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Biomechanical criterion of dynamic stability based on ZMP formula and Flash-Hogan principle of minimum jerk

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Języki publikacji
EN
Abstrakty
EN
The main aim of the article is to define a criterion of dynamic stability based on the Flash- Hogan principle and the ZMP method. The gait researches were focused on analysis and observation of the human biomechanism with the optical system Optitrack. The smooth reference trajectory is defined forming a stability pattern. The optimal, due to the minimum jerk criterion, ZMP trajectory is illustrated in the results Section in order to demonstrate the dynamic stability pattern for the needs of rehabilitation in cases of neuromuscular damage or injuries affecting gait stability.
Słowa kluczowe
Rocznik
Strony
3--9
Opis fizyczny
Bibliogr. 22 poz., rys.
Twórcy
  • Warsaw University of Technology, Faculty of Mechatronics, Warsaw, Poland
  • Lodz University of Technology, Faculty of Mechanical Engineering, Lodz, Poland
  • Lodz University of Technology, Faculty of Mechanical Engineering, Lodz, Poland
  • Lodz University of Technology, Faculty of Mechanical Engineering, Lodz, Poland
  • Lodz University of Technology, Faculty of Mechanical Engineering, Lodz, Poland
Bibliografia
  • 1. Antipov V., Postolny A., Yatsun A., Jatsun S., 2018, The control algorithm of the lower limb exoskeleton synchronous gait, MATEC Web of Conferences, 161.
  • 2. Arisumi H., Miossec S., Chardonnet J., Yokoi K., 2008. Dynamic lifting by whole body motion of humanoid robots, 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, 668-675.
  • 3. Bruijn S., Bregman D., Meijer O., Beek P., Dieën J., 2012, Maximum Lyapunov exponents as predictors of global gait stability: A modeling approach, Medical Engineering and Physics, 34, 4, 428-436.
  • 4. Engelbrecht S., 2001,Minimum principles in motor control, Journal of Mathematical Physiology, 45, 497-542.
  • 5. Flash T., Hogan N., 1985, The coordination of arm movements: An experimentally confirmed mathematical model, The Journal of Neuroscience, 5, 7, 1688-1703.
  • 6. Flash T., Hogan N., Richardson N., 2003, Optimization principles in motion control, [In:] The Handbook of Brain Theory and Neural Network, 2d ed., MIT Press, Cambridge, 827-831.
  • 7. Fligge N., McIntyre J., van der Smagt, 2012, Minimum jerk for human catching movements in 3D, The Fourth IEEE RAS/EMBS. International Conference on Biomedical Robotics and Biomechatronics.
  • 8. Gouwanda D., Muraledharan S., 2012, Local gait dynamic stability of individuals with knee brace and ankle brace, IEEE EMBS International Conference on Biomedical Engineering and Sciences.
  • 9. Ha T., Choi C., 2007, An effective trajectory generation method for bipedal walking, Robotics and Autonomous Systems, 55, 10, 795-810.
  • 10. Ilewicz G., Wojnarowski J., 2012, Anthropometrical model of human gait, International Journal of Applied Mechanics and Engineering, 17, 4, 1139-1148.
  • 11. Kazemi J., Ozgoli S., 2019, Real-time gait planner for human walking using a lower limb exoskeleton and its implementation on Exoped robot, Robotics and Autonomous Systems, 116, 1-23.
  • 12. Meirovitch Y., Bennequin D., Flash T., 2016, Geometrical invariance and smoothness maximization for task-space movement generation, IEEE Transactions on Robotics, 32, 4, 837-853.
  • 13. Mrozowski J., Awrejcewicz J., Bamberski P., 2008, Analysis of stability of the human gait, Journal of Theoretical and Applied Mechanics, 45, 1, 91-98.
  • 14. Popovic M., Goswami A., Herr H., 2005, Ground reference points in legged locomotion: definitions, biological trajectories and control implications, The International Journal of Robotics Research, 24, 12, 1013-1032.
  • 15. Sha D., Patton J., Mussa-Ivaldi, 2006, Minimum jerk reaching movements of human arm with mechanical constraints at endpoint, International Journal of Computers, Systems and Signals, 7, 1.
  • 16. Suleiman W. 2016, Inverse kinematics: new method for minimum jerk trajectory generation wholebody control for robots in the real world, IROS14 Workshop, Chicago.
  • 17. Todorov E., Jordan M., 1998, Smoothness maximization along a predefined path accurately predicts the speed profiles of complex arm movement, Journal of Neurophysiology, 80, 696-714.
  • 18. Vukobratović M., Borovac B., 2004, Zero-moment point thirty five years of its life, International Journal of Humanoid Robotics, 1, 1, 157-173.
  • 19. Vukobratović M., Juričić D., 1968, Contribution to the synthesis of biped gait, Proceedings of IFAC Symposium. Technical and Biological Problem on Control, Erevan, USSR.
  • 20. Xiang Y., Arefeen A., 2020, Two-dimensional team lifting prediction with floating-base box dynamics and grasping force coupling, Multibody System Dynamics, 50, 2, 211-231.
  • 21. Zatziorsky V., 1998, Kinematics of Human Motion, Human Kinetics, Champaign. IL, USA.
  • 22. Zatziorsky V., Seluyanov V., 1983, The mass and inertia characteristics of the mass segments of the human body, Biomechanics. Human Kinetics, 8b, 4b, 1152-115.
Uwagi
Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-fb8d8bd0-e611-4417-9b39-911507064beb
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