Huang Felix C, Patton James L, Mussa-Ivaldi Ferdinando A
Sensory Motor Performance Program, Rehabilitation Institute of Chicago, Physical Medicine & Rehabilitation, 345 East Superior St., Room 1406, Chicago, IL 60611, USA. ; Physical Medicine and Rehabilitation, Mechanical and Biomedical Engineering, Northwestern University.
IEEE Int Conf Rehabil Robot. 2009 Jun;2009:474-479. doi: 10.1109/ICORR.2009.5209528.
We investigated how learning of inertial load manipulation is influenced by movement amplification with negative viscosity. Using a force-feedback device, subjects trained on anisotropic loads (5 orientations) with free movements in one of three conditions (inertia only, negative viscosity only, or combined), prior to common evaluation conditions (prescribed circular pattern with inertia only). Training with Combined-Load resulted in lower error (6.89±3.25%) compared to Inertia-Only (8.40±4.32%) and Viscosity-Only (8.17±4.13%) according to radial deviation analysis (% of trial mean radius). Combined-Load and Inertia-Only groups exhibited similar unexpected no-load trials (8.38±4.31% versus 8.91±4.70% of trial mean radius), which suggests comparable low-impedance strategies. These findings are remarkable since negative viscosity, only available during training, evidently enhanced learning when combined with inertia. Modeling analysis suggests that a feedforward after-effect of negative viscosity cannot predict such performance gains. Instead, results from Combined-Load training are consistent with greater feedforward inertia compensation along with a small increase in impedance control. The capability of the nervous system to generalize learning from negative viscosity suggests an intriguing new method for enhancing sensorimotor adaptation.
我们研究了负粘性运动放大对惯性负载操纵学习的影响。使用力反馈装置,受试者在三种条件之一(仅惯性、仅负粘性或两者结合)下,通过自由运动对各向异性负载(5个方向)进行训练,然后进行常规评估条件(仅惯性的规定圆形模式)。根据径向偏差分析(试验平均半径的百分比),与仅惯性组(8.40±4.32%)和仅粘性组(8.17±4.13%)相比,组合负载训练导致的误差更低(6.89±3.25%)。组合负载组和仅惯性组在意外无负载试验中的表现相似(试验平均半径的8.38±4.31%对8.91±4.70%),这表明两者采用了类似的低阻抗策略。这些发现很显著,因为仅在训练期间可用的负粘性,与惯性结合时明显增强了学习效果。建模分析表明,负粘性的前馈后效无法预测这种性能提升。相反,组合负载训练的结果与更大的前馈惯性补偿以及阻抗控制的小幅增加相一致。神经系统从负粘性中泛化学习的能力表明了一种增强感觉运动适应的有趣新方法。