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3D Kinematic Gait Analysis for Preclinical Studies in Rodents
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Reliability of a commercially available and algorithm-based kinetic analysis software compared to manual-based

Kevin M Carroll1, John P Wagle1, Kimitake Sato1

  • 1a Department of Sport, Exercise, Recreation, and Kinesiology , East Tennessee State University , Johnson City , TN , USA.

Sports Biomechanics
|September 27, 2017
PubMed
Summary
This summary is machine-generated.

An algorithm-based kinetic analysis program demonstrated perfect reliability for athlete monitoring, outperforming manual methods. This offers coaches and sport scientists a superior tool for analyzing athlete force data.

Keywords:
Athlete monitoringforce-time analysissport science

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Area of Science:

  • Sports Science
  • Biomechanics
  • Performance Analysis

Background:

  • Reliable kinetic data analysis is crucial for athlete monitoring by coaches and sport scientists.
  • Current manual methods may lack consistent reliability for key performance metrics.

Purpose of the Study:

  • To assess the intra- and inter-rater reliability of a manual kinetic analysis program.
  • To evaluate the test-retest reliability of an algorithm-based kinetic analysis program for athlete monitoring.

Main Methods:

  • Five raters manually analyzed 100 isometric mid-thigh pull trials three times each.
  • The same trials were analyzed using an algorithm-based software.
  • Peak force and rate of force development (RFD) at 50ms and 200ms were measured.

Main Results:

  • Manual analysis showed high reliability for peak force (ICC > 0.92) but poor reliability for RFD (CV > 16.25% intra-rater, > 32.27% inter-rater).
  • The algorithm-based method achieved perfect reliability for all variables (ICC = 1.0, CV = 0%).

Conclusions:

  • While manual kinetic analysis can be reliable, algorithm-based methods offer superior, perfect reliability.
  • Algorithm-based analysis is recommended as a superior tool for athlete monitoring programs.