DocumentCode :
2102975
Title :
Classifying knee pathologies using instantaneous screws of the six degrees-of-freedom knee motion
Author :
Wolf, Alon ; Degani, Amir
Author_Institution :
Dept. of Mech. Eng., Technion-Israel Inst. of Technol., Haifa
fYear :
2006
fDate :
15-19 May 2006
Firstpage :
2946
Lastpage :
2951
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 screw parameters which describe the transformation of the tibia with respect to the femur in each two successive observation are represented as the instantaneous screw axis of the motion given in its Plucker line coordinate, along with its corresponding pitch. The set of screw parameters associated with a particular knee with a given pathology is then identified and clustered in R6 to form a "signature" of the motion for the given pathology. Bone 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 :
biomechanics; learning (artificial intelligence); medical computing; pattern classification; Plucker line coordinate; knee kinematics; knee pathologies; machine learning classifier; optical tracking system; screw theory; six degrees-of-freedom knee motion; Cities and towns; Fasteners; Humans; Knee; Machine learning; Mechanical engineering; Pathology; Performance evaluation; Robot kinematics; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation, 2006. ICRA 2006. Proceedings 2006 IEEE International Conference on
Conference_Location :
Orlando, FL
ISSN :
1050-4729
Print_ISBN :
0-7803-9505-0
Type :
conf
DOI :
10.1109/ROBOT.2006.1642149
Filename :
1642149
Link To Document :
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