Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Anatomical analysis of the posterior elbow joint capsule and small muscle bundle deep to the triceps brachii: a combined cadaveric and in vivo study.

BMC musculoskeletal disorders·2026
Same author

Grip Strength Estimation Using Input Data From a Commodity Smartphone: Model Development and Validation Study.

JMIR human factors·2026
Same author

Grooved Surface of the Obturator Internus Muscle With Two Distinct Adjacent Parts.

Clinical anatomy (New York, N.Y.)·2026
Same author

The Trapezius Aponeurosis Insertion on the Acromion: An Anatomical Study with a Possible Implication for Dynamic Stabilization of the Acromioclavicular Joint.

The Journal of bone and joint surgery. American volume·2025
Same author

Anatomy of Adipose Compartments and Fascial Structures in the Posterolateral Region of the Kidney With Special Focus on the Thin Adipose Compartment.

International journal of urology : official journal of the Japanese Urological Association·2025
Same author

Thumb rotation patterns during pinch in patients with trapeziometacarpal osteoarthritis.

The Journal of hand surgery, European volume·2025

Related Experiment Video

Updated: Nov 13, 2025

Screening of Axonal Degeneration in Carpal Tunnel Syndrome Using Ultrasonography and Nerve Conduction Studies
06:40

Screening of Axonal Degeneration in Carpal Tunnel Syndrome Using Ultrasonography and Nerve Conduction Studies

Published on: January 11, 2019

11.9K

A Screening Method Using Anomaly Detection on a Smartphone for Patients With Carpal Tunnel Syndrome: Diagnostic

Takafumi Koyama1, Shusuke Sato2, Madoka Toriumi2

  • 1Department of Orthopedic and Spinal Surgery, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan.

JMIR Mhealth and Uhealth
|March 14, 2021
PubMed
Summary

A new smartphone app effectively screens for carpal tunnel syndrome (CTS) by analyzing thumb movements. This accessible tool offers high sensitivity and specificity for early diagnosis.

Keywords:
algorithmanomaly detectionappcarpal tunnel syndromedata collectiondiagnosticmachine learningscreeningsmartphonethumb

More Related Videos

Metacarpal Small Incision for Carpal Tunnel Syndrome
04:08

Metacarpal Small Incision for Carpal Tunnel Syndrome

Published on: April 5, 2024

885
Video Movement Analysis Using Smartphones ViMAS: A Pilot Study
07:51

Video Movement Analysis Using Smartphones ViMAS: A Pilot Study

Published on: March 14, 2017

17.0K

Related Experiment Videos

Last Updated: Nov 13, 2025

Screening of Axonal Degeneration in Carpal Tunnel Syndrome Using Ultrasonography and Nerve Conduction Studies
06:40

Screening of Axonal Degeneration in Carpal Tunnel Syndrome Using Ultrasonography and Nerve Conduction Studies

Published on: January 11, 2019

11.9K
Metacarpal Small Incision for Carpal Tunnel Syndrome
04:08

Metacarpal Small Incision for Carpal Tunnel Syndrome

Published on: April 5, 2024

885
Video Movement Analysis Using Smartphones ViMAS: A Pilot Study
07:51

Video Movement Analysis Using Smartphones ViMAS: A Pilot Study

Published on: March 14, 2017

17.0K

Area of Science:

  • Medical diagnostics
  • Biomedical engineering
  • Machine learning applications

Background:

  • Carpal tunnel syndrome (CTS) is caused by median nerve compression, leading to finger numbness and muscle atrophy.
  • Current diagnostic methods like physical exams and nerve conduction studies have limitations.
  • Previous app-based screening research faced challenges with tablet usage and data collection.

Purpose of the Study:

  • To develop a more accessible CTS screening tool using a smartphone app and anomaly detection.
  • To simplify data collection for machine learning models in CTS screening.
  • To evaluate the system's effectiveness as a CTS screening tool.

Main Methods:

  • Developed a smartphone app for CTS screening utilizing anomaly detection.
  • Recruited participants with and without CTS, recording thumb position and movement time.
  • Generated classification models using anomaly detection and autoencoders, calculating sensitivity, specificity, and AUC.

Main Results:

  • The app achieved 94% sensitivity, 67% specificity, and an AUC of 0.86 in classifying CTS.
  • A specific model analyzing thumb opposition direction reached 99% AUC, 92% sensitivity, and 100% specificity.
  • The system effectively identified difficulties in thumb opposition characteristic of CTS.

Conclusions:

  • The developed smartphone app can reveal thumb opposition difficulties in patients with CTS.
  • The app serves as a highly sensitive and specific screening tool for CTS.
  • Smartphone accessibility and anomaly detection enhance the usability and potential of this CTS screening method.