Abstract
For robot-assisted rehabilitation and assessment of the patients with motor dysfunction, the parametric generation of their normal gait as the input for the robot is essential to match with the features of the patient to a greater extent. In addition, the gait needs to be in three-dimensional space, which meets the physiological structure of the human better, rather than only in sagittal plane. Thus, a method for the parametric generation of three-dimensional gait based on the influence of the motion parameters (MPs) and structure parameters (SPs) is presented. First, the three-dimensional gait kinematic of participants is collected, and trajectories of ankle joint angle and ankle center position are calculated. Second, for the trajectories, the gait features are extracted including gait events indicating the physiological features of the walking gait in additional to extremes indicating the geometrical features of the trajectories. Third, regression models are derived after using leave-one-out cross-validation for model optimization. Finally, cubic splines are fitted between the predicted gait features to generate the trajectories for a full gait cycle. It is inferred the generated curves well match the measured curves. The method presented herein will gives an important reference for the research of the lower limb rehabilitation robots.
Funder
National Key R&D Program of China
National Natural Science Foundation of China
Publisher
The Company of Biologists
Subject
General Agricultural and Biological Sciences,General Biochemistry, Genetics and Molecular Biology
Cited by
10 articles.
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