Forecasting Wear of Head and Acetabulum in Hip Joint Implant
Total hip joint replacement is a multi-aspect issue, where life span of the implant system in human body depends on numerous factors. One of the main reasons for having a hip replacement is loosening or wear of the associated components in artificial joint. The rate of wear depends mainly on the type of materials working together in the artificial joint, the burden resulting from the patient’s body weight, intensity of use, limb functionality, age of the patient’s and individual factors. The analysis of all factors leading to the joint wear and articulation expensiveness will allow for the appropriate selection of an head–acetabulum system which provide long-lasting and trouble-free operation. We use neuro–fuzzy systems to machine–learn the data to predict automatically the wear of elements in the artificial hip joint.
KeywordsMembership Function Fuzzy System Joint Component Fuzzy Inference Engine Femoral Head Fracture
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