阿尔茨海默病相关的数字生物标志物应用与研究进展

Application and Research Progress of Digital Biomarkers Related to Alzheimer’s Disease

摘要: 阿尔茨海默病(Alzheimer’s Disease, AD)作为一种进行性神经退行性疾病，其早期诊断和疾病监测面临巨大挑战。传统诊断方法依赖临床症状和脑脊液、影像学等侵入性或高成本手段，难以实现大规模早期筛查。近年来，数字生物标志物(Digital Biomarkers, DBs)作为新兴的非侵入性评估工具，借助可穿戴设备、智能手机和人工智能技术，实现了对认知行为、语言能力、运动功能及生理信号等多维数据的连续采集与分析，为AD的早期识别与病程追踪提供了新途径。本文系统综述了DBs在AD筛查、诊断及进展评估中的研究进展，详细阐述了其类型、采集方法及其与经典生物标志物的关联性，并分析了当前面临的隐私安全、数据标准化及临床验证等挑战，展望了未来发展方向，旨在为AD的数字化精准诊疗提供理论依据。

Abstract: Alzheimer’s Disease (AD) is a progressive neurodegenerative disease. Its early diagnosis and disease‑monitoring face great challenges. Traditional diagnostic methods rely on clinical symptoms, cerebrospinal fluid tests, imaging examinations and other invasive or high‑cost techniques, which cannot achieve large‑scale early‑stage screening. In recent years, as an emerging non‑invasive evaluation tool, Digital Biomarkers (DBs) adopt wearable devices, smartphones and artificial‑intelligence technologies to continuously collect and analyze multidimensional data including cognitive behaviors, language competence, motor functions and physiological signals, providing a new approach for early identification and disease‑progression tracking of AD. This paper systematically reviews the research progress of DBs in AD screening, diagnosis and progression assessment. It elaborates on the types and acquisition methods of DBs, as well as their correlations with classic biomarkers. This article also analyzes current challenges including privacy security, data standardization and clinical validation, and prospects future development directions, aiming to supply theoretical foundations for digital‑based precise diagnosis and treatment of AD.