Huang Xianwei, Naghdy Fazel, Naghdy Golshah, Du Haiping
IEEE Int Conf Rehabil Robot. 2017 Jul;2017:511-515. doi: 10.1109/ICORR.2017.8009299.
Robot-assisted therapy is regarded as an effective and reliable method for the delivery of highly repetitive rehabilitation training in restoring motor skills after a stroke. This study focuses on the rehabilitation of fine hand motion skills due to their vital role in performing delicate activities of daily living (ADL) tasks. The proposed rehabilitation system combines an adaptive assist-as-needed (AAN) control algorithm and a Virtual Reality (VR) based rehabilitation gaming system (RGS). The developed system is described and its effectiveness is validated through clinical trials on a group of eight subacute stroke patients for a period of six weeks. The impact of the training is verified through standard clinical evaluation methods and measuring key kinematic parameters. A comparison of the pre- and post-training results indicates that the method proposed in this study can improve fine hand motion rehabilitation training effectiveness.
机器人辅助治疗被视为一种有效且可靠的方法,用于在中风后恢复运动技能时提供高度重复的康复训练。本研究专注于精细手部运动技能的康复,因为它们在执行日常生活(ADL)的精细活动中起着至关重要的作用。所提出的康复系统结合了自适应按需辅助(AAN)控制算法和基于虚拟现实(VR)的康复游戏系统(RGS)。描述了所开发的系统,并通过对一组八名亚急性中风患者进行为期六周的临床试验来验证其有效性。通过标准临床评估方法和测量关键运动学参数来验证训练的效果。训练前后结果的比较表明,本研究提出的方法可以提高精细手部运动康复训练的有效性。