An Inverse Optimal Control Approach to Explain Human Arm Reaching Control Based on Multiple Internal Models

被引:17
|
作者
Oguz, Ozgur S. [1 ]
Zhou, Zhehua [1 ]
Glasauer, Stefan [2 ]
Wollherr, Dirk [1 ]
机构
[1] Tech Univ Munich, Dept Elect & Comp Engn, Chair Automat Control Engn LSR, D-80333 Munich, Germany
[2] Ludwig Maximilian Univ Munich, Dept Neurol, D-81377 Munich, Germany
来源
SCIENTIFIC REPORTS | 2018年 / 8卷
关键词
FEEDBACK-CONTROL; MOTOR CONTROL; OPTIMIZATION; ADAPTATION; MOVEMENTS; COORDINATION; FEEDFORWARD; PRIMITIVES; PRINCIPLES; ACCURATE;
D O I
10.1038/s41598-018-23792-7
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Human motor control is highly efficient in generating accurate and appropriate motor behavior for a multitude of tasks. This paper examines how kinematic and dynamic properties of the musculoskeletal system are controlled to achieve such efficiency. Even though recent studies have shown that the human motor control relies on multiple models, how the central nervous system (CNS) controls this combination is not fully addressed. In this study, we utilize an Inverse Optimal Control (IOC) framework in order to find the combination of those internal models and how this combination changes for different reaching tasks. We conducted an experiment where participants executed a comprehensive set of free-space reaching motions. The results show that there is a trade-off between kinematics and dynamics based controllers depending on the reaching task. In addition, this trade-off depends on the initial and final arm configurations, which in turn affect the musculoskeletal load to be controlled. Given this insight, we further provide a discomfort metric to demonstrate its influence on the contribution of different inverse internal models. This formulation together with our analysis not only support the multiple internal models (MIMs) hypothesis but also suggest a hierarchical framework for the control of human reaching motions by the CNS.
引用
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页数:17
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