{"title":"Sensor-embedded teeth for oral activity recognition","authors":"Cheng-Yuan Li, Yen-Chang Chen, Wei-Ju Chen, Polly Huang, Hao-Hua Chu","doi":"10.1145/2493988.2494352","DOIUrl":null,"url":null,"abstract":"This paper presents the design and implementation of a wearable oral sensory system that recognizes human oral activities, such as chewing, drinking, speaking, and coughing. We conducted an evaluation of this oral sensory system in a laboratory experiment involving 8 participants. The results show 93.8% oral activity recognition accuracy when using a person-dependent classifier and 59.8% accuracy when using a person-independent classifier.","PeriodicalId":90988,"journal":{"name":"The semantic Web--ISWC ... : ... International Semantic Web Conference ... proceedings. International Semantic Web Conference","volume":"7 1","pages":"41-44"},"PeriodicalIF":0.0000,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"47","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The semantic Web--ISWC ... : ... International Semantic Web Conference ... proceedings. International Semantic Web Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2493988.2494352","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 47
Abstract
This paper presents the design and implementation of a wearable oral sensory system that recognizes human oral activities, such as chewing, drinking, speaking, and coughing. We conducted an evaluation of this oral sensory system in a laboratory experiment involving 8 participants. The results show 93.8% oral activity recognition accuracy when using a person-dependent classifier and 59.8% accuracy when using a person-independent classifier.