{"created":"2023-08-02T03:58:02.915836+00:00","id":7177,"links":{},"metadata":{"_buckets":{"deposit":"5af3e430-1872-4b7b-b1c3-b0cc0221974f"},"_deposit":{"created_by":10,"id":"7177","owners":[10],"pid":{"revision_id":0,"type":"depid","value":"7177"},"status":"published"},"_oai":{"id":"oai:repository.lib.tottori-u.ac.jp:00007177","sets":["1:10","2:12"]},"author_link":["2512","26564","26565"],"item_10001_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2020","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"9","bibliographic_titles":[{"bibliographic_title":"Electronics"},{"bibliographic_title":"Electronics","bibliographic_titleLang":"en"}]}]},"item_10001_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Biometrics such as fingerprints and iris scans has been used in authentication. However, conventional biometrics is vulnerable to identity theft, especially in user-management systems. As a new biometrics without this vulnerability, brain waves have been a focus. In this paper, brain waves (electroencephalograms (EEGs)) were measured from ten experiment subjects. Individual features were extracted from the log power spectra of the EEGs using principal component analysis, and verification was achieved using a support vector machine. It was found that, for the proposed authentication method, the equal error rate (EER) for a single electrode was about 22–32%, and that, for a multiple electrodes, was 4.4% by using the majority decision rule. Furthermore, nonlinear features based on chaos analysis were introduced for feature extraction and then extended to multidimensional ones. By fusing the results of all electrodes when using the proposed multidimensional nonlinear features and the spectral feature, an EER of 0% was achieved. As a result, it was confirmed that individuals can be authenticated using induced brain waves when they are subjected to ultrasounds.","subitem_description_type":"Other"}]},"item_10001_publisher_8":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"MDPI"}]},"item_10001_relation_14":{"attribute_name":"DOI","attribute_value_mlt":[{"subitem_relation_type":"isVersionOf","subitem_relation_type_id":{"subitem_relation_type_id_text":"10.3390/electronics9010024","subitem_relation_type_select":"DOI"}}]},"item_10001_relation_16":{"attribute_name":"情報源","attribute_value_mlt":[{"subitem_relation_name":[{"subitem_relation_name_text":"Isao Nakanishi, Takehiro Maruoka. Biometrics Using Electroencephalograms Stimulated by Personal Ultrasound and Multidimensional Nonlinear Features. Electronics. 2020, 9, 24."}]}]},"item_10001_rights_15":{"attribute_name":"権利","attribute_value_mlt":[{"subitem_rights":"©2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open accessarticle distributed under the terms and conditions of the Creative Commons Attribution(CC BY) license (http://creativecommons.org/licenses/by/4.0/)."}]},"item_10001_source_id_9":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"20799292","subitem_source_identifier_type":"ISSN"}]},"item_10001_text_33":{"attribute_name":"著者所属（英）","attribute_value_mlt":[{"subitem_text_language":"en","subitem_text_value":"Faculty of Engineering, Tottori University"},{"subitem_text_language":"en","subitem_text_value":"Graduate School of Sustainability Sciences, Tottori University"}]},"item_10001_version_type_20":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_type":"AM"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Nakanishi, Isao"},{"creatorName":"ナカニシ, イサオ","creatorNameLang":"ja-Kana"},{"creatorName":"Nakanishi, Isao","creatorNameLang":"en"}],"nameIdentifiers":[{},{},{}]},{"creatorNames":[{"creatorName":"Maruoka, Takehiro"},{"creatorName":"マルオカ, タケヒロ","creatorNameLang":"ja-Kana"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Maruoka, Takehiro","creatorNameLang":"en"},{"creatorName":"マルオカ, タケヒロ","creatorNameLang":"ja-Kana"}],"nameIdentifiers":[{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2023-03-17"}],"displaytype":"detail","filename":"Electronics_24.pdf","filesize":[{"value":"1.4 MB"}],"format":"application/pdf","licensefree":"©2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open accessarticle distributed under the terms and conditions of the Creative Commons Attribution(CC BY) license (http://creativecommons.org/licenses/by/4.0/).","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"Electronics_24.pdf","url":"https://repository.lib.tottori-u.ac.jp/record/7177/files/Electronics_24.pdf"},"version_id":"06ad9c73-e70e-4ec5-806c-e4a603532222"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"biometrics","subitem_subject_scheme":"Other"},{"subitem_subject":"brain wave","subitem_subject_scheme":"Other"},{"subitem_subject":"EEG","subitem_subject_scheme":"Other"},{"subitem_subject":"ultrasound","subitem_subject_scheme":"Other"},{"subitem_subject":"evoked potential","subitem_subject_scheme":"Other"},{"subitem_subject":"multidimensional nonlinear feature","subitem_subject_scheme":"Other"},{"subitem_subject":"biometrics","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"brain wave","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"EEG","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"ultrasound","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"evoked potential","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"multidimensional nonlinear feature","subitem_subject_language":"en","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"journal article"}]},"item_title":"Biometrics Using Electroencephalograms Stimulated by Personal Ultrasound and Multidimensional Nonlinear Features","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Biometrics Using Electroencephalograms Stimulated by Personal Ultrasound and Multidimensional Nonlinear Features","subitem_title_language":"en"}]},"item_type_id":"10001","owner":"10","path":["12","10"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2020-06-05"},"publish_date":"2020-06-05","publish_status":"0","recid":"7177","relation_version_is_last":true,"title":["Biometrics Using Electroencephalograms Stimulated by Personal Ultrasound and Multidimensional Nonlinear Features"],"weko_creator_id":"10","weko_shared_id":-1},"updated":"2023-09-29T00:37:40.437899+00:00"}