{"title":"Velocity and acceleration induced response to bicep EMG signal threshold for motion intention detection","authors":"Armyn C. Sy, N. Bugtai","doi":"10.1109/HNICEM.2014.7016198","DOIUrl":null,"url":null,"abstract":"A key factor in robotic-based physical rehabilitation is providing robotic assistance only when the subjects exert muscular effort and that movement intention does not translate into an actual physical movement. Thus, an accurate motion intention detection system plays an important role. This study focuses on the use of Electromyography signals (EMG) in detecting motion intention. Since this type of signals can be affected by factors including movement velocity and movement acceleration, it is therefore the objective of this research to determine how various levels of movement velocities, and acceleration would affect EMG signal amplitudes. Eight healthy subjects performed bicep curl movements at three different velocities with at least thirty movement repetitions each. The results were summarized, processed, and statistically analysed in order to show the relationship between the above stated factors and the dependent variable EMG.","PeriodicalId":309548,"journal":{"name":"2014 International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HNICEM.2014.7016198","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
A key factor in robotic-based physical rehabilitation is providing robotic assistance only when the subjects exert muscular effort and that movement intention does not translate into an actual physical movement. Thus, an accurate motion intention detection system plays an important role. This study focuses on the use of Electromyography signals (EMG) in detecting motion intention. Since this type of signals can be affected by factors including movement velocity and movement acceleration, it is therefore the objective of this research to determine how various levels of movement velocities, and acceleration would affect EMG signal amplitudes. Eight healthy subjects performed bicep curl movements at three different velocities with at least thirty movement repetitions each. The results were summarized, processed, and statistically analysed in order to show the relationship between the above stated factors and the dependent variable EMG.