Seo Kap-Ho, Lee Ju-Jang
Department of Electrical Engineering and Computer Science, Korea Advanced Institute of Science and Technology, Daejon 305-701, Korea.
IEEE Trans Neural Syst Rehabil Eng. 2009 Apr;17(2):156-66. doi: 10.1109/TNSRE.2009.2015179. Epub 2009 Feb 18.
The ability to walk without the help of a caretaker enhances the quality of life for those who are bed-ridden or confined to a wheelchair. At present, most of the available gait rehabilitation robot systems have been designed to support the body weight externally. For gait training to be effective, a mobile body weight support (BWS) mechanism is needed. In mobile gait training robot systems, functions such as patient path following and constant BWS are important issues, particularly in dynamic environments. In the present study, two types of robotic systems were developed for gait rehabilitation. The first is known as the mobile manipulator type and the second the mobile vehicle type. The differences between the two systems in design and control are discussed. A control algorithm based on a neural network was used to compensate for dynamic interactions, unmodeled dynamics, and disturbances by the user on the system. Both electrical and pneumatic BWS mechanisms were built and compared. The proposed BWS systems were tested experimentally for their effectiveness in gait rehabilitation while maximizing the therapeutic outcome.
无需护理人员帮助就能行走，可提高卧床或依赖轮椅者的生活质量。目前，大多数现有的步态康复机器人系统都设计为从外部支撑身体重量。为使步态训练有效，需要一种可移动的身体重量支撑（BWS）机制。在移动步态训练机器人系统中，诸如患者路径跟踪和恒定BWS等功能是重要问题，尤其是在动态环境中。在本研究中，开发了两种用于步态康复的机器人系统。第一种是移动操纵器类型，第二种是移动车辆类型。讨论了这两种系统在设计和控制方面的差异。使用基于神经网络的控制算法来补偿系统上用户产生的动态相互作用、未建模动态和干扰。构建并比较了电动和气动BWS机制。对所提出的BWS系统进行了实验测试，以检验其在步态康复中的有效性，同时使治疗效果最大化。
