{"title":"Salat相关肌肉收缩的频率肌电功率谱分析","authors":"Farzana Khanam, Mohiudding Ahmad","doi":"10.1109/CEEE.2015.7428245","DOIUrl":null,"url":null,"abstract":"Mean frequency (MNF) based EMG power spectrum analysis is presented to determine Salat associated muscle fatigue and indices. The main complexity of the parameter is a non-linear relationship between muscle fatigue and feature value, especially in large muscle and in cyclic dynamic contraction which is solved by this proposal. By this work, we can compute frequency dependent MNF for dynamic contractions and relaxations. Through Acknowledge software, FB-MNF is calculated and compared with the standard MNF. The results demonstrate that mean parameter of selected FB-MNF has a better linear relationship with muscle contraction compared to the others for different subjects. In addition, it has been observed through analysis of variance (ANOVA), compared to the traditional methods and have a significant difference (p<;0.05) between feature values among the MNF signal data of EMG power spectrum for different subjects. Furthermore, we have computed Mean Power (MNP), Total Power (TTP) and Peak Frequency (PKF) to determine both muscle load and muscle fatigue indices.","PeriodicalId":6490,"journal":{"name":"2015 International Conference on Electrical & Electronic Engineering (ICEEE)","volume":"19 1","pages":"161-164"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"Frequency based EMG power spectrum analysis of Salat associated muscle contraction\",\"authors\":\"Farzana Khanam, Mohiudding Ahmad\",\"doi\":\"10.1109/CEEE.2015.7428245\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Mean frequency (MNF) based EMG power spectrum analysis is presented to determine Salat associated muscle fatigue and indices. The main complexity of the parameter is a non-linear relationship between muscle fatigue and feature value, especially in large muscle and in cyclic dynamic contraction which is solved by this proposal. By this work, we can compute frequency dependent MNF for dynamic contractions and relaxations. Through Acknowledge software, FB-MNF is calculated and compared with the standard MNF. The results demonstrate that mean parameter of selected FB-MNF has a better linear relationship with muscle contraction compared to the others for different subjects. In addition, it has been observed through analysis of variance (ANOVA), compared to the traditional methods and have a significant difference (p<;0.05) between feature values among the MNF signal data of EMG power spectrum for different subjects. Furthermore, we have computed Mean Power (MNP), Total Power (TTP) and Peak Frequency (PKF) to determine both muscle load and muscle fatigue indices.\",\"PeriodicalId\":6490,\"journal\":{\"name\":\"2015 International Conference on Electrical & Electronic Engineering (ICEEE)\",\"volume\":\"19 1\",\"pages\":\"161-164\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 International Conference on Electrical & Electronic Engineering (ICEEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CEEE.2015.7428245\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 International Conference on Electrical & Electronic Engineering (ICEEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CEEE.2015.7428245","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Frequency based EMG power spectrum analysis of Salat associated muscle contraction
Mean frequency (MNF) based EMG power spectrum analysis is presented to determine Salat associated muscle fatigue and indices. The main complexity of the parameter is a non-linear relationship between muscle fatigue and feature value, especially in large muscle and in cyclic dynamic contraction which is solved by this proposal. By this work, we can compute frequency dependent MNF for dynamic contractions and relaxations. Through Acknowledge software, FB-MNF is calculated and compared with the standard MNF. The results demonstrate that mean parameter of selected FB-MNF has a better linear relationship with muscle contraction compared to the others for different subjects. In addition, it has been observed through analysis of variance (ANOVA), compared to the traditional methods and have a significant difference (p<;0.05) between feature values among the MNF signal data of EMG power spectrum for different subjects. Furthermore, we have computed Mean Power (MNP), Total Power (TTP) and Peak Frequency (PKF) to determine both muscle load and muscle fatigue indices.