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

Kazuya Tsukamoto, Ryota Matsui, Yuta Sugiura, Koji Fujita

Research output: Contribution to journalArticlepeer-review

Abstract

: 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).

Original languageEnglish
Pages (from-to)634-636
Number of pages3
JournalJournal of Hand Surgery: European Volume
Volume49
Issue number5
DOIs
Publication statusPublished - 2024 May

Keywords

  • 10-s grip-and-release test
  • carpal tunnel syndrome
  • machine learning
  • screening
  • video analysis

ASJC Scopus subject areas

  • Surgery

Fingerprint

Dive into the research topics of 'Diagnosis of carpal tunnel syndrome using a 10-s grip-and-release test with video and machine learning analysis'. Together they form a unique fingerprint.

Cite this