AUT LibraryAUT
View Item 
  •   Open Research
  • AUT Faculties
  • Faculty of Health and Environmental Sciences
  • School of Sport and Recreation
  • View Item
  •   Open Research
  • AUT Faculties
  • Faculty of Health and Environmental Sciences
  • School of Sport and Recreation
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

Detection of Different Throw Types and Ball Velocity With IMUs and Machine Learning in Team Handball

van den Tillaar, R; Bhandurge, S; Stewart, T
Thumbnail
View/Open
Conference Contribution (223.3Kb)
Permanent link
http://hdl.handle.net/10292/13633
Metadata
Show full metadata
Abstract
The purpose of this study was to investigate if an inertial measurement unit (IMU) and machine learning could be used to detect different types of team handball throws and predict ball velocity. Throwing was measured using IMUs and a radar gun in seventeen participants during standing, running and jump throws with a circular and whip-like wind up. Using these data, machine learning could predict peak ball velocity with an error of 1.05 m/s and classify approach types and throw types with ~85–90% accuracy. It was concluded that to monitor throwing load, the combination of inertial measurement units and machine learning offers a practical and automated method of quantifying throw counts and discriminating throw types in handball players under standard conditions.
Keywords
Throwing velocity; Artificial intelligence
Date
July 18, 2020
Source
ISBS Proceedings Archive: Vol. 38 : Iss. 1 , Article 48. Available at: https://commons.nmu.edu/isbs/vol38/iss1/48
Item Type
Conference Contribution
Publisher
International Society of Biomechanics in Sport (ISBS)
Publisher's Version
https://commons.nmu.edu/isbs/vol38/iss1/48/
Rights Statement
The following uses are always permitted to the author(s) and do not require further permission from provided the author does not alter the format or content of the articles, including the copyright notification: Posting of the article on the internet as part of a non-commercial open access institutional repository or other non-commercial open access publication site affiliated with the author(s)'s place of employment.

Contact Us
  • Admin

Hosted by Tuwhera, an initiative of the Auckland University of Technology Library

 

 

Browse

Open ResearchTitlesAuthorsDateSchool of Sport and RecreationTitlesAuthorsDate

Alternative metrics

 

Statistics

For this itemFor all Open Research

Share

 
Follow @AUT_SC

Contact Us
  • Admin

Hosted by Tuwhera, an initiative of the Auckland University of Technology Library