基于改进样本熵的牵张反射起始点检测研究  

Stretch reflex onset detection based on modified sample entropy

作　　者：胡保华[1] 朱宗俊 刘正士[1] 王勇[1] Hu Baohua;Zhu Zongjun;Liu Zhengshi;Wang Yong(School of Mechanical Engineering,Hefei University of Technology,Hefei 230009,China;Acupuncture&Rehabilitation Department,The First Affiliated Hospital of Anhui University of Chinese Medicine,Hefei 230031,China)

机构地区：[1]合肥工业大学机械工程学院,合肥230009 [2]安徽中医药大学第一附属医院针灸康复科,合肥230031

出　　处：《电子测量与仪器学报》2019年第2期1-9,共9页Journal of Electronic Measurement and Instrumentation

基　　金：国家自然科学基金(51279044);市级科技计划重点项目(2015cy04)资助

摘　　要：针对痉挛状态患者表面肌电(sEMG)信号质量差、易出现尖锐毛刺噪声且信号时序较短的问题,提出基于改进样本熵的牵张反射起始点(SRO)判定方法,利用固定长度的滑动窗对sEMG信号进行分帧,计算每帧信号改进样本熵,设定自适应阈值确定SRO,并分析对比了基于标准样本熵的SRO检测性能。实验结果表明,基于改进样本熵SRO最大识别率为89.06%,SRO识别能力优于标准样本熵(最大识别率为48.18%),且数据长度依赖性优于标准样本熵,在短时序列与含尖锐毛刺噪声sEMG信号处理上表现出更好的鲁棒性,为定量与细化上肢痉挛状态提供了基础。Surface electromyography(sEMG)signals of spasticity patients can be problematic due to involuntary spikes and the poor signal quality.Also,the length of sEMG signals can be very short.In order to solve these problems,a stretch reflex onset(SRO)detection method based on modified sample entropy is proposed:Firstly,sEMG signals are framed by a fixed-length sliding window and the sample entropy of each frame is calculated.Afterwards,adaptive threshold is set to determine the SRO.The results show that the modified sample entropy achieves improved performance in SRO detection compared with the standard sample entropy,and shows better robustness in processing shorter time data series and against spurious background spikes.The recognition accuracy rate reaches 89.06%using modified sample entropy but only reaches 48.18%when using standard sample entropy.The findings from this study show that the proposed method can provide insight as to the mechanisms underlying the passive resistance.

关 键 词：改进样本熵 表面肌电信号 痉挛状态 牵张反射起始点 

分 类 号：TH77[机械工程—仪器科学与技术]