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

被引：3

作者：

Tsukamoto, Kazuya ^{[1
]}

Matsui, Ryota ^{[2
]}

Sugiura, Yuta ^{[2
]}

Fujita, Koji ^{[3
,4
,5
]}

机构：

[1] Tokyo Med & Dent Univ, Grad Sch Med & Dent Sci, Dept Orthoped & Spinal Surg, Tokyo, Japan

[2] Keio Univ, Sch Sci Open & Environm Syst, Grad Sch Sci & Technol, Yokohama, Japan

[3] Tokyo Med & Dent Univ, Grad Sch Med & Dent Sci, Dept Funct Joint Anat, Tokyo, Japan

[4] Tokyo Med & Dent Univ, Inst Res Innovat, Open Innovat Ctr, Div Med Design Innovat, Tokyo, Japan

[5] 1-5-45 Yushima,Bunkyo-Ku, Tokyo 1138519, Japan

来源：

JOURNAL OF HAND SURGERY-EUROPEAN VOLUME | 2024年 / 49卷 / 05期

关键词：

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

D O I：

10.1177/17531934231214661

中图分类号：

R826.8 [整形外科学]; R782.2 [口腔颌面部整形外科学]; R726.2 [小儿整形外科学]; R62 [整形外科学（修复外科学）];

学科分类号：

摘要：

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).Level of evidence III

引用

页码：634 / 636

页数：3

共 19 条

[1] Screening for degenerative cervical myelopathy with the 10-second grip-and-release test using a smartphone and machine learning: A pilot study
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[3] Automatic Electrodiagnosis of Carpal Tunnel Syndrome Using Machine Learning
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DIAGNOSTICS, 2022, 12 (09)
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