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COMAP: A new computational interpretation of human movement planning level based on coordinated minimum angle jerk policies and six universal movement elements

机译:COMAP:基于协调的最小角度冲击策略和六个通用运动元素的人类运动计划水平的新计算解释

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Flash and Hogan (1985) suggested that the CNS employs a minimum jerk strategy when planning any given movement. Later, Nakano et al. (1999) showed that minimum angle jerk predicts the actual arm trajectory curvature better than the minimum jerk model. Friedman and Flash (2009) confirmed this claim. Besides the behavioral support that we will discuss, we will show that this model allows simplicity in planning any given movement. In particular, we prove mathematically that each movement that satisfies the minimum joint angle jerk condition is reproducible by a linear combination of six functions. These functions are calculated independent of the type of the movement and are normalized in the time domain. Hence, we call these six universal functions the Movement Elements (ME). We also show that the kinematic information at the beginning and end of the movement determines the coefficients of the linear combination. On the other hand, in analyzing recorded data from sit-to-stand (STS) transfer, arm-reaching movement (ARM) and gait, we observed that minimum joint angle jerk condition is satisfied only during different successive phases of these movements and not for the entire movement. Driven by these observations, we assumed that any given ballistic movement may be decomposed into several successive phases without overlap, such that for each phase the minimum joint angle jerk condition is satisfied. At the boundaries of each phase the angular acceleration of each joint should obtain its extremum (zero third derivative). As a consequence, joint angles at each phase will be linear combinations of the introduced MEs. Coefficients of the linear combination at each phase are the values of the joint kinematics at the boundaries of that phase. Finally, we conclude that these observations may constitute the basis of a computational interpretation, put differently, of the strategy used by the Central Nervous System (CNS) for motor planning. We call this possible interpretation "Coordinated Minimum Angle jerk Policy" or COMAP. Based on this policy, the function of the CNS in generating the desired pattern of any given task (like STS, ARM or gait) can be described computationally using three factors: (1) the kinematics of the motor system at given body states, i.e., at certain movement events/instances, (2) the time length of each phase, and (3) the proposed MEs. From a computational point of view, this model significantly simplifies the processes of movement planning as well as feature abstraction for saving characterizing information of any given movement in memory.
机译:Flash and Hogan(1985)建议中枢神经系统在计划任何给定运动时采用最小的跳动策略。后来,中野等。 (1999年)表明,最小角度跳动比最小跳动模型更好地预测了实际的手臂轨迹曲率。 Friedman and Flash(2009)证实了这一说法。除了我们将讨论的行为支持外,我们还将证明该模型可以简化计划任何给定运动的过程。特别是,我们用数学方法证明了,通过最小限度的六个关节的线性组合,可以满足每个最小关节角度跳动条件的运动。这些函数的计算与运动类型无关,并在时域中进行了归一化。因此,我们将这六个通用功能称为运动元素(ME)。我们还表明,运动开始和结束时的运动学信息决定了线性组合的系数。另一方面,在分析从坐到站(STS)转移,手臂伸直运动(ARM)和步态的记录数据时,我们观察到最小关节角度跳动条件仅在这些运动的不同连续阶段中得到满足,而在整个运动。根据这些观察结果,我们假定任何给定的弹道运动都可以分解成几个连续的相而没有重叠,这样,对于每个相,最小的关节角急动条件都得到了满足。在每个相位的边界处,每个关节的角加速度应获得其极值(零三阶导数)。结果,在每个阶段的关节角将是引入的ME的线性组合。每个阶段的线性组合系数是该阶段边界处的联合运动学值。最后,我们得出结论,这些观察结果可能构成对中枢神经系统(CNS)用于运动计划的策略进行计算解释的基础。我们称这种可能的解释为“协调最小角度冲击策略”或COMAP。基于此策略,CNS在生成任何给定任务(如STS,ARM或步态)的所需模式方面的功能可以使用以下三个因素进行计算描述:(1)在给定身体状态下的运动系统运动学,即,在某些运动事件/实例下,(2)每个阶段的时间长度,以及(3)建议的ME。从计算的角度来看,此模型显着简化了运动计划的过程以及用于将任何给定运动的特征信息保存在内存中的特征抽象的过程。

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