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首页> 外文期刊>Mathematical Biosciences: An International Journal >A Poincare map based analysis of stroke patients' walking after a rehabilitation by a robot
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A Poincare map based analysis of stroke patients' walking after a rehabilitation by a robot

机译:基于Poincare地图的康复后康复患者分析

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Since the past decade, rehabilitation robots have become common technologies for recovering gait ability after a stroke. Nevertheless, it is believed that these robots can be further enhanced. Hence, several researches are making progress in optimizing gait rehabilitation robots. However, most of these researches have only assessed the robots and their controllers in improving spatiotemporal and kinetic features of walking. There are not many researchers have focused on the robots' controllers' effects on the central nervous or neuromuscular systems. On the other hand, recently computational methods have been utilized to investigate the rehabilitations of neural disorders, through developing neuromechanical models. However, these methods have neither studied the robot assisted gait rehabilitation, nor have they theoretically proved why rehabilitation exercises enhance patients' walking ability. Therefore, this paper merged a theoretical approach into a computational method to investigate the effects of gait rehabilitation robots on post-stroke neuromuscular system. To this end, a neuromechanical model of gait has been developed and thereby, the Poincare maps of intact and stroke people have been obtained. Comparison of these maps revealed why a stroke reduces the stability of walking. Then, the effect of an impedance controller, which is used in a rehabilitative robot, is scrutinized in stabilizing a walking motion. Obtaining the Poincare map of this close-loop system, proved that this controller improves motion stability. Finally, the effect of this controller is investigated by simulations and experiments. The experimental tests are performed by Arman rehabilitative robot.
机译:自过去十年以来,康复机器人已成为中风后恢复步态能力的常见技术。然而,据信这些机器人可以进一步增强。因此,几项研究正在优化步态康复机器人方面取得进展。然而,大多数这些研究只评估了机器人及其控制器,以改善行走的时空和动力学特征。没有许多研究人员专注于机器人的控制器对中枢神经或神经肌肉系统的影响。另一方面,通过开发神经力学模型,已经利用最近计算方法来研究神经障碍的康复。然而,这些方法既没有研究机器人辅助步态康复,也没有理论上证明为何康复锻炼提高患者的行走能力。因此,本文将理论方法与计算方法合并,以研究步态康复机器人对卒中后神经肌肉系统的影响。为此,已经开发了一种神经力学模型,从而获得了完整和中风人的庞然石地图。这些地图的比较揭示了为什么冲程降低行走的稳定性。然后,在恢复机器人中使用的阻抗控制器的效果被屏蔽在稳定行走运动中。获取此封闭环系统的庞加尔地图,证明了该控制器提高了运动稳定性。最后,通过模拟和实验研究了该控制器的效果。实验测试由Arman康复机器人进行。

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