Skip to main navigation Skip to search Skip to main content

Regression model for predicting the maximum load of the movement

  • Mahidol University
  • Liverpool John Moores University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, the motion information is considered to be essential for calculating the corresponding maximum load of the movement. Due to the high cost of force plates and the challenges on practical scenes, recording the body joints' loading in a direct way is not feasible to do outside the laboratory. Therefore, the main purpose of this paper is to investigate the relationship between the motion pattern and the maximum load, using the regression analysis. In our experiments, the dataset contains 22 subjects. The motion information of each subject is recorded using the 3D motion-capture camera system. The knee's angles, hip's angles, and ankle's angles on sagittal and non-sagittal planes are investigated for predicting the maximum loads. Finally, the proposed method can achieve the average relative error about twelve percent for the prediction.

Original languageEnglish
Title of host publicationProceeding of 2017 2nd International Conference on Information Technology, INCIT 2017
EditorsWudhichart Sawangphol, Jarernsri L. Mitrpanont
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-4
Number of pages4
ISBN (Electronic)9781538614310
DOIs
Publication statusPublished - 1 Jul 2017
Event2nd International Conference on Information Technology, INCIT 2017 - Nakhon Pathom, Thailand
Duration: 2 Nov 20173 Nov 2017

Publication series

NameProceeding of 2017 2nd International Conference on Information Technology, INCIT 2017
Volume2018-January

Conference

Conference2nd International Conference on Information Technology, INCIT 2017
Country/TerritoryThailand
CityNakhon Pathom
Period2/11/173/11/17

Keywords

  • angles
  • maximum load prediction
  • moments
  • motion patterns
  • regression analysis

Fingerprint

Dive into the research topics of 'Regression model for predicting the maximum load of the movement'. Together they form a unique fingerprint.

Cite this