Recognizing knee pathologies by classifying instantaneous screws of the six degrees-of-freedom knee motion
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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 Plücker 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 “signature” 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.
KeywordsKnee kinematics Screw axis Pathology classification Support vector machines
This work has been supported by NSF ITR grant IIS-0325920.
- 1.Andriacchi T P, Alexander E J., et al. (1998) A point cluster method for in vivo motion analysis: applied to a study of knee kinematics. J Biomech Eng 120(6):743–749Google Scholar
- 2.Ball RS (1900) A treatise on the theory of screws. Cambridge University Press CambridgeGoogle Scholar
- 5.Bottlang M, Marsh JL, et al. (1998) Factors influencing accuracy of screw displacement axis detection with a D.C.-based electromagnetic tracking system. J Biomech Eng Trans ASME 120(3):431Google Scholar
- 12.Hart R, Mote C J, et al. (1991) A finite helical axis as a landmark for kinematic reference of the knee. J Biomech Eng 113(2):215–222Google Scholar
- 13.Hasan SS, Hurwitz DE, et al. (1998) Dynamic evaluation of knee instability during gait in anterior cruciate ligament deficient patients. Trans Orthop Res Soc 44:805Google Scholar
- 17.Maki B (1997) Gait changes in older adults: predictors of falls or indicators of fear? J Am Geriatr Soc 45:313–320Google Scholar
- 19.Roth B (1984) Screws, motors, and wrenches that cannot be bought in a hardware store. MIT Press, CambridgeGoogle Scholar
- 20.Scholten R J, Opstelten W, et al. (2003) Accuracy of physical diagnostic tests for assessing ruptures of the anterior cruciate ligament: a meta-analysis. J Fam PractGoogle Scholar