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Computational model of a primate arm: from hand position to joint angles, joint torques and muscle forces

机译:灵长类动物手臂的计算模型:从手的位置到关节角度,关节扭矩和肌肉力

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摘要

Three-dimensional reaching by non-human primates is an important behavioral paradigm for investigating representations existing in motor control areas of the brain. Most studies to date have correlated neural activity to a few of the many arm motion parameters including: global hand position or velocity, joint angles, joint angular velocities, joint torques or muscle activations. So far, no single study has been able to incorporate all these parameters in a meaningful way that would allow separation of these often highly correlated variables. This paper introduces a three-dimensional, seven degree-of-freedom computational musculoskeletal model of the macaque arm that translates the coordinates of eight tracking markers placed on the arm into joint angles, joint torques, musculotendon lengths and finally into an optimized prediction of muscle forces. This paper uses this model to illustrate how the classic center-out reaching task used by many researchers over the last 20 years is not optimal in separating out intrinsic, extrinsic, kinematic and kinetic variables. However, by using the musculoskeletal model to design and test novel behavioral movement tasks, a priori, it is possible to disassociate the myriad of movement parameters in motor neurophysiological reaching studies.
机译:非人类灵长类动物的三维触及是研究大脑运动控制区域中存在的表示的重要行为范例。迄今为止,大多数研究都将神经活动与许多手臂运动参数中的一些相关,包括:整体手的位置或速度,关节角度,关节角速度,关节扭矩或肌肉激活。迄今为止,还没有一项研究能够以有意义的方式合并所有这些参数,从而无法分离这些通常高度相关的变量。本文介绍了猕猴手臂的三维,七自由度计算肌肉骨骼模型,该模型将放置在手臂上的八个跟踪标记的坐标转换为关节角度,关节扭矩,肌腱长度,最后转化为对肌肉的优化预测势力。本文使用该模型来说明过去20年中许多研究人员所使用的经典的中心向外到达任务在分离内在,外在,运动和动力学变量方面不是最佳方法。但是,通过使用肌肉骨骼模型先验设计和测试新的行为运动任务,可以在运动神经生理学研究中取消无数运动参数的关联。

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