步态相关数字化诊断标志物对早期识别阿尔茨海默病的应用价值OA
The application values of gait-related digital diagnostic markers for the early detection of Alzheimer's disease
步态异常长期被视为阿尔茨海默病(AD)的排除性证据,但随着现代步态分析研究的深入,这一传统观念正被打破.借助可穿戴传感设备、计算机视觉以及人工智能算法的现代步态分析法所采集的步态相关参数,初步具备了早期、精准、动态识别异常步态的诸多优势.本文拟从 AD 状态下步态异常的发生机制,结合 AD 脑内病理演变规律,全面回顾步态分析在 AD 领域的研究进展,尤其是数字化的步态参数与AD 生物学诊断标志物(BDMs)之间的关联研究,旨在探讨步态相关数字化诊断标志物(DDMs)在早期识别AD中的应用价值.
Gait abnormalities have long been regarded as exclusion criteria for Alzheimer's disease(AD).However,with advances in modern gait-analysis research,this traditional view is being overturned.Modern gait analysis,which integrates wearable sensors,computer vision,and artificial-intelligence algorithms,now generates gait parameters that already support the early,accurate,and dynamic detection of abnormal gait patterns.This paper reviews the mechanisms underlying gait disturbances in AD,integrating them with the cerebral pathological evolution characteristic of the disorder.We provide a comprehensive overview of progress in gait-analysis research in AD,with particular emphasis on studies linking digitized gait parameters to biological diagnostic markers(BDMs),aiming to evaluate the application values of gait-related digital diagnostic markers(DDMs)for the early identification of AD.
火婉颖;刘巍;许若琳;徐武华
暨南大学附属广州红十字会医院,广东 广州,510220暨南大学附属广州红十字会医院,广东 广州,510220暨南大学附属广州红十字会医院,广东 广州,510220暨南大学附属广州红十字会医院,广东 广州,510220
医药卫生
阿尔茨海默病步态分析数字化诊断标志物早期识别
Alzheimer's diseaseGait analysisDigital diagnostic biomarkersEarly identification
《阿尔茨海默病及相关病》 2026 (2)
135-138,144,5
广州市卫健委特色技术项目(2023C-TS07)广州市科技局市校联合项目(2023A03J0532)广州市科技局市校联合项目(2023A03J0608)
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