A System to Identify Walking Pattern Using Machine Learning for a Load Reduction Exoskeleton Robot

Hanqing Zhao, Hidetaka Nambo
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Abstract

In this study, to realize the gait recognition and gait prediction of Load reduction exoskeleton robot in the walking process. Firstly, we designed a plantar pressure measurement device. The information about walking posture of human legs, feet, and the whole body can be reflected by the magnitude and distribution of plantar pressure. The plantar pressure measurement device is used to collect data and generate the required training datasets. Gait recognition and gait prediction analysis are obtained by using deep neural networks and recurrent neural networks for gait recognition and gait prediction. Eventually, it can be applied to the control system of exoskeleton walking and abnormal gait prediction.
基于机器学习的减载外骨骼机器人行走模式识别系统
在本研究中,实现减载外骨骼机器人在行走过程中的步态识别和步态预测。首先,我们设计了一个足底压力测量装置。足底压力的大小和分布可以反映人的腿、脚和全身的行走姿势信息。足底压力测量装置用于收集数据并生成所需的训练数据集。采用深度神经网络和递归神经网络进行步态识别和预测,获得步态识别和预测分析。最终将其应用于外骨骼行走控制系统和异常步态预测。
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