利用sEMG能量高斯分布特性提取动作信号的方法  

Motion Signal Extraction Method Based on sEMG Energy Gauss Distribution Characteristics

作　　者：李瑞辉[1] 范志坚[1] 赵翠莲[1] 罗林辉[1] 王凯 

机构地区：[1]上海大学上海市机械自动化及机器人重点实验室,上海市200072 [2]上海市静安区老年医院康复科,上海市200040

出　　处：《中国医疗器械杂志》2014年第3期177-180,共4页Chinese Journal of Medical Instrumentation

基　　金：上海市重点学科建设项目资助(Y0102);上海市科学技术委员会重点科技攻关项目资助(10441900800)

摘　　要：对于采集到的连续动作肌电信号,首先要进行动作信号的分割和提取,该文针对肌电能量阈值需要反复人工试验才能设置的问题,从sEMG信号能量高斯分布特性出发,建立了连续重复动作的数学模型,进而根据高斯分布的区间规律设定能量阈值,结合能量比较的方法实现了动作信号的有效分割和提取。实验表明,该方法可以实现连续重复动作的有效分割,并且与信号手工分段的结果相比,达到了较高的重合度。Motion segment and extraction from continuous signals is the premise of surface electromyography （sEMG） analysis, For the problem that sEMG energy threshold required repeated manual testing to set, this the paper established a this mathematical model of continuous actions based on Gaussian sEMG energy curve, in which the energy threshold was set according to the distribution of Gaussian signal section, and differentiated the action signals from no-action signals combined with energy comparison method. The experiment results showed the method can achieve continuous repetitive action segmentation, and compared with manual segmentation of the same signal, has a higher degree of coincidence.

关 键 词：表面肌电信号 动作提取 高斯分布 能量阈值 

分 类 号：R318[医药卫生—生物医学工程]