D. Sueaseenak, Thunchanok Uburi, Paphawarin Tirasuwannarat
{"title":"Optimal Placement of Multi-Channels sEMG Electrod for Finger Movement Classification","authors":"D. Sueaseenak, Thunchanok Uburi, Paphawarin Tirasuwannarat","doi":"10.1145/3168776.3168802","DOIUrl":null,"url":null,"abstract":"This research aims to propose the optimal electrode positions for surface EMG by using a modern gesture control device called MYO armband. Seven healthy volunteers participated in this research. The sEMG signal was collected form three different electrode positions in the superficial forearm muscles positions such as Extenser digitorum muscle, Flexor digitorum superficialis muscle, Palmaris longus muscle during finger movements 5 gesture including flexion thumb, index, middle, ring and little. Waveform length (WL) is a feature extraction method, EMG features were represented in scatter diagrams to explain their behaviors. The well-known quantitative parameters used to evaluate the performance of EMG feature included scattering criterion. The result showed optimal position to obtain the best quality surface EMG recording by MYO armband for finger movement classification. The position is a middle of forearm length area.","PeriodicalId":253305,"journal":{"name":"Proceedings of the 2017 4th International Conference on Biomedical and Bioinformatics Engineering","volume":"423 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2017 4th International Conference on Biomedical and Bioinformatics Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3168776.3168802","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
This research aims to propose the optimal electrode positions for surface EMG by using a modern gesture control device called MYO armband. Seven healthy volunteers participated in this research. The sEMG signal was collected form three different electrode positions in the superficial forearm muscles positions such as Extenser digitorum muscle, Flexor digitorum superficialis muscle, Palmaris longus muscle during finger movements 5 gesture including flexion thumb, index, middle, ring and little. Waveform length (WL) is a feature extraction method, EMG features were represented in scatter diagrams to explain their behaviors. The well-known quantitative parameters used to evaluate the performance of EMG feature included scattering criterion. The result showed optimal position to obtain the best quality surface EMG recording by MYO armband for finger movement classification. The position is a middle of forearm length area.