{"title":"动态收缩时表面肌电信号多重分形的来源分析","authors":"K. Marri, R. Swaminathan","doi":"10.1115/1.4032005","DOIUrl":null,"url":null,"abstract":"The aim of this study is analyze the origin of multifractality of surface electromyography (sEMG) signals during dynamic contraction in nonfatigue and fatigue conditions. sEMG signals are recorded from triceps brachii muscles of twenty two normal healthy subjects. The signals are divided into six equal segments on time scale for normalization. The first and sixth segments are considered as nonfatigue and fatigue condition respectively. The source of multifractality can be due to correlation and probability distribution. The original sEMG series are transformed into shuffled and surrogate series. These three series namely, original, shuffled and surrogate series in nonfatigue and fatigue conditions are subjected to multifractal detrended fluctuation analysis (MFDFA) and features are extracted. The results indicate that sEMG signals exhibit multifractal behavior. Further investigation revealed that origin of multifractality is primarily due to correlation. The origin of multifractality due to correlation is quantified as 80% in nonfatigue and 86% in fatigue conditions. This method of multifractal analysis may be useful for analyzing progressive changes in muscle contraction in varied neuromuscular studies.","PeriodicalId":73845,"journal":{"name":"Journal of nanotechnology in engineering and medicine","volume":"6 1","pages":"031002"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1115/1.4032005","citationCount":"9","resultStr":"{\"title\":\"Analyzing Origin of Multifractality of Surface Electromyography Signals in Dynamic Contractions\",\"authors\":\"K. Marri, R. Swaminathan\",\"doi\":\"10.1115/1.4032005\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aim of this study is analyze the origin of multifractality of surface electromyography (sEMG) signals during dynamic contraction in nonfatigue and fatigue conditions. sEMG signals are recorded from triceps brachii muscles of twenty two normal healthy subjects. The signals are divided into six equal segments on time scale for normalization. The first and sixth segments are considered as nonfatigue and fatigue condition respectively. The source of multifractality can be due to correlation and probability distribution. The original sEMG series are transformed into shuffled and surrogate series. These three series namely, original, shuffled and surrogate series in nonfatigue and fatigue conditions are subjected to multifractal detrended fluctuation analysis (MFDFA) and features are extracted. The results indicate that sEMG signals exhibit multifractal behavior. Further investigation revealed that origin of multifractality is primarily due to correlation. The origin of multifractality due to correlation is quantified as 80% in nonfatigue and 86% in fatigue conditions. This method of multifractal analysis may be useful for analyzing progressive changes in muscle contraction in varied neuromuscular studies.\",\"PeriodicalId\":73845,\"journal\":{\"name\":\"Journal of nanotechnology in engineering and medicine\",\"volume\":\"6 1\",\"pages\":\"031002\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1115/1.4032005\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of nanotechnology in engineering and medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1115/1.4032005\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of nanotechnology in engineering and medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/1.4032005","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analyzing Origin of Multifractality of Surface Electromyography Signals in Dynamic Contractions
The aim of this study is analyze the origin of multifractality of surface electromyography (sEMG) signals during dynamic contraction in nonfatigue and fatigue conditions. sEMG signals are recorded from triceps brachii muscles of twenty two normal healthy subjects. The signals are divided into six equal segments on time scale for normalization. The first and sixth segments are considered as nonfatigue and fatigue condition respectively. The source of multifractality can be due to correlation and probability distribution. The original sEMG series are transformed into shuffled and surrogate series. These three series namely, original, shuffled and surrogate series in nonfatigue and fatigue conditions are subjected to multifractal detrended fluctuation analysis (MFDFA) and features are extracted. The results indicate that sEMG signals exhibit multifractal behavior. Further investigation revealed that origin of multifractality is primarily due to correlation. The origin of multifractality due to correlation is quantified as 80% in nonfatigue and 86% in fatigue conditions. This method of multifractal analysis may be useful for analyzing progressive changes in muscle contraction in varied neuromuscular studies.