Department of Electrical and Computer Engineering, Queen's University, Kingston, ON K7L 3N6, Canada.
IEEE Trans Biomed Eng. 2010 Apr;57(4):790-8. doi: 10.1109/TBME.2009.2036444. Epub 2009 Nov 20.
An important aspect of accurate representation of human movement is the ability to account for differences between individuals. The following paper proposes a methodology using Hill-based candidate functions in the fast orthogonal search (FOS) method to predict translational force at the wrist from flexion and extension torque at the elbow. Within this force-prediction framework, it is possible to implicitly estimate subject-specific physiological parameters of Hill-based models of upper arm muscles. Surface electromyography data from three muscles of the upper arm (biceps brachii, brachioradialis, and triceps brachii) were recorded from ten subjects, as they performed isometric contractions at varying elbow joint angles. Estimated muscle activation level and joint angle were utilized as inputs to the FOS model. Subject-specific estimates of optimal joint angles for the three muscles were determined via frequency analysis of the selected FOS candidate functions.
准确表示人体运动的一个重要方面是能够解释个体之间的差异。本文提出了一种使用基于 Hill 的候选函数在快速正交搜索(FOS)方法中预测手腕处的平移力的方法,该方法基于肘部处的屈伸扭矩。在这个力预测框架中,可以隐式估计基于 Hill 的上臂肌肉模型的特定于主体的生理参数。从十个受试者记录了上臂的三块肌肉(肱二头肌、肱桡肌和肱三头肌)的表面肌电图数据,因为他们在不同的肘关节角度下进行等长收缩。估计的肌肉激活水平和关节角度被用作 FOS 模型的输入。通过对选定的 FOS 候选函数进行频率分析,确定了三个肌肉的最佳关节角度的个体特异性估计值。