Exoskeleton robot measurement system, walking gait modeling analysis method and equipment

Abstract

An exoskeleton robot measurement system, a walking gait modeling and analysis method, a device, and a computer-readable storage medium, wherein the method includes: acquiring a trajectory signal of the hip joint rotation angle in the walking gait; according to the trajectory signal and The nonlinear oscillator model determines the modeling error; corrects the model parameters of the nonlinear oscillator model according to the modeling error, and the model parameters include the amplitude, phase and frequency of the nonlinear oscillator; according to the corrected The nonlinear oscillator model is updated with the model parameters. According to the trajectory signal of the hip joint rotation angle, the embodiment of the present application can realize the adaptive synchronization of the gait trajectory, and has fast convergence characteristics, parameter adaptability and noise robustness.

Description

technical field [0001] This article relates to the field of information processing, especially an exoskeleton robot measurement system, a walking gait modeling and analysis method, a device and a computer-readable storage medium. Background technique [0002] Walking is one of the most important daily activities. Gait modeling and analysis technology has important clinical significance for gait diagnosis, health assessment, sports rehabilitation and assistive devices. [0003] Gait digital modeling technology can quantitatively analyze gait parameters such as step length, step frequency, step width and various abnormal gait conditions, and provide the necessary basis for analyzing the principle of abnormal gait, correcting abnormal gait, and formulating treatment methods. At the same time, it also provides an objective basis for formulating rehabilitation treatment plan and evaluating rehabilitation efficacy. [0004] However, the feature space of human walking gait is comp...

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Problems solved by technology

[0004] However, the feature space of human walking gait is complex, there are large differences between individuals, and there is a strong coupling effect in the environment, so it is difficult to directly perform mathematical modeling and prediction

At present, gait modeling methods can be roughly divided into two categories: (1) based on captured human gait data; (2) based on dynamic modeling methods; the first type is data-based methods, which are based on captured data. Fitting prediction, its model is relatively fixed, poor adaptability to environmental changes, individual differences, etc. The second type of method is a method based on a dynamic model, which can accurately restore and analyze the kinematics and dynamics characteristics of the body under the walking gait. However, it relies on an accurate dynamic model. For the human body, parameters such as inertia, damping and stiffness of each part are difficult to obtain

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