This dissertation, "Generalized Artificial Finger Joint Design Process Employing Reverse Engineering Techniques" by Xiaoping, Wang, 王曉平, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author.
Abstract:
Abstract of thesis entitled Generalized Artificial Finger Joint Design Process Employing Reverse Engineering Techniques Submitted by WANG Xiaoping for the degree of Master of Philosophy at The University of Hong Kong in August 2003
Arthritis is a common disease that causes discomfort and disability in a significant number of individuals. Severe sufferers of this disease can only recover motion in their fingers with the aid of an artificial finger joint. The closer the artificial joint matches the finger anatomy, the greater the range of movement that can be achieved. However, it is not economically feasible to customise each joint to the patient. This study therefore describes a method of capturing finger joint surface data and efficiently processing and storing it so that generalised artificial finger joints can be manufactured as closely as possible to the human anatomy. The method uses the techniques of reverse engineering. A systematic approach for the construction of a generalized human finger joint model is proposed and divided into three main phases: finger joint digitalization, finger joint feature extraction, and generalized model construction. Finger joint digitalization process is used to obtain digital data from real finger joint specimens, which provides statistical samples for analysis used for the construction of the generalized model. Feature extraction process can be subdivided into two sequential steps. (1) NURBS surface reconstruction; and (2) surface curve feature extraction. NURBS surface reconstruction manipulates the sampled data and constructs surface models for subsequent feature extraction. The curve features which characterize the sampled finger joint geometries are then extracted and are used in the construction of the generalized model for the design of the finger joint prosthesis. The generalized model is constructed based on statistical analysis of the sampled finger joint specimens. Databases are built to hold the finger joint surface features and statistical analysis is applied to provide a generalized representation for finger joint replacement. From these statistical studies, different schemes to interpret the collected data are identified. In addition, the sampled specimens are categorized into different classes for specific populations to offer more precise and adaptive models. Compared with existing finger joint replacement design methods, the proposed approach is more widely applicable and accurate. An automatic implementation of the generalized model construction is presented, which has proven to be very efficient and flexible in finger joint replacement design.
DOI: 10.5353/th_b2953527
Subjects:
Finger joint - Data processing
Artificial joints - Design and construction
Reverse engineering
Generalized Artificial Finger Joint Design Process Employing Reverse Engineering Techniques
