A computational trajectory formation model for the human sagittal plane movement at various motion durations

被引:1
|
作者
Wada, Y
Aiba, T
Fukuzawa, K
机构
[1] Nagaoka Univ Technol, Nagaoka, Niigata 9402188, Japan
[2] Waseda Univ, Tokyo 1628644, Japan
关键词
trajectory formation; duration; sagittal plane;
D O I
10.1016/S0925-2312(01)00565-3
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
We have confirmed from human arm movement measurement on the sagittal plane that the highest position in the vertical direction where the hand passes through changes according to the motion duration. In this paper, we propose an estimation algorithm of the position where the hand passes through according to the variation in the motion duration. We add the algorithm into the hardware of the trajectory formation model, i.e., the forward inverse relaxation model, which is the trajectory formation model based on the minimum commanded torque change criterion. Finally, we show that the model can reproduce the same trajectories as the human trajectories at various motion durations on the sagittal plane. (C) 2001 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:1589 / 1594
页数:6
相关论文
共 50 条
  • [31] Human trajectory formation: Taxonomy of movement based on phase flow topology
    Huys, Raoul
    Jirsa, Viktor K.
    Studenka, Brearma E.
    Rheaume, Nicole
    Zelaznik, Howard N.
    COORDINATION: NEURAL, BEHAVIORAL AND SOCIAL DYNAMICS, 2008, : 77 - +
  • [33] Neural network based posture control of a human arm model in the sagittal plane
    Liu, Shan
    Wang, Yongji
    Huang, Jian
    ADVANCES IN NEURAL NETWORKS - ISNN 2006, PT 3, PROCEEDINGS, 2006, 3973 : 792 - 798
  • [34] Human Motion Trajectory Prediction Using the Social Force Model for Real-Time and Low Computational Cost Applications
    Gil, Oscar
    Sanfeliu, Alberto
    ROBOT 2023: SIXTH IBERIAN ROBOTICS CONFERENCE ADVANCES IN ROBOTICS, VOL 1, 2024, 976 : 235 - 247
  • [35] Trajectory Formation Based on a Human Arm Model with Redundancy
    Kashima, Tadashi
    Yanagihara, Keisuke
    Iwaseya, Masao
    PROCEEDINGS 2012 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC), 2012, : 959 - 963
  • [36] Central mechanisms for force and motion-Towards computational synthesis of human movement
    Hemami, Hooshang
    Dariush, Behzad
    NEURAL NETWORKS, 2012, 36 : 167 - 178
  • [37] Optimal trajectory formation and control of human arm point-to-point movement
    Sun, Pengwei
    Wang, Shimin
    Wang, Qi
    Fang, Jie
    Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics, 2010, 36 (07): : 826 - 829
  • [38] On Configuration Trajectory Formation in Spatiotemporal Profile for Reproducing Human Hand Reaching Movement
    Chen, Wenbin
    Xiong, Caihua
    Yue, Shigang
    IEEE TRANSACTIONS ON CYBERNETICS, 2016, 46 (03) : 804 - 816
  • [39] Research on Three-dimensional Motion History Image Model and Extreme Learning Machine for Human Body Movement Trajectory Recognition
    Chang, Zheng
    Ban, Xiaojuan
    Shen, Qing
    Guo, Jing
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2015, 2015
  • [40] Algorithmic differentiation improves the computational efficiency of OpenSim-based trajectory optimization of human movement
    Falisse, Antoine
    Serrancol, Gil
    Dembia, Christopher L.
    Gillis, Joris
    De Groote, Friedl
    PLOS ONE, 2019, 14 (10):