基于矢状面质心角动量的人类行走步态周期阶段划分方法
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(燕山大学电气工程学院,河北秦皇岛066004)

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E-mail: leowang587@aliyun.com.

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TP24

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国家自然科学基金项目(61503325);中国博士后科学基金项目(2015M581316).


Division method of human walking gait cycle based on centroid angular momentum
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(Institute of Electrical Engineering, Yanshan University,Qinhuangdao066004,China)

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    摘要:

    认知人类的步行机理是双足机器人开发的重要基础.在人类行走过程中,外力力矩是影响行走稳定性的决定性因素,步态与外力力矩的相互作用是人类步行机理研究中的关键问题.尽管质心角动量可反映人体受到的外力力矩变化,但会随步态的演化呈现不同的变化规律.以人类自然行走步态为研究目标,通过准确获取人体行走过程中实时运动信息与质心角动量的变化,根据人体行走过程中的外力力矩与质心角动量的角度对人体步态进行力学分析,并结合人体行走过程中的足地关系与矢状面质心角动量变化规律,得出角动量特征点与步态特征点在时间上具有高度一致性的结论,最终实现基于矢状面质心角动量的人类步态周期阶段的精准划分.研究结果对于认知人类步行机理,指导行走康复医疗和双足机器人研发具有重要意义.

    Abstract:

    The cognition of human walking mechanism is an important foundation for the development of bipedal robots. During human walking, the external force moment is the decisive factor affecting the stability of walking, the interaction between gait and external force moment is a key issue in the study of human walking mechanism. The centroid angular momentum can reflect the change of external force received by the human body, but it will show different changing rules with the evolution of gait. In this paper, the human walking gait is taken as the research goal to accurately obtain the change of the real-time motion information and the centroid angular momentum during the human walking, Then, the mechanical analysis of the human gait is carried out according to the external force moment and the angle of centroid angular momentum during human walking, and combining with the changing rules between the foot-land relationship and the sagittal-centered centroid momentum during human walking, the conclusion is obtained that the angular momentum feature points and the gait feature points are highly consistent in time. Finally, the precise division of the human gait cycle phase based on the sagittal plane centroid angular momentum is realized. The result is of great significance for understanding the mechanism of human walking and guiding the rehabilitation therapy and the development of bipedal robot.

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吴晓光,王挺进,韦磊,等.基于矢状面质心角动量的人类行走步态周期阶段划分方法[J].控制与决策,2020,35(1):91-98

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  • 在线发布日期: 2019-12-27
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