Buchanan T S, Moniz M J, Dewald J P, Zev Rymer W
Sensory Motor Performance Program, Rehabilitation Institute of Chicago, IL 60611.
J Biomech. 1993 Apr-May;26(4-5):547-60. doi: 10.1016/0021-9290(93)90016-8.
A technique for estimating isometric muscle forces based on EMGs and anatomical parameters is presented. In the present study, we record EMGs from five muscles acting at the wrist, during a series of isometric contractions in flexion, extension, ulnar deviation and radial deviation. The method then uses these EMG signals and the necessary anatomical data to estimate individual muscle forces. For one subject, complete anatomical parameters were estimated by MRI reconstruction of muscle moment arms and lines of muscle action. In all subjects, the errors associated with variability in the EMG signals were reduced through the use of signal processing techniques and intensive subject training. These EMG-based force estimates were then validated by evaluations at torque directions in which no mechanical redundancy existed. The stability of the solution space was examined using Monte Carlo simulations. The results of our study show that individual muscle forces at the wrist can be estimated with considerable accuracy, without assuming any control strategy (as is done with optimization theories). However, due to the limited mechanical redundancy of the wrist, it is uncertain whether the method can be used to estimate muscle forces in more highly redundant systems.
提出了一种基于肌电图(EMG)和解剖学参数估计等长肌力的技术。在本研究中,我们记录了在一系列等长收缩(包括屈曲、伸展、尺侧偏斜和桡侧偏斜)过程中,作用于手腕的五块肌肉的肌电图。该方法随后利用这些肌电图信号和必要的解剖学数据来估计各肌肉的力量。对于一名受试者,通过对肌肉力臂和肌肉作用线进行MRI重建来估计完整的解剖学参数。在所有受试者中,通过使用信号处理技术和强化受试者训练,减少了与肌电图信号变异性相关的误差。然后,通过在不存在机械冗余的扭矩方向上进行评估,对这些基于肌电图的力估计进行了验证。使用蒙特卡罗模拟检查了解决方案空间的稳定性。我们的研究结果表明,无需假设任何控制策略(如优化理论那样),就能以相当高的精度估计手腕处的各肌肉力量。然而,由于手腕的机械冗余有限,该方法是否可用于估计冗余度更高的系统中的肌肉力量尚不确定。