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A rehabilitation gait training system for half lower limb disorder

机译:下半身障碍康复步态训练系统

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Gait training is one of main means of rehabilitation of lower limb disfunction. Nevertheless, the promotion of clinical gait training is inhibited by the professional skill and labor consumption of physiatrist. It is with great practical value to design an automatic rehabilitation equipment which could increase the effectiveness and quality of training progress, meanwhile reduce labor costs. In this paper, we presented a new automatic rehabilitation gait training system constructed by wearable sensors and robotic manipulator for hemiplegia patients. After that, using the measurement of normal lower limb, the correction of the disorder lower limb has been estimated. For the detection of the normal lower limb motion, a movement capturing system based on a Kinect and several wearable initial measurement units (IMU) is proposed, and a fusion method is designed to handle time synchronization between multiple sensors and to alleviate cumulative errors. After analyzing the lower limb trajectories, a gait model is constructed based on the regression model with spline interpolation. Finally, corrected lower limb gait trajectories generated by the constructed gait model is simulated using 3D animation, which illustrate the stability and practicability of the proposed system.
机译:步态训练是下肢功能障碍康复的主要手段之一。然而,生理学家的专业技能和劳力消耗抑制了临床步态训练的促进。设计一种自动康复设备,具有一定的实用价值,可以提高培训效果和质量,同时降低人工成本。在本文中,我们介绍了一种由可穿戴传感器和机器人操纵器构建的用于偏瘫患者的新型自动康复步态训练系统。之后,使用正常下肢的测量,可以估计下肢疾病的矫正。为了检测正常的下肢运动,提出了一种基于Kinect和几个可穿戴初始测量单元(IMU)的运动捕获系统,并设计了一种融合方法来处理多个传感器之间的时间同步并减轻累积误差。在分析了下肢的轨迹之后,基于带有样条插值的回归模型构建了步态模型。最后,使用3D动画对由构造的步态模型生成的校正后的下肢步态轨迹进行仿真,这说明了所提出系统的稳定性和实用性。

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