{"title":"基于多通道单元件超声换能器的人机界面初步研究","authors":"Yuefeng Li, Keshi He, Xueli Sun, Honghai Liu","doi":"10.1109/HealthCom.2016.7749483","DOIUrl":null,"url":null,"abstract":"Ultrasound (US) imaging is a promising sensing technique in the field of human-machine interface, and many positive results have been reported in literature on hand gesture recognition or finger angle prediction based on US imaging. However, in most of these studies, linear array ultrasound probes were used to generate US images, which made the US device expensive and bulky. In this paper, a method of extracting forearm muscle information via multiple single-element US transducers is proposed. By using this kind of transducers, a low-cost and small-size human-machine interface can be expected. Preliminary results show that an average recognition accuracy of 96% can be achieved for six motions, including five finger flexions and rest state.","PeriodicalId":167022,"journal":{"name":"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":"{\"title\":\"Human-machine interface based on multi-channel single-element ultrasound transducers: A preliminary study\",\"authors\":\"Yuefeng Li, Keshi He, Xueli Sun, Honghai Liu\",\"doi\":\"10.1109/HealthCom.2016.7749483\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Ultrasound (US) imaging is a promising sensing technique in the field of human-machine interface, and many positive results have been reported in literature on hand gesture recognition or finger angle prediction based on US imaging. However, in most of these studies, linear array ultrasound probes were used to generate US images, which made the US device expensive and bulky. In this paper, a method of extracting forearm muscle information via multiple single-element US transducers is proposed. By using this kind of transducers, a low-cost and small-size human-machine interface can be expected. Preliminary results show that an average recognition accuracy of 96% can be achieved for six motions, including five finger flexions and rest state.\",\"PeriodicalId\":167022,\"journal\":{\"name\":\"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"26\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HealthCom.2016.7749483\",\"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 18th International Conference on e-Health Networking, Applications and Services (Healthcom)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HealthCom.2016.7749483","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Human-machine interface based on multi-channel single-element ultrasound transducers: A preliminary study
Ultrasound (US) imaging is a promising sensing technique in the field of human-machine interface, and many positive results have been reported in literature on hand gesture recognition or finger angle prediction based on US imaging. However, in most of these studies, linear array ultrasound probes were used to generate US images, which made the US device expensive and bulky. In this paper, a method of extracting forearm muscle information via multiple single-element US transducers is proposed. By using this kind of transducers, a low-cost and small-size human-machine interface can be expected. Preliminary results show that an average recognition accuracy of 96% can be achieved for six motions, including five finger flexions and rest state.