Carlos Galvão Pinheiro Júnior, Marcus Fraga Vieira, C. Amorim, G. Bourhis, A. Andrade
{"title":"Facial Muscular Human-Computer Interface at a Motor Unit Level","authors":"Carlos Galvão Pinheiro Júnior, Marcus Fraga Vieira, C. Amorim, G. Bourhis, A. Andrade","doi":"10.1142/s2424922x19500086","DOIUrl":null,"url":null,"abstract":"Assistive technology allows motor-impaired people to overcome limitations. Several myoelectric interfaces have been developed, however, there is no reported study employing information at a motor unit (MU) level for controlling purposes. Thus, we developed a facial myoelectric interface operating at the level of MU for controlling a computer screen cursor. Data were collected from 11 able-bodied and 1 tetraplegic subjects. Different from traditional approaches, there was no significant difference ([Formula: see text]) in learning with respect to the level of difficulty, occurring evenly and faster. Information at MU level opens new possibilities for the development of fine control myoelectric interfaces.","PeriodicalId":47145,"journal":{"name":"Advances in Data Science and Adaptive Analysis","volume":"67 1","pages":"1950008:1-1950008:23"},"PeriodicalIF":0.5000,"publicationDate":"2019-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Data Science and Adaptive Analysis","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/s2424922x19500086","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"MATHEMATICS, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Assistive technology allows motor-impaired people to overcome limitations. Several myoelectric interfaces have been developed, however, there is no reported study employing information at a motor unit (MU) level for controlling purposes. Thus, we developed a facial myoelectric interface operating at the level of MU for controlling a computer screen cursor. Data were collected from 11 able-bodied and 1 tetraplegic subjects. Different from traditional approaches, there was no significant difference ([Formula: see text]) in learning with respect to the level of difficulty, occurring evenly and faster. Information at MU level opens new possibilities for the development of fine control myoelectric interfaces.