摘要
在线的步态相位识别和压力中心COP检测是两足类人机器人、人工假肢,以及腿部康复训练机器人的关键技术之一.建立了基于多传感器系统的测量模型,并分析了步态相位关系.采用鞋底传感器与膝关节弯曲传感器的信息融合实现了步态相位识别和COP的在线检测,取得了较好的测试效果.该系统可以识别步行周期的5个重要状态(支撑、膝关节弯曲、足跟抬起、摆动、足跟着地)和4个不稳定状态(前倾、后倾、左倾和右倾),并能够实时检测COP.进行了测量实验研究,试验结果表明,系统的可靠性高,能够自动识别第一个步态相位,可实现对被测者运动速度的自动补偿,这种方法可以判别正常步态与异常步态.
The calculation of the online gait phase identification and centre of pressure （COP） is one of the key technologies of biped robot, artificial limb, and rehabilitation robot. The multi-sensor based measure model is established in this paper and the gait phase is analyzed, In our research, 5 pieces of force sensitive resistors are used as exsole sensor, and a fibre sensor is used for measuring of the bend of the legs. Based on these sensors＇ data fusion, the online gait phase identification can be obtained. The 5 normal gait Phases such as Stance, Stance-knee-bend, Heel-off, Swing-bend, Swing-extend, Heel-strike and 4 Irregularities such as Stance-External-tip over, stance-internal-tip over, forward _tipping over, etc. can be identified with a combination of sensors. The COP can also be calculated real-timely. The identification is independent from the order of the walking. The reliability of the results is 100% attainable. The first gait phase is also identifiable. Additionally, whether human walks fast or quite slowly doesn＇t influence the identification result. The normal gait phase and irregularities can be distinguished.
出处
《哈尔滨工程大学学报》
EI
CAS
CSCD
北大核心
2007年第2期218-221,共4页
Journal of Harbin Engineering University
基金
国家自然科学基金资助项目(60575053)
黑龙江省自然科学基金资助项目(F2004-03)
关键词
步态相位
重心
两足机器人
康复机器人
测量系统
gait phase
centre of pressure
biped robot
rehabilitation
measuring system
