Apiwat Junlasat, Tanatawan Kamolklang, P. Uthansakul, M. Uthansakul
{"title":"基于多个肌电图位置的手指运动检测","authors":"Apiwat Junlasat, Tanatawan Kamolklang, P. Uthansakul, M. Uthansakul","doi":"10.1109/ICITEED.2019.8929980","DOIUrl":null,"url":null,"abstract":"The use of ElectroMyoGraphy (EMG) has been widely applied to many applications. To further develop more sophisticated applications, the more advanced techniques of EMG detections have to be studied. So far there are a few works to study the detection of finger movements using EMG. However, they cannot provide the exact solution of finger detection using only one EMG position. Therefore, this paper presents the finger movement detection based on multiple EMG positions. The investigation is carried out by using Myoware muscle sensors to record EMG signals. The measured EMG signals are captured and processed in a low computational processing unit. The results indicate the successful finding of finger movement detection based on multiple EMG positions.","PeriodicalId":6598,"journal":{"name":"2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"150 1","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Finger Movement Detection Based on Multiple EMG Positions\",\"authors\":\"Apiwat Junlasat, Tanatawan Kamolklang, P. Uthansakul, M. Uthansakul\",\"doi\":\"10.1109/ICITEED.2019.8929980\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The use of ElectroMyoGraphy (EMG) has been widely applied to many applications. To further develop more sophisticated applications, the more advanced techniques of EMG detections have to be studied. So far there are a few works to study the detection of finger movements using EMG. However, they cannot provide the exact solution of finger detection using only one EMG position. Therefore, this paper presents the finger movement detection based on multiple EMG positions. The investigation is carried out by using Myoware muscle sensors to record EMG signals. The measured EMG signals are captured and processed in a low computational processing unit. The results indicate the successful finding of finger movement detection based on multiple EMG positions.\",\"PeriodicalId\":6598,\"journal\":{\"name\":\"2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE)\",\"volume\":\"150 1\",\"pages\":\"1-4\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICITEED.2019.8929980\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 11th International Conference on Information Technology and Electrical Engineering (ICITEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICITEED.2019.8929980","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Finger Movement Detection Based on Multiple EMG Positions
The use of ElectroMyoGraphy (EMG) has been widely applied to many applications. To further develop more sophisticated applications, the more advanced techniques of EMG detections have to be studied. So far there are a few works to study the detection of finger movements using EMG. However, they cannot provide the exact solution of finger detection using only one EMG position. Therefore, this paper presents the finger movement detection based on multiple EMG positions. The investigation is carried out by using Myoware muscle sensors to record EMG signals. The measured EMG signals are captured and processed in a low computational processing unit. The results indicate the successful finding of finger movement detection based on multiple EMG positions.