movement / facial expression

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基金资助

国家重点研发计划(2023YFC3604805)