摘要
通过下肢表面肌电信号的人体行走步态周期识别方法设计了实验系统;针对表面肌电信号的微弱性、交变性、低频性等特点,提出了识别肌肉动作起始时刻的峰—谷线性插值分段积分算法,并将该算法与阈值法相结合,提取足跟着地前肌肉动作起始时刻,从而达到划分步态周期的目的;该方法仅需单通道信号作为信息源,不同被测者可以选用不同的肌电信号;有效回避了肌电信号传感器零点漂移现象;文中分别对5位被测者行走时的7个下肢肌电信号进行采集,以VisualC++为工具,基于用户界面设计了步态周期的识别系统,其系统识别结果验证了该方法具有广泛性、可靠性、准确性和实用性。
An walking gait cycle identification system based on lower limb surface electromyogram is designed. Peak--valley linear inter-polation and piecewise integrator arithmetic, which can identify the starting action moment of muscle and aim at the faintness, alternating and low--frequency of the surface electromyogram, is presented. The starting action moment before heel--strike can be extracted through an appropriate threshold condition of the eigenvalues got by the arithmetic, so the gait cycle can he partitioned. Only one input signal source is re quired to be the information, and different surface electromyogram signals of lower limb could be gathered from different bodies. The signals analysised in this article are sampled from 7 surface electromyogram signals of 5 bodies when walking, the gait cycle identification system is designed through Visual C+ +6. 0 based on user interface. The results of the identification system show that the identification method is universal, reliable, accurate and practical.
出处
《计算机测量与控制》
CSCD
北大核心
2011年第8期1965-1967,1971,共4页
Computer Measurement &Control
基金
国家科技支撑计划(2009BAI71B04)
(2006BAI22B07)
关键词
表面肌电信号
步态周期
峰—谷线性插值分段积分算法
移动平均滤波
surface electromyogram, gait cycle, peak valley linear interpolation and piecewise integrator, moving average filtering