...
首页> 外文期刊>international journal of emerging electric power systems >Upper limb movement simulation and biomechanical characteristics during human movement
【24h】

Upper limb movement simulation and biomechanical characteristics during human movement

机译:人体运动过程中的上肢运动模拟和生物力学特性

获取原文
获取原文并翻译 | 示例

摘要

The movement process of the human body is not the movement process of a single limb, but the movement process of skeletal muscles that coordinate multiple adjacent limbs with joints as the hub. Human body movement has different actions and links. When observing the human body movement mechanism, introducing the body movement chain can maintain the integrity and independence of the movement system. The upper limb of the human body is a kinematic chain with multiple limbs and multiple degrees of freedom, which can perform various complex movements. This article mainly introduces the upper limb movement simulation and biomechanical characteristics analysis during human movement, and intends to provide some ideas and directions for the upper limb movement simulation and biomechanical characteristics research during human movement. This paper proposes the research methods of upper limb motion simulation and biomechanical characteristics analysis during human movement, summarizes the human upper limb physiological structure and the relevant theoretical knowledge of human body biomechanics, and proposes the human upper limb motion capture and the human upper limb posture description algorithm for the human body Simulation experiment of upper limb movement during exercise. The experimental results of this paper show that the overall prediction time of simulation using MSCNN is only 0.0065 s, which ensures the real-time prediction.
机译:人体的运动过程不是单个肢体的运动过程,而是以关节为枢纽协调多个相邻肢体的骨骼肌的运动过程。人体运动有不同的动作和环节。在观察人体运动机理时,引入人体运动链可以保持运动系统的完整性和独立性。人体的上肢是一条具有多肢体、多自由度的运动链,可以进行各种复杂的运动。本文主要介绍人体运动过程中的上肢运动模拟和生物力学特征分析,旨在为人体运动过程中的上肢运动模拟和生物力学特征研究提供一些思路和方向。本文提出了人体运动过程中上肢运动模拟和生物力学特征分析的研究方法,总结了人体上肢生理结构和人体生物力学的相关理论知识,提出了人体上肢运动捕捉和人体上肢姿态描述算法,用于人体运动过程中上肢运动的模拟实验。实验结果表明,使用MSCNN进行仿真的总体预测时间仅为0.0065 s,保证了实时性预测。

著录项

获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号