广东商学院数学与计算科学学院基于肌电信号的行为识别的研究本科毕业论文（设计）基于肌电信号的行为识别的研究院（系）数学与计算科学学院专业信息与计算科学班级09信息与计算科学一班提交日期2013年月日毕业论文(设计)成绩评定表毕业论文（设计）指导教师评语及成绩1广东商学院2013-JX16-广东商学院数学与计算科学学院基于肌电信号的行为识别的研究成绩指导教师签名年月日毕业论文（设计）复评教师评语及成绩成绩复评教师签名年月日毕业论文（设计）答辩评语及成绩成绩答辩委员会主席签名年月毕业论文（设计）总成绩（五级记分制）院（系）负责人签名年月日TITLE:RecognitionResearchBasedOnTheBehaviorofTheEMGSignal2广东商学院数学与计算科学学院基于肌电信号的行为识别的研究MAJOR:InformationAndComputingScience内容摘要3广东商学院数学与计算科学学院基于肌电信号的行为识别的研究本文对前臂肌肉群多个位置（包括肱桡肌、桡侧腕屈肌、桡侧腕长伸肌、尺侧腕伸肌、尺侧腕屈肌）进行表面肌电信号的采集，用RMS（均方差）与AR模型两种方法分别对采集的肌电信号进行特征分析和特征提取，再通过不同的分类方法（包括监督式学习、LDA分类算法）对现有的信号数据进行模式识别，区别屈肘、屈腕、屈指和前臂旋转等多种动作，最终使用MATLAB实验软件绘图直观表示各种分类方法的识别率，得到多种分类方法的优劣程度并最终得出结论从而将该项的研究成果拓展到人体其他肌群及相关假肢的控制中，另外在仿生控制人工动力假肢研究领域同样具有重要的意义。关键词：特征提取模式识别MATLAB表面肌电信号AbstractInthisresearch,IcollectthesurfaceEMGsinseveraloftheforearmmusclegroups(includingbrachioradialis、flexorcarpi、carpiradialislongus、extensorcarpiulnarisandflexorcarpiulnaris).WiththemethodssuchasRMSandARmodel,IextractthefeaturefromtheEMGswhichhasbeencollected.Thenbyusingclassificationmethods(SupervisedLearning:TheLDAalgorithm),IusetheexistingEMGsinordertodifferentiatebetweenelbow、wristflexion,、flexor、forearmrotationandsoon.Ialsousetwomoresignaloptimizationstoraiserecognitionrate.Ultimately,weuseMATLABtoplotpicturesandintuitivelytoshowtherecognitionrate.Finallythebestrecognitionrateis98.611%.4广东商学院数学与计算科学学院基于肌电信号的行为识别的研究Keywords:PatternrecognitionFeatureextractionSEMG目录1引言···································································11．1理论研究····························································11．2国内外文献综述与研究现状·······················································12表面肌电信号的采集··································································32．1肌电信号的模型说明································································32．2肌电信号的数据说明································································42.2.1肌电信号的拾取················································5广东商学院数学与计算科学学院基于肌电信号的行为识别的研究··················42.2.2肌电信号的位置··································································52.2.3动作展示·······································...
