Yanbin Xu, Chenguang Yang, P. Liang, Lijun Zhao, Zhijun Li
{"title":"Development of a hybrid motion capture method using MYO armband with application to teleoperation","authors":"Yanbin Xu, Chenguang Yang, P. Liang, Lijun Zhao, Zhijun Li","doi":"10.1109/ICMA.2016.7558729","DOIUrl":null,"url":null,"abstract":"In this paper, we have developed a motion capture method based on data collected by MYO armband. The method can be applied on any healthy operator wearing two MYO armbands on both upper and lower arms, respectively. The first MYO armband is worn near the centre of the operator's upper arm, the other is worn near the centre of the forearm. MYO armband has built-in eight bioelectrical sensors as well as a 9-axis IMU. The IMU sensors of the MYO are used to detect and reconstruct physical motion of shoulder and elbow joints, while the bioelectrical sensors are used to collect electromyography (EMG) signals associated with wrist motion. This hybrid method enable us to fully capture the motion of the 6-DOF (degree of freedom) of the arm. To test the proposed method, hardware-in-loop simulations studies are performed, with both physiological and physical signals received and processed in MATLAB/Simulink via a low-power bluetooth interface. Results demonstrate the validness and effectiveness of the proposed method.","PeriodicalId":260197,"journal":{"name":"2016 IEEE International Conference on Mechatronics and Automation","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"32","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Mechatronics and Automation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMA.2016.7558729","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 32
Abstract
In this paper, we have developed a motion capture method based on data collected by MYO armband. The method can be applied on any healthy operator wearing two MYO armbands on both upper and lower arms, respectively. The first MYO armband is worn near the centre of the operator's upper arm, the other is worn near the centre of the forearm. MYO armband has built-in eight bioelectrical sensors as well as a 9-axis IMU. The IMU sensors of the MYO are used to detect and reconstruct physical motion of shoulder and elbow joints, while the bioelectrical sensors are used to collect electromyography (EMG) signals associated with wrist motion. This hybrid method enable us to fully capture the motion of the 6-DOF (degree of freedom) of the arm. To test the proposed method, hardware-in-loop simulations studies are performed, with both physiological and physical signals received and processed in MATLAB/Simulink via a low-power bluetooth interface. Results demonstrate the validness and effectiveness of the proposed method.