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Fuzzy Logic based Implementation of a Real-Time Gait Phase Detection Algorithm using Kinematical Parameters for Walking

机译:基于模糊逻辑的实时步态相位检测算法使用运动学参数步行

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The concept of fuzzy logic was applied to develop a gait phase detection algorithm, to address the complexity of distinguishing between gait phases based on gait parameters obtained for walking. The proposed intelligent algorithm detects seven gait phases taking into consideration only joint parameters. Three inertial sensors were placed at the thigh, shank and foot in order to acquire hip, knee and ankle joint angles. The main objective is to incorporate the algorithm to a rehabilitation device in order to determine accurate timing for feedback. The gait phases detected could also be analyzed to identify normal and abnormal gait depending on the sequence of gait phases detected. Experiments were carried out to validate the feasibility of the algorithm with the acquisition of the joint parameters for five gait cycles. This paper also elaborates the results obtained along with the graphical representation of the gait parameters and the gait phases detected for normal and abnormal walking gait.
机译:模糊逻辑的概念被应用于开发步态相位检测算法,以解决基于用于步行的步态参数的步态阶段区分的复杂性。所提出的智能算法检测到仅考虑联合参数的七个步态阶段。将三个惯性传感器放置在大腿,柄和脚上,以获得臀部,膝关节和踝关节角度。主要目的是将该算法纳入康复装置,以便确定反馈的准确定时。根据检测到的步态序列序列,也可以分析检测到检测到的步态阶段以识别正常和异常的步态。进行实验以验证算法的可行性与采集五个步态周期的接合参数。本文还详细阐述了与正常和异常行走步态检测到的步态参数的图形表示以及检测到的步态阶段的结果。

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