Son Choonghyun, Moon Hyunsik, Kim Daeeun, Chun Min Ho, Kim Seungjong, Choi Junho
Annu Int Conf IEEE Eng Med Biol Soc. 2018 Jul;2018:2475-2478. doi: 10.1109/EMBC.2018.8512766.
Rapidly aging society faces with increases in neurological disorders including stroke. Hemiplegia, which is one of the common sequelae due to stroke, causes difficulties in activities of daily living. As the number of stroke patients grows, demands for gait training increases, where robotic gait training systems are necessary. A robotic gait training system, called "COWALK-I," is designed to provide pelvic motion on the transverse plane as well as leg motions in the sagittal plane during gait training sessions. The pelvic motion allows weight-shifting as well as more natural gait patterns during gait training. In this research, effect of the pelvic motion during waking in the COWALK-I system is studied. Interaction force between the healthy subjects and the COWALK-I and electromyography(EMG) sensor data are measured. The average interaction forces did not show significant difference while each subject exhibited diverse patterns. The EMG signals shows that more activation of rectus femoris and less activation of gastrocnemius and gluteus medius.
快速老龄化社会面临包括中风在内的神经系统疾病增多的问题。偏瘫是中风常见的后遗症之一,会导致日常生活活动困难。随着中风患者数量的增加,对步态训练的需求也在增加,而机器人步态训练系统是必要的。一种名为“COWALK - I”的机器人步态训练系统旨在在步态训练过程中提供骨盆在横平面上的运动以及腿部在矢状平面上的运动。骨盆运动在步态训练中允许体重转移以及更自然的步态模式。在本研究中,研究了在COWALK - I系统中行走时骨盆运动的效果。测量了健康受试者与COWALK - I之间的相互作用力以及肌电图(EMG)传感器数据。平均相互作用力没有显示出显著差异,而每个受试者表现出不同的模式。EMG信号显示股直肌的激活更多,而腓肠肌和臀中肌的激活较少。