Several kinds of knee motion simulator systems have been developed for the accurate analysis of knee biomechanics. Knee motion simulators, however, are not recognized for their practical use because of difficulties in design and control. In this study, a wire-driven knee simulator whichgenerates physiological knee motion has been developed. Physiological three-dimensional tibia motion against the femur can be generated by the simulator. Many clinical studies have been performed to analyze the length displacement pattern of the anterior cruciate ligament (ACL) and the posteriorcruciate ligament (PCL). We assume that the physiological knee motion can be realized if the length displacement patterns of the ACL and PCL against the knee flexion angle are the same as the experimental data obtained from the literature. A fuzzy neural control policy, one of the most effectiveintelligent control policies, has been applied for control of the simulator. Applying the fuzzy neural control policy, human knowledge and experience can be reflected and adaptive/learning ability can be incorporated in the controller. On-line learning of the fuzzy neural controller is carriedout to minimize a fuzzy controlled evaluation function using the back-propagation learning algorithm. The effectiveness of the proposed simulator has been evaluated by experiments using a model bone.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Human-Computer Interaction
- Hardware and Architecture
- Computer Science Applications