Abstract
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.
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Szarek, A., Korytkowski, M., Rutkowski, L., Scherer, R., Szyprowski, J. (2012). Forecasting Wear of Head and Acetabulum in Hip Joint Implant. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2012. Lecture Notes in Computer Science(), vol 7268. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29350-4_41
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DOI: https://doi.org/10.1007/978-3-642-29350-4_41
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29349-8
Online ISBN: 978-3-642-29350-4
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