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Robotics, motor learning, and neurologic recovery.
Annual Review of Biomedical Engineering ( IF 12.8 ) Pub Date : 2004-07-17 , DOI: 10.1146/annurev.bioeng.6.040803.140223
David J Reinkensmeyer 1 , Jeremy L Emken , Steven C Cramer
Affiliation  

Robotic devices are helping shed light on human motor control in health and injury. By using robots to apply novel force fields to the arm, investigators are gaining insight into how the nervous system models its external dynamic environment. The nervous system builds internal models gradually by experience and uses them in combination with impedance and feedback control strategies. Internal models are robust to environmental and neural noise, generalized across space, implemented in multiple brain regions, and developed in childhood. Robots are also being used to assist in repetitive movement practice following neurologic injury, providing insight into movement recovery. Robots can haptically assess sensorimotor performance, administer training, quantify amount of training, and improve motor recovery. In addition to providing insight into motor control, robotic paradigms may eventually enhance motor learning and rehabilitation beyond the levels possible with conventional training techniques.

中文翻译:

机器人技术,运动学习和神经系统恢复。

机器人设备正在帮助人们了解健康和伤害方面的人体运动控制。通过使用机器人在手臂上施加新的力场,研究人员正在深入了解神经系统如何模拟其外部动态环境。神经系统根据经验逐步建立内部模型,并将其与阻抗和反馈控制策略结合使用。内部模型对环境和神经噪声具有鲁棒性,可以在整个空间范围内泛化,可以在多个大脑区域实施,并在儿童时期发展。机器人还被用于协助神经系统损伤后的重复性运动练习,从而提供对运动恢复的洞察力。机器人可以在触觉上评估感觉运动表现,进行训练,量化训练量并改善运动恢复。
更新日期:2019-11-01
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