Jetsada Arnil, D. Anopas, M. Horapong, K. Luangrat, Yunyong Punsawad, Y. W. Ongsawat
{"title":"基于bci的辅助机械臂","authors":"Jetsada Arnil, D. Anopas, M. Horapong, K. Luangrat, Yunyong Punsawad, Y. W. Ongsawat","doi":"10.1109/ISMICT.2013.6521730","DOIUrl":null,"url":null,"abstract":"People who lost their limbs by injury or congenital missing need prosthesis to replace the missing body part to assist or enhance the motor ability or for cosmetic purpose. In this paper, brain-computer interface (BCI) technology is proposed to assist the person with disability who has no arm. The proposed system includes two BCI algorithms, i.e. ERD/ERS algorithm and hybrid EEG-EOG algorithm. The designed assistive robot arm is light weight, low power consumption, user friendly and pleasing aesthetic. The ERD/ERS algorithm can achieve the accuracy of approximately 66% with 3 commands. Moreover, the accuracy of the hybrid EEG-EOG algorithm yields nearly 96%.","PeriodicalId":387991,"journal":{"name":"2013 7th International Symposium on Medical Information and Communication Technology (ISMICT)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2013-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Bci-based assistive robot arm\",\"authors\":\"Jetsada Arnil, D. Anopas, M. Horapong, K. Luangrat, Yunyong Punsawad, Y. W. Ongsawat\",\"doi\":\"10.1109/ISMICT.2013.6521730\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"People who lost their limbs by injury or congenital missing need prosthesis to replace the missing body part to assist or enhance the motor ability or for cosmetic purpose. In this paper, brain-computer interface (BCI) technology is proposed to assist the person with disability who has no arm. The proposed system includes two BCI algorithms, i.e. ERD/ERS algorithm and hybrid EEG-EOG algorithm. The designed assistive robot arm is light weight, low power consumption, user friendly and pleasing aesthetic. The ERD/ERS algorithm can achieve the accuracy of approximately 66% with 3 commands. Moreover, the accuracy of the hybrid EEG-EOG algorithm yields nearly 96%.\",\"PeriodicalId\":387991,\"journal\":{\"name\":\"2013 7th International Symposium on Medical Information and Communication Technology (ISMICT)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 7th International Symposium on Medical Information and Communication Technology (ISMICT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISMICT.2013.6521730\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 7th International Symposium on Medical Information and Communication Technology (ISMICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISMICT.2013.6521730","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
People who lost their limbs by injury or congenital missing need prosthesis to replace the missing body part to assist or enhance the motor ability or for cosmetic purpose. In this paper, brain-computer interface (BCI) technology is proposed to assist the person with disability who has no arm. The proposed system includes two BCI algorithms, i.e. ERD/ERS algorithm and hybrid EEG-EOG algorithm. The designed assistive robot arm is light weight, low power consumption, user friendly and pleasing aesthetic. The ERD/ERS algorithm can achieve the accuracy of approximately 66% with 3 commands. Moreover, the accuracy of the hybrid EEG-EOG algorithm yields nearly 96%.
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