{"created":"2024-12-12T01:08:50.396088+00:00","id":2009008,"links":{},"metadata":{"_buckets":{"deposit":"3fb80103-8d72-4095-9599-157a17da440b"},"_deposit":{"created_by":7,"id":"2009008","owners":[7],"pid":{"revision_id":0,"type":"depid","value":"2009008"},"status":"published"},"_oai":{"id":"oai:tokushima-u.repo.nii.ac.jp:02009008","sets":["1713853213384:1713853295607"]},"author_link":["373","421","96"],"control_number":"2009008","item_10001_alternative_title_1":{"attribute_name":"タイトル別表記","attribute_value_mlt":[{"subitem_alternative_title":"Human-Wants Detection Based on Electroencephalogram Analysis","subitem_alternative_title_language":"en"}]},"item_10001_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2020-08-20","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"4","bibliographicPageEnd":"730","bibliographicPageStart":"724","bibliographicVolumeNumber":"32","bibliographic_titles":[{"bibliographic_title":"Journal of Robotics and Mechatronics","bibliographic_titleLang":"en"}]}]},"item_10001_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"We propose a method to detect human wants by using an electroencephalogram (EEG) test and specifying brain activity sensing positions. EEG signals can be analyzed by using various techniques. Recently, convolutional neural networks (CNNs) have been employed to analyze EEG signals, and these analyses have produced excellent results. Therefore, this paper employs CNN to extract EEG features. Also, support vector machines (SVMs) have shown good results for EEG pattern classification. This paper employs SVMs to classify the human cognition into “wants,” “not wants,” and “other feelings”. In EEG measurements, the electrical activity of the brain is recorded using electrodes placed on the scalp. The sensing positions are related to the frontal cortex and/or temporal cortex activities although the mechanism to create wants is not clear. To specify the sensing positions and detect human wants, we conducted experiments using real EEG data. We confirmed that the mean and standard deviation values of the detection accuracy rate were 99.4% and 0.58, respectively, when the target sensing positions were related to the frontal and temporal cortex activities. These results prove that both the frontal and temporal cortex activities are relevant for creating wants in the human brain, and that CNN and SVM are effective for the detection of human wants.","subitem_description_language":"en","subitem_description_type":"Abstract"}]},"item_10001_publisher_8":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"Fuji Technology Press","subitem_publisher_language":"en"}]},"item_10001_rights_15":{"attribute_name":"権利情報","attribute_value_mlt":[{"subitem_rights":"This is an Open Access article distributed under the terms of the Creative Commons Attribution-NoDerivatives 4.0 International License (http://creativecommons.org/licenses/by-nd/4.0/).","subitem_rights_language":"en"}]},"item_10001_source_id_9":{"attribute_name":"収録物ID","attribute_value_mlt":[{"subitem_source_identifier":"09153942","subitem_source_identifier_type":"ISSN"},{"subitem_source_identifier":"18838049","subitem_source_identifier_type":"ISSN"},{"subitem_source_identifier":"AA10809998","subitem_source_identifier_type":"NCID"}]},"item_10001_version_type_20":{"attribute_name":"出版タイプ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_1715043197608":{"attribute_name":"アクセス権","attribute_value_mlt":[{"subitem_access_right":"open 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detection","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"electroencephalogram","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"listening to music","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"convolutional neural networks","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"support vector machine","subitem_subject_language":"en","subitem_subject_scheme":"Other"},{"subitem_subject":"brain computer interface","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","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"Human-Wants Detection Based on Electroencephalogram Analysis During Exposure to 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