The Robotics Institute

Carnegie Mellon Robotics Institute

Not available for download due to copyright restrictions. Please contact the author(s) for a copy.

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract

We address the problem of knee pathology assessment by using screw theory to describe the knee motion and by using the screw representation of the motion as an input to a machine learning classifier. The flexions of knees with different pathologies are tracked using an optical tracking system. The instantaneous screw parameters which describe the transformation of the tibia with respect to the femur in each two successive observation is represented as the instantaneous screw axis of the motion given in its Pl?ker line coordinates along with its corresponding pitch. The set of instantaneous screw parameters associated with a particular knee with a given pathology is then identified and clustered in R^6 to form a ?ignature?of the motion for the given pathology. Sawbones model and two cadaver knees with different pathologies were tracked, and the resulting screws were used to train a classifier system. The system was then tested successfully with new, never-trained-before data. The classifier demonstrated a very high success rate in identifying the knee pathology.

Keywords

Knee kinematics, Screw axis, Pathology classification, Support vector machines

Notes

Grant ID: Berlin / Heidelberg

Associated Center(s) / Consortia: Center for the Foundations of Robotics

Associated Lab(s) / Group(s): Biorobotics and Biomedical Robotics Lab

Number of pages: 8

Text Reference

Alon Wolf and Amir Degani, "Recognizing knee pathologies by classifying instantaneous screws of the six degrees-of-freedom knee motion," Medical and Biological Engineering and Computing, Vol. 45, No. 5, May, 2007, pp. 475-482.

BibTeX Reference

@article{Wolf_2007_5952,
   author = "Alon Wolf and Amir Degani",
   title = "Recognizing knee pathologies by classifying instantaneous screws of the six degrees-of-freedom knee motion",
   journal = "Medical and Biological Engineering and Computing",
   pages = "475-482",
   publisher = "Springer",
   address = "Berlin / Heidelberg",
   month = "May",
   year = "2007",
   volume = "45",
   number = "5",
}

The Robotics Institute

Menu