{"title":"基于肌电信号模糊推理的人体前臂运动识别","authors":"A. Kiso, H. Seki","doi":"10.1109/ICORR.2009.5209587","DOIUrl":null,"url":null,"abstract":"This paper describes a human forearm motion discrimination method based on the myoelectric signal by the fuzzy inference. In the conventional studies, the neural network is often used to estimate motion intention by the myoelectric signal and realizes the high discrimination precision. On the other hand, this study uses the fuzzy inference for a human forearm motion discrimination based on the myoelectric signal. This study designs the membership function and the fuzzy rules from the average value and the standard deviation of the root mean square of the myoelectric potential for every channel of each motion. Some experiments on the myoelectric hand simulator show the effectiveness of the proposed motion discrimination method.","PeriodicalId":189213,"journal":{"name":"2009 IEEE International Conference on Rehabilitation Robotics","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Human forearm motion discrimination based on myoelectric signal by fuzzy inference\",\"authors\":\"A. Kiso, H. Seki\",\"doi\":\"10.1109/ICORR.2009.5209587\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes a human forearm motion discrimination method based on the myoelectric signal by the fuzzy inference. In the conventional studies, the neural network is often used to estimate motion intention by the myoelectric signal and realizes the high discrimination precision. On the other hand, this study uses the fuzzy inference for a human forearm motion discrimination based on the myoelectric signal. This study designs the membership function and the fuzzy rules from the average value and the standard deviation of the root mean square of the myoelectric potential for every channel of each motion. Some experiments on the myoelectric hand simulator show the effectiveness of the proposed motion discrimination method.\",\"PeriodicalId\":189213,\"journal\":{\"name\":\"2009 IEEE International Conference on Rehabilitation Robotics\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 IEEE International Conference on Rehabilitation Robotics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICORR.2009.5209587\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Rehabilitation Robotics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICORR.2009.5209587","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Human forearm motion discrimination based on myoelectric signal by fuzzy inference
This paper describes a human forearm motion discrimination method based on the myoelectric signal by the fuzzy inference. In the conventional studies, the neural network is often used to estimate motion intention by the myoelectric signal and realizes the high discrimination precision. On the other hand, this study uses the fuzzy inference for a human forearm motion discrimination based on the myoelectric signal. This study designs the membership function and the fuzzy rules from the average value and the standard deviation of the root mean square of the myoelectric potential for every channel of each motion. Some experiments on the myoelectric hand simulator show the effectiveness of the proposed motion discrimination method.