摘要
瘫痪病人的数量与日俱增,其康复训练通常是一个长期的过程.相对于传统的理疗,使用机器人辅助康复训练能够提高效率,降低成本,减少理疗师的人员和体力消耗,因此节省了康复医疗资源,并且可以完成更加多样的主被动训练策略,从而提高了康复效果.根据患者进行康复运动时的身体姿态,下肢康复机器人可分以下4类:坐卧式机器人、直立式机器人、辅助起立式机器人和多体位式机器人,坐卧式又细分为末端式和外骨骼式,直立式进一步划分为悬吊减重(Suspending body weight support,s BWS)式步态训练机器人和独立可穿戴式机器人.由于下肢康复机器人是与运动功能受损的患肢相互作用,为了给患者创造一个安全、舒适、自然的训练环境,机器人和患者之间的交互控制不可或缺.根据获取运动意图时所使用的传感器信号,交互控制可以基本分为两类:1)基于力信号的交互控制;2)基于生物医学信号的交互控制.在基于力信号的交互控制中,力位混合控制和阻抗控制是最为常用的两种方法;而在基于生物医学信号的交互控制中,表面肌电(Surface electromyogram,s EMG)和脑电(Electroencephalogram,EEG)最常被用于运动意图的推断.
The number of paralytic sufferers is currently growing huge and the rehabilitation for them is usually a long-time process. Compared to the traditional physiotherapy, rehabilitation with the assistance of robots can reduce the cost and time, and less labor intensity is required. Moreover, various training strategies are provided by robots, so that rehabilitation effect can be improved. Lower limb rehabilitation robots are categorized into horizontal exercisers, vertical locomotors, sit-to-stand aids and multi-orientation hybrids, according to the posture of patient during therapy. Horizontal exercisers are subcategorized into end effectors and exoskeletons, and vertical locomotors are further grouped as suspending body weight support （sBWS） based gait trainers and stand-alone wearables. Interactive control between mechanism and patient is required to create a secure, comfortable and natural training environment for paralytic patients. According to the signals employed to deduce the movement intention of patients, interactive control methods are classified into force-based control and biomedical-signal-based control. Two approaches that are in particular worth mentioning for force-based interactive control are hybrid force-position control and impedance control. Surface electromyogram （sEMG） and electroencephalogram （EEG） are two mostly used signals for biomedical-signal-based control.
出处
《自动化学报》
EI
CSCD
北大核心
2014年第11期2377-2390,共14页
Acta Automatica Sinica
基金
国家自然科学基金项目(61225017
61175076)
国家国际科技合作专项项目(2011DFG13390)资助~~
关键词
下肢康复机器人
研究现状
交互控制
生物医学信号
发展趋势
Lower limb rehabilitation robot
state of the art
interactive control
biomedical signals
future development
