计算机视觉揭示了帕金森病左旋多巴反应性运动改善的三个基本维度

IF 6.7 1区医学 Q1 NEUROSCIENCES

NPJ Parkinson's Disease Pub Date : 2025-05-28 DOI:10.1038/s41531-025-00999-w

Florian Lange, Diego L. Guarin, Esther Ademola, Dalia Mahdy, Gabriela Acevedo, Thorsten Odorfer, Joshua K. Wong, Jens Volkmann, Robert Peach, Martin Reich

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引用次数: 0

摘要

我们开发了VisionMD，一个人工智能计算机视觉平台，分析了13年来1200多个帕金森患者手部运动的临床视频。这种大规模的无标记分析确定了左旋多巴可靠地改善了三个运动域（速度、一致性、时间/尺度）。与传统量表相比，我们的方法提供了客观、定量的运动评估，减少了主观性，提高了再现性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

Computer vision uncovers three fundamental dimensions of levodopa-responsive motor improvement in Parkinson’s disease

查看原文本刊更多论文

Computer vision uncovers three fundamental dimensions of levodopa-responsive motor improvement in Parkinson’s disease

We developed VisionMD, an AI computer vision platform, analyzing over 1200 clinical videos of Parkinson’s patients’ hand movements across 13 years. This large-scale, markerless analysis identified three kinematic domains (speed, consistency, timing/scale) reliably improved by levodopa. Our method offers objective, quantitative motor assessment, reducing subjectivity and enhancing reproducibility compared to traditional scales.

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来源期刊

NPJ Parkinson's Disease Medicine-Neurology (clinical)

CiteScore

9.80

自引率

5.70%

发文量

156

审稿时长

11 weeks

期刊介绍： npj Parkinson's Disease is a comprehensive open access journal that covers a wide range of research areas related to Parkinson's disease. It publishes original studies in basic science, translational research, and clinical investigations. The journal is dedicated to advancing our understanding of Parkinson's disease by exploring various aspects such as anatomy, etiology, genetics, cellular and molecular physiology, neurophysiology, epidemiology, and therapeutic development. By providing free and immediate access to the scientific and Parkinson's disease community, npj Parkinson's Disease promotes collaboration and knowledge sharing among researchers and healthcare professionals.