Barradas Victor R, Cho Woorim, Koike Yasuharu
Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, Japan.
School of Engineering, Tokyo Institute of Technology, Yokohama, Japan.
Front Hum Neurosci. 2023 Jan 20;16:805867. doi: 10.3389/fnhum.2022.805867. eCollection 2022.
Augmented feedback provided by a coach or augmented reality system can facilitate the acquisition of a motor skill. Verbal instructions and visual aids can be effective in providing feedback about the kinematics of the desired movements. However, many skills require mastering not only kinematic, but also complex kinetic patterns, for which feedback is harder to convey. Here, we propose the electromyography (EMG) space similarity feedback, which may indirectly convey kinematic and kinetic feedback by comparing the muscle activations of the learner and an expert in the task. The EMG space similarity feedback is a score that reflects how well a set of muscle synergies extracted from the expert can reconstruct the learner's EMG when performing the task. We tested the EMG space similarity feedback in a virtual bimanual polishing task that uses a robotic system to simulate the dynamics of a real polishing operation. We measured the expert's and learner's EMG from eight muscles in each arm during the real and virtual polishing tasks, respectively. The goal of the virtual task was to smoothen the surface of a virtual object. Therefore, we defined performance in the task as the smoothness of the object at the end of a trial. We separated learners into real feedback and null feedback groups to assess the effects of the EMG space similarity feedback. The real and null feedback groups received veridic and no EMG space similarity feedback, respectively. Subjects participated in five training sessions on different days, and we evaluated their performance on each day. Subjects in both groups were able to increase smoothness throughout the training sessions, with no significant differences between groups. However, subjects in the real feedback group were able to improve in the EMG space similarity score to a significantly greater extent than the null feedback group. Additionally, subjects in the real feedback group produced muscle activations that became increasingly consistent with an important muscle synergy found in the expert. Our results indicate that the EMG space similarity feedback promotes acquiring expert-like muscle activation patterns, suggesting that it may assist in the acquisition of complex motor skills.
由教练或增强现实系统提供的增强反馈可以促进运动技能的习得。言语指令和视觉辅助手段在提供有关期望动作的运动学反馈方面可能是有效的。然而,许多技能不仅需要掌握运动学,还需要掌握复杂的动力学模式,而对于这些模式,反馈更难传达。在此,我们提出肌电图(EMG)空间相似性反馈,它可以通过比较学习者和该任务专家的肌肉激活情况来间接传达运动学和动力学反馈。EMG空间相似性反馈是一个分数,反映了从专家身上提取的一组肌肉协同作用在执行任务时能够在多大程度上重构学习者的肌电图。我们在一个虚拟双手抛光任务中测试了EMG空间相似性反馈,该任务使用机器人系统来模拟真实抛光操作的动力学。我们分别在真实和虚拟抛光任务期间测量了专家和学习者每只手臂中八块肌肉的肌电图。虚拟任务的目标是使虚拟物体的表面变得光滑。因此,我们将任务中的表现定义为一次试验结束时物体的光滑度。我们将学习者分为真实反馈组和无反馈组,以评估EMG空间相似性反馈的效果。真实反馈组和无反馈组分别接受真实的和无EMG空间相似性反馈。受试者在不同的日子参加了五次训练课程,我们评估了他们每天的表现。两组受试者在整个训练课程中都能够提高光滑度,两组之间没有显著差异。然而,真实反馈组的受试者在EMG空间相似性分数上的提高程度明显大于无反馈组。此外,真实反馈组的受试者产生的肌肉激活与在专家身上发现的一种重要肌肉协同作用越来越一致。我们的结果表明,EMG空间相似性反馈促进了类专家肌肉激活模式的习得,这表明它可能有助于复杂运动技能的习得。