Load-bearing optimization for customized exoskeleton design based on kinematic gait reconstruction.

This paper presents a load-bearing optimization method for customized exoskeleton design based on kinematic gait reconstruction (KGR). For people with acute joint injury, it is no longer probable to obtain the movement gait via computer vision. With this in mind, the 3D reconstruction can be executed from the CT (computed tomography) or MRI (magnetic resonance imaging) of the injured area, in order to generate micro-morphology of the joint occlusion. Innovatively, the disconnected entities can be registered into a whole by surface topography matching with semi-definite computing, further implementing KGR by rebuilding continuous kinematic skeletal flexion postures. To verify the effectiveness of reconstructed kinematic gait, finite element analysis (FEA) is conducted via Hertz contact theory. The lower limb exoskeleton is taken as a verification instance, where rod length ratio and angular rotation range can be set as the design considerations, so as to optimize the load-bearing parameters, which is suitable for individual kinematic gaits. The instance demonstrates that the proposed KGR helps to provide a design paradigm for optimizing load-bearing capacity, on the basis of which the ergonomic customized exoskeleton can be designed from merely medical images, thereby making it more suitable for the large rehabilitation population.