Visual analysis of multi-joint kinematic data

Authors:
Peter R. Krekel;Edward R. Valstar;Jurriaan de Groot;Frits H. Post;Rob G. H. H. Nelissen;Charl P. Botha
Affiliations:
Biomechanics and Imaging Group, Leiden University Medical Center and Computer Graphics, Delft University of Technology;Biomechanics and Imaging Group, Leiden University Medical Center and Biomechanical Engineering, Delft University of Technology;Department of Rehabilitation Medicine, Leiden University Medical Center;Computer Graphics, Delft University of Technology;Biomechanics and Imaging Group, Leiden University Medical Center;Computer Graphics, Delft University of Technology and Divison of Image Processing, Leiden University Medical Center
Venue:
EuroVis'10 Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization
Year:
2010

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Abstract

Kinematics is the analysis of motions without regarding forces or inertial effects, with the purpose of understanding joint behaviour. Kinematic data of linked joints, for example the upper extremity, i.e. the shoulder and arm joints, contains many related degrees of freedom that complicate numerical analysis. Visualisation techniques enhance the analysis process, thus improving the effectiveness of kinematic experiments. This paper describes a new visualisation system specifically designed for the analysis of multi-joint kinematic data of the upper extremity. The challenge inherent in the data is that the upper extremity is comprised of five cooperating joints with a total of fifteen degrees of freedom. The range of motion may be affected by subtle deficiencies of individual joints that are difficult to pinpoint. To highlight these subtleties our approach combines interactive filtering and multiple visualisation techniques. Our system is further differentiated by the fact that it integrates simultaneous acquisition and visual analysis of biokinematic data. Also, to facilitate complex queries, we have designed a visual query interface with visualisation and interaction elements that are based on the domain-specific anatomical representation of the data. The combination of these techniques form an effective approach specifically tailored for the investigation and comparison of large collections of kinematic data. This claim is supported by an evaluation experiment where the technique was used to inspect the kinematics of the left and right arm of a patient with a healed proximal humerus fracture, i.e. a healed shoulder fracture.