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In diagnosis and treatment of knee joint diseases, it is effective to study the three-dimensional (3D) motion of the patient's knee joint involving the femur, tibia, and patella. A 2D/3D registration method with use of fluoroscopy and CT images is promising for this purpose. However, there is no report showing whether the dynamic 3D motion of the patella can be obtained. In this study, we tried to examine dynamic 3D motion of the knee joint which included the patella. First, in order to investigate the accuracy of the position estimation, we conducted an experiment on a pig knee joint which had several fiducial markers placed on it, and we found that errors in the estimation of rotation and translation were less than 1 mm and 1 deg. We then carried out an image-acquisition experiment with healthy knee joints of three volunteers and confirmed that 3D motions of the femur, tibia, and patella were successfully obtained for all cases.

The purpose of this study is to develop a sheet-like curved type pneumatic rubber muscle and the power assist wear to assist an activity of daily living of aged or disabled person. In view of using the power assist wear in daily life, it is required to have compact, light-weight and flexibility. The developed sheet-liked curved type pneumatic rubber muscle is made of rubber band, and it has a high affinity for human skin. In this paper, the characteristics and the effectiveness of the sheet-liked curved type pneumatic rubber muscle and the developed power assist wear are described.

Previously, we proposed a 2D/3D registration method that uses Powell’s algorithm to obtain 3D motion of a knee joint by 3D computed-tomography and bi-plane fluoroscopic images. The 2D/3D registration is performed consecutively and automatically for each frame of the fluoroscopic images. This method starts from the optimum parameters of the previous frame for each frame except for the first one, and it searches for the next set of optimum parameters using Powell’s algorithm. However, if the flexion motion of the knee joint is fast, it is likely that Powell’s algorithm will provide a mismatch because the initial parameters are far from the correct ones. In this study, we applied a hybrid optimization algorithm (HPS) combining Powell’s algorithm with the Nelder–Mead simplex (NM-simplex) algorithm to overcome this problem. The performance of the HPS was compared with the separate performances of Powell’s algorithm and the NM-simplex algorithm, the Quasi-Newton algorithm and hybrid optimization algorithm with the Quasi-Newton and NM-simplex algorithms with five patient data sets in terms of the root-mean-square error (RMSE), target registration error (TRE), success rate, and processing time. The RMSE, TRE, and the success rate of the HPS were better than those of the other optimization algorithms, and the processing time was similar to that of Powell’s algorithm alone.