Video-Based Analyses of Parkinson's Disease Severity: A Brief Review

被引:44
|
作者
Sibley, Krista G. [1 ]
Girges, Christine [1 ]
Hoque, Ehsan [2 ]
Foltynie, Thomas [1 ]
机构
[1] UCL, Inst Neurol, Dept Clin & Movement Neurosci, London, England
[2] Univ Rochester, Dept Comp Sci, Rochester, NY 14627 USA
基金
美国国家卫生研究院;
关键词
Parkinson's disease; video; artificial intelligence; machine learning; TELEMEDICINE; TECHNOLOGY; ACCESS; TRIAL; PILOT; CARE; RISK;
D O I
10.3233/JPD-202402
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Remote and objective assessment of the motor symptoms of Parkinson's disease is an area of great interest particularly since the COVID-19 crisis emerged. In this paper, we focus on a) the challenges of assessing motor severity via videos and b) the use of emerging video-based Artificial Intelligence (AI)/Machine Learning techniques to quantitate human movement and its potential utility in assessing motor severity in patients with Parkinson's disease. While we conclude that video-based assessment may be an accessible and useful way of monitoring motor severity of Parkinson's disease, the potential of video-based AI to diagnose and quantify disease severity in the clinical context is dependent on research with large, diverse samples, and further validation using carefully considered performance standards.
引用
收藏
页码:S83 / S93
页数:11
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