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<p>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.</p><p></p>

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

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年5月28日

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

摘要

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.