Diagnosis of carpal tunnel syndrome using a 10-s grip-and-release test with video and machine learning analysis.

Journal: The Journal of hand surgery, European volume
PMID: 37994011

Abstract

UNLABELLED: We developed a finger motion-based diagnostic system for carpal tunnel syndrome by analysing 10 second grip-and-release test videos. Using machine learning, it estimated presence of carpal tunnel syndrome (89% sensitivity and 83% specificity) and correlated with severity on nerve conduction studies (coefficient 0.68).

Authors

  • Kazuya Tsukamoto
    Department of Orthopedic and Spinal Surgery, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan.
  • Ryota Matsui
    School of Science for Open and Environmental Systems, Graduate School of Science and Technology, Keio University, Yokohama, Japan.
  • Yuta Sugiura
    Faculty of Science and Technology, Keio University, Yokohama 223-8522, Japan.
  • Koji Fujita
    Department of Molecular Pathology, Tokyo Medical University, Shinjuku-ku, Tokyo, 160-8402, Japan.

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