Research Article

Toward a New Approach for Analysis of Joint Range of Motion in Three-dimensional Digitized Analysis by One Camera

Abstract

Introduction: The use of multiple cameras for motion analysis and single joint motion is very difficult and needs high technology in laboratory conditions. Detection of single joint motion in kinesthesia and analysis of its changes can be done by one camera at one direction. In this study, we present the validity and reliability of a new prototype simulator system used for motion analysis application.
Material and Methods: A moveable lever arm can rotate in three dimensions (3D) and can be controlled by three goniometers separately. A special software was written for the detection of four reflective markers that fixed to moveable liver arm, by one camera in front of it. Two approaches for this study were (a) selective and (b) random 3D simulation. Three repetitions for each variation and each dimension were selected and correlation was computed between simulator and images captured by camera.
Results: There are high correlations between simulator and one camera system for each condition. In addition, a minimum degree error appeared.
Conclusion: Results indicated that this new approach can be useful for all clinical and research approaches in biomechanical or occupational areas.

Schöler H. Production of photogrammetric stereo pairs by beam division in single-lens cameras. In: Szangolies K, editor. Kompendium Photogrammetrie XV. Leipzig, Germany: Akademische Verlagsgesellschaft Geest and Portig; 1981. p. 77-86.

Soutas-Little RW. Motion analysis and biomechanics. In: Delisa JA, editor. Gait analysis in the science of rehabilitation. Washington DC:

Veterans Administration, Rehabilitation Research and Development Service; 1998. p. 49-55.

Chun-sen Z. Motion stereo double matching restriction in 3D movement analysis. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences 2008; XXXVII(Part B3b): 675-80.

Wipf D, Palmer J, Rao B. Perspectives on sparse bayesian learning. Advances in Neural Information Processing Systems 2003; 16: 1-8. Available from: URL: http://papers.nips.cc/paper/2393-perspectives-on-sparse-bayesian-learning

Files
IssueVol 10 No 3 (2016) QRcode
SectionResearch Article(s)
Keywords
Joint motion Motion analysis Three-dimensional software
Rights and permissions
Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
How to Cite
1.
Talebian S, Mehdikhani R, Talebian M, Saba M, Olyaei GR. Toward a New Approach for Analysis of Joint Range of Motion in Three-dimensional Digitized Analysis by One Camera. jmr. 2017;10(3):134-138.