Osteoarthritis diagnosis using wear particle analysis technique: Investigation of correlation between particle and cartilage surface in walking process
Peng, Z. (2007) Osteoarthritis diagnosis using wear particle analysis technique: Investigation of correlation between particle and cartilage surface in walking process. Wear, 262 (5-6). pp. 630-640.
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Osteoarthritis (OA), the most prevalent form of arthritis, is a degenerative joint disease affecting millions of people worldwide. The overall aims of the project were: (i) to gain a better understanding of the wear processes occurring in human joints during a walking process, particularly in relation to osteoarthritic degeneration and (ii) to develop effective, minimally intrusive tools to assess OA activity and progression. Based on existing developments, this project, using three-dimensional numerical descriptors, further investigated correlation between the cartilage surface subjected and particle generated in the walking process. This is a critical step in developing and utilizing wear particle analysis techniques for OA assessment. With further study and development along with this study, it is possible to develop better diagnostic and prognostic procedures for clinic OA assessment using wear debris analysis techniques.
|Item Type:||Article (Refereed Research - C1)|
|Keywords:||quantitative wear debris; osteoarthritis; surface morphology; boundary characteristics; numerical parameters|
|FoR Codes:||09 ENGINEERING > 0903 Biomedical Engineering > 090302 Biomechanical Engineering @ 100%|
|SEO Codes:||92 HEALTH > 9202 Health and Support Services > 920203 Diagnostic Methods @ 40%|
92 HEALTH > 9205 Specific Population Health (excl. Indigenous Health) > 920502 Health Related to Ageing @ 30%
92 HEALTH > 9201 Clinical Health (Organs, Diseases and Abnormal Conditions) > 920116 Skeletal System and Disorders (incl. Arthritis) @ 30%
|Deposited On:||23 Jul 2009 12:17|
|Last Modified:||23 May 2013 00:28|
Last 12 Months: 0
|Citation Counts with External Providers:||Web of Science: 10|
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