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 Experiment Video

Updated: Aug 9, 2025

Measurement of Spatial Stability in Precision Grip
09:36

Measurement of Spatial Stability in Precision Grip

Published on: June 4, 2020

3.3K

Comparing Statistics and Machine Learning to Detect Insincere Grip Force Testing Using Manugraphy.

Marion Mühldorfer-Fodor1, Eren Cenik2, Peter Hahn3

  • 1Hand Surgery, RHÖN-KLINIKUM Campus Bad Neustadt, Bad Neustadt an der Saale, DEU.

Cureus
|February 23, 2023
PubMed
Summary
This summary is machine-generated.

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

Healthcare professionals show high AI enthusiasm but limited knowledge: A cross-sectional study.

PLOS digital health·2026
Same author

[Prevalence of Pisotriquetral Subluxation and Osteoarthritis in Carpal Collapse - Pisotriquetral osteoarthritis with carpal collapse].

Handchirurgie, Mikrochirurgie, plastische Chirurgie : Organ der Deutschsprachigen Arbeitsgemeinschaft fur Handchirurgie : Organ der Deutschsprachigen Arbeitsgemeinschaft fur Mikrochirurgie der Peripheren Nerven und Gefasse : Organ der V...·2026
Same author

[Final sprint for the hybrid DRG radius fracture].

Handchirurgie, Mikrochirurgie, plastische Chirurgie : Organ der Deutschsprachigen Arbeitsgemeinschaft fur Handchirurgie : Organ der Deutschsprachigen Arbeitsgemeinschaft fur Mikrochirurgie der Peripheren Nerven und Gefasse : Organ der V...·2025
Same author

[Intraoperative Shock-Wave Application in Scaphoid Reconstruction with Non-Vascularised Bone Grafts: A Randomised Controlled Trial].

Handchirurgie, Mikrochirurgie, plastische Chirurgie : Organ der Deutschsprachigen Arbeitsgemeinschaft fur Handchirurgie : Organ der Deutschsprachigen Arbeitsgemeinschaft fur Mikrochirurgie der Peripheren Nerven und Gefasse : Organ der V...·2025
Same author

[Deep flexor tendon-rupture close to the insertion combined with simultaneous dislocation of the proximal tendon stump out of the flexor tendon sheath].

Handchirurgie, Mikrochirurgie, plastische Chirurgie : Organ der Deutschsprachigen Arbeitsgemeinschaft fur Handchirurgie : Organ der Deutschsprachigen Arbeitsgemeinschaft fur Mikrochirurgie der Peripheren Nerven und Gefasse : Organ der V...·2025
Same author

[Good News from HaMiPla].

Handchirurgie, Mikrochirurgie, plastische Chirurgie : Organ der Deutschsprachigen Arbeitsgemeinschaft fur Handchirurgie : Organ der Deutschsprachigen Arbeitsgemeinschaft fur Mikrochirurgie der Peripheren Nerven und Gefasse : Organ der V...·2025

Machine learning accurately detects insincere grip force testing. This novel approach analyzes hand load distribution, significantly improving sincerity detection compared to traditional methods.

Area of Science:

  • Biomechanics
  • Machine Learning
  • Medical Diagnostics

Background:

  • Current grip force testing lacks reliable sincerity assessment.
  • Variations in maximal vs. submaximal effort parameters are known.
  • Novel data analysis is needed to improve grip force measurement validity.

Purpose of the Study:

  • To explore machine learning (ML) for sincere/insincere grip force testing.
  • To compare ML with conventional statistical methods for accuracy.
  • To determine if hand load distribution patterns can predict effort sincerity.

Main Methods:

  • Utilized manugraphy data from 54 healthy subjects.
  • Analyzed load distribution patterns and percentage contributions of 7 hand areas.
  • Compared ML algorithm predictions with conventional statistical methods.
Keywords:
grip forcegrip force testinghand functionsinsincere effortload distributionmachine learningmalingeringmanugraphypredictive modelvalue of statistics

More Related Videos

One Dimensional Turing-Like Handshake Test for Motor Intelligence
14:05

One Dimensional Turing-Like Handshake Test for Motor Intelligence

Published on: December 15, 2010

27.2K
Studying Food Reward and Motivation in Humans
12:09

Studying Food Reward and Motivation in Humans

Published on: March 19, 2014

23.6K

Related Experiment Videos

Last Updated: Aug 9, 2025

Measurement of Spatial Stability in Precision Grip
09:36

Measurement of Spatial Stability in Precision Grip

Published on: June 4, 2020

3.3K
One Dimensional Turing-Like Handshake Test for Motor Intelligence
14:05

One Dimensional Turing-Like Handshake Test for Motor Intelligence

Published on: December 15, 2010

27.2K
Studying Food Reward and Motivation in Humans
12:09

Studying Food Reward and Motivation in Humans

Published on: March 19, 2014

23.6K

Main Results:

  • Conventional methods: 54% sensitivity, 78% specificity for insincere effort.
  • ML model: 94% sensitivity, 99% specificity for detecting submaximal effort.
  • ML accurately recognized submaximal effort via hand load distribution.

Conclusions:

  • Machine learning significantly enhances manugraphy validity.
  • ML algorithms offer superior accuracy in discerning grip effort sincerity.
  • Hand load distribution patterns are key indicators for ML-based sincerity detection.