Abstract:
The article discusses the development of a mathematical model of human gait for the synthesis of a control system for a mechatronic rehabilitation complex. The relevance of the research is determined by the necessity to create effective rehabilitation technologies for patients with motor function impairments. Existing rehabilitation complexes can be divided into exoskeletons and devices with mechanical linkage (end effectors), with exoskeletons demonstrating higher rehabilitation effectiveness by mimicking natural gait. The scientific novelty of this study lies in the development of a model that takes into account the individual anthropometric parameters of the patient, including body mass and the lengths of limb segments, as well as the ability to simulate foot rotation. Within the framework of the study, a method for dividing the gait cycle into four phases is proposed, each described by a separate system of mathematical equations, which ensures high accuracy in reproducing various stages of movement. To validate the model, a marker-based motion capture system was used, which provided data on movement trajectories. The results showed that the model effectively generates trajectories of sagittal angles of hip, shank, and foot elevation, contributing to improved control of the rehabilitation device. In conclusion, the work emphasizes the importance of mathematical modeling for the development of adaptive control systems that can significantly enhance the rehabilitation process. Further research will focus on refining the model and integrating it with machine learning methods to improve the accuracy and reliability of rehabilitation programs.
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