Identifikacija, analiza i klasifikacija kretanja zgloba kolena

Abstract

Gait is a fundamental human activity. One of the main joints that participate in walking process is knee joint. This joint is considered to be the largest and most complex joint in human body. This complexity comes from possibility of translation and rotation along and around all axes. All of these movements have corresponding pattern. Main purpose of this doctoral thesis is to identify and analyze standard values and patterns of basic movement parameters of healthy individuals. Experimental research was done in Clinical Centre Kragujevac on healthy individuals and on patients with deficient/diseased soft tissue and/or cartilaginous knee structures. Three systems were used for acquiring data – OptiTrack, Kinetic XBOX camera and simple web camera. Mathematical model of a knee was created for calculating identified gait parameters. It is concluded, with a help of statistical methods, that there is a significant difference in gait pattern between healthy individuals and patients with deficient/diseased knee joint structures. For the purpose of getting objective results, models for predicting/classification (based on logistic regression and neural network models) possible damage/illness of knee joint based on walk parameters values and gait curves were created. Models for predicting/classification are valued by diagnostic tests. Results showed that this approach can help in better understanding of processes in knee joint that occur during walking, can help to achieve objectivity in walking process evaluation, improve rehabilitation process depending on level of recovery of the patient, etc.