Riener R, Straube A
Department of Automatic Control Engineering, Technical University of Munich, Germany.
J Neurosci Methods. 1997 Mar;72(1):87-96. doi: 10.1016/s0165-0270(96)02168-1.
Kinematic analysis of limb movements can be used to evaluate motion of patients with movement disorders. Those with clinically mild to moderate impairment, however, often show only small, insignificant deviations in the measured trajectories compared to those of healthy controls. Furthermore, kinematic data alone do not give sufficient information about internal quantities such as muscle activation or joint moments. In order to improve the sensitivity of motion analysis of limb movements, we propose the use of inverse dynamics, since it allows biomechanical quantities to be determined without restricting movement. We developed an inverse dynamic model of the upper limb with 9 degrees of freedom. Spatial positions (Cartesian coordinates) of anatomical landmarks, which were recorded by an infrared video-based three-dimensional motion analysis system, are transformed into body-related Cardan angles. The model determines joint moments and powers at the shoulder, elbow, and wrist. Arm tracking movements in a patient with a mild cerebellar ataxia and a healthy control demonstrate that the model allows a clear differentiation between normal and abnormal limb movements, even if no significant differences are noted in the recorded trajectories. We conlude that inverse dynamic modeling can be an effective tool for motion analysis in patients with cerebellar disorders. It also gives further insight into the parameters that may be controlled by the central nervous system.
肢体运动的运动学分析可用于评估运动障碍患者的运动情况。然而,那些临床症状为轻度至中度受损的患者,与健康对照组相比,在测量轨迹上往往仅表现出微小的、不显著的偏差。此外,仅运动学数据无法提供足够的关于内部量的信息,如肌肉激活或关节力矩。为了提高肢体运动分析的敏感性,我们建议使用逆动力学,因为它能够在不限制运动的情况下确定生物力学量。我们开发了一个具有9个自由度的上肢逆动力学模型。通过基于红外视频的三维运动分析系统记录的解剖标志点的空间位置(笛卡尔坐标)被转换为与身体相关的卡尔丹角。该模型可确定肩部、肘部和腕部的关节力矩和功率。对一名轻度小脑共济失调患者和一名健康对照者的手臂跟踪运动进行的研究表明,即使在记录的轨迹中未发现显著差异,该模型也能清晰地区分正常和异常的肢体运动。我们得出结论,逆动力学建模可以成为小脑疾病患者运动分析中的有效工具。它还能进一步深入了解可能由中枢神经系统控制的参数。