{"title":"使用Emotiv EPOC耳机控制机械臂的低复杂度方法","authors":"S. Aguiar, Wilson Yánez, D. Benítez","doi":"10.1109/ROPEC.2016.7830526","DOIUrl":null,"url":null,"abstract":"A relative simple approach based on the computation of the area of a parametric curve produced by the 2D space representation of a set of parametric experimental functions defined by the signals of only two active EEG electrodes of a low cost neuroheadset (Emotiv EPOC) is proposed on this paper for the fast recognition of eye winks activity as control commands. This approach together with the use of the signals from the gyroscope available in the EPOC device, allowed the development of a Head-Computer Interface that enables complete interaction with a robotic arm. The results obtained indicate that the proposed approach is effective for detecting the eye-wink commands with a good rate of accuracy (over 93%).","PeriodicalId":166098,"journal":{"name":"2016 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Low complexity approach for controlling a robotic arm using the Emotiv EPOC headset\",\"authors\":\"S. Aguiar, Wilson Yánez, D. Benítez\",\"doi\":\"10.1109/ROPEC.2016.7830526\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A relative simple approach based on the computation of the area of a parametric curve produced by the 2D space representation of a set of parametric experimental functions defined by the signals of only two active EEG electrodes of a low cost neuroheadset (Emotiv EPOC) is proposed on this paper for the fast recognition of eye winks activity as control commands. This approach together with the use of the signals from the gyroscope available in the EPOC device, allowed the development of a Head-Computer Interface that enables complete interaction with a robotic arm. The results obtained indicate that the proposed approach is effective for detecting the eye-wink commands with a good rate of accuracy (over 93%).\",\"PeriodicalId\":166098,\"journal\":{\"name\":\"2016 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ROPEC.2016.7830526\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ROPEC.2016.7830526","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Low complexity approach for controlling a robotic arm using the Emotiv EPOC headset
A relative simple approach based on the computation of the area of a parametric curve produced by the 2D space representation of a set of parametric experimental functions defined by the signals of only two active EEG electrodes of a low cost neuroheadset (Emotiv EPOC) is proposed on this paper for the fast recognition of eye winks activity as control commands. This approach together with the use of the signals from the gyroscope available in the EPOC device, allowed the development of a Head-Computer Interface that enables complete interaction with a robotic arm. The results obtained indicate that the proposed approach is effective for detecting the eye-wink commands with a good rate of accuracy (over 93%).