{"title":"Nasal Breath Input: Exploring Nasal Breath Input Method for Hands-Free Input by Using a Glasses Type Device with Piezoelectric Elements","authors":"Ryoma Ogawa, Kyosuke Futami, Kazuya Murao","doi":"10.26421/jdi3.4-2","DOIUrl":null,"url":null,"abstract":"Research on hands-free input methods has been actively conducted. However, most of the previous methods are difficult to use at any time in daily life due to using speech sounds or body movements. In this study, to realize a hands-free input method based on nasal breath using wearable devices, we propose a method for recognizing nasal breath gestures, using piezoelectric elements placed on the nosepiece of a glasses-type device. In the proposed method, nasal vibrations generated by nasal breath are acquired as sound data from the devices. Next, the breath pattern is recognized based on the factors of breath count, time interval, and intensity. We implemented a prototype system. The evaluation results for 10 subjects showed that the proposed method can recognize eight types of nasal breath gestures at 0.82\\% of F-value. The evaluation results also showed that the recognition accuracy is increased to more than 90\\% by limiting gestures to those with a different breath count or different breath interval. Our study provides the first glasses type wearable sensing technology that uses nasal breathing for hands-free input.","PeriodicalId":32592,"journal":{"name":"Journal of Artificial Intelligence and Data Mining","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Artificial Intelligence and Data Mining","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.26421/jdi3.4-2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Research on hands-free input methods has been actively conducted. However, most of the previous methods are difficult to use at any time in daily life due to using speech sounds or body movements. In this study, to realize a hands-free input method based on nasal breath using wearable devices, we propose a method for recognizing nasal breath gestures, using piezoelectric elements placed on the nosepiece of a glasses-type device. In the proposed method, nasal vibrations generated by nasal breath are acquired as sound data from the devices. Next, the breath pattern is recognized based on the factors of breath count, time interval, and intensity. We implemented a prototype system. The evaluation results for 10 subjects showed that the proposed method can recognize eight types of nasal breath gestures at 0.82\% of F-value. The evaluation results also showed that the recognition accuracy is increased to more than 90\% by limiting gestures to those with a different breath count or different breath interval. Our study provides the first glasses type wearable sensing technology that uses nasal breathing for hands-free input.