Université de Poitiers, Université de Tours, Centre National de la Recherche Scientifique, Centre de Recherches sur la Cognition et l'Apprentissage (UMR 7295), Poitiers, France.
Université de Poitiers, Université de Tours, Centre National de la Recherche Scientifique, Centre de Recherches sur la Cognition et l'Apprentissage (UMR 7295), Poitiers, France.
Hum Mov Sci. 2024 Jun;95:103221. doi: 10.1016/j.humov.2024.103221. Epub 2024 May 1.
Robotic assistance can improve the learning of complex motor skills. However, the assistance designed and used up to now mainly guides motor commands for trajectory learning, not dynamics learning. The present study explored how a complex motor skill involving the right arm can be learned without suppressing task dynamics, by means of an innovative device with robotic guidance that allows a torque versus motion profile to be learned with admittance control. In addition, we assessed how concurrent visual feedback on this profile can enhance learning without creating dependency, by means of a fading procedure (i.e., feedback reduction across trials). On Day 1, a Control group performed an acquisition session (6 blocks) featuring concurrent visual feedback, while a Fading group performed the session with a gradual reduction in feedback (from 100% to 0% over the 6 blocks). On Day 2, both groups performed a block first without feedback (i.e., Transfer test), then with feedback (i.e., Retention test). Results revealed that on Day 1, movement rehearsal induced a significant improvement in spatiotemporal parameters for the Control group, compared with the Fading group. On Day 2, the opposite was found when this visual feedback was removed, as the Fading group performed significantly better than the Control group on the Transfer test. Vision allows a relationship to be established between the required torque and the motion profile. Its suppression then forces the processing of more intrinsic information, leading to the development of a stable internal representation of the task.
机器人辅助可以提高复杂运动技能的学习效果。然而,到目前为止,设计和使用的辅助手段主要指导轨迹学习的运动指令,而不是动力学学习。本研究通过一种具有机器人引导功能的创新设备,探索了如何在不抑制任务动力学的情况下学习涉及右臂的复杂运动技能,该设备采用顺应性控制,允许学习扭矩与运动的关系。此外,我们还评估了在该轮廓上同时提供视觉反馈如何通过淡出程序(即在试验中逐渐减少反馈)增强学习而不产生依赖性。在第 1 天,对照组进行了一个包含视觉反馈的获取会话(6 个块),而淡出组则在会话中逐渐减少反馈(在 6 个块中从 100%减少到 0%)。在第 2 天,两组首先在没有反馈的情况下进行一个块(即转移测试),然后有反馈(即保持测试)。结果表明,在第 1 天,与淡出组相比,对照组的运动排练显著提高了时空参数。在第 2 天,当这种视觉反馈被移除时,情况正好相反,因为淡出组在转移测试中的表现明显优于对照组。视觉允许建立所需扭矩和运动轮廓之间的关系。它的抑制迫使处理更多的内在信息,从而导致任务的稳定内部表示的发展。