Olree K S, Vaughan C L
Department of Biomedical Engineering, University of Virginia, Charlottesville 22903, USA.
Biol Cybern. 1995 Oct;73(5):409-14. doi: 10.1007/BF00201475.
Human gait is characterized by smooth, regular and repeating movements but the control system is complex: there are many more actuators (i.e. muscles) than degrees of freedom in the system. Statistical pattern-recognition techniques have been applied to examine muscle activity signals, but these have all concentrated exclusively on unilateral gait. We report here the application of factor analysis to the electromyographic patterns of 16 muscles (eight bilateral pairs) in ten normal subjects. Consistent with our prior work, we have established two factors, named loading response and propulsion, which correspond with important phases in the gait cycle. In addition, we have also discovered a third factor, which we have named the coordinating factor, that maintains the phase shift between the left and right sides. These findings suggest that the central nervous system solves the problem of high dimensionality by generating a few fundamental signals which control the major muscle groups in both legs.
人类步态的特点是动作平稳、规律且重复，但控制系统很复杂：系统中执行器（即肌肉）的数量比自由度多得多。统计模式识别技术已被用于检测肌肉活动信号，但这些技术都只专注于单侧步态。我们在此报告将因子分析应用于十名正常受试者的16块肌肉（八对双侧肌肉）的肌电图模式。与我们之前的工作一致，我们确定了两个因子，分别命名为负重反应和推进，它们与步态周期中的重要阶段相对应。此外，我们还发现了第三个因子，我们将其命名为协调因子，它维持左右两侧之间的相位差。这些发现表明，中枢神经系统通过生成一些控制双腿主要肌肉群的基本信号来解决高维度问题。
