{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00212426","sets":["1164:3865:10488:10659"]},"path":["10659"],"owner":"44499","recid":"212426","title":["脳波・心拍変動解析による機械学習を用いたヒューマンエラーの予測手法の提案"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-08-26"},"_buckets":{"deposit":"2aa595c6-2850-4b21-ac2f-1529ddd8bd58"},"_deposit":{"id":"212426","pid":{"type":"depid","value":"212426","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"脳波・心拍変動解析による機械学習を用いたヒューマンエラーの予測手法の提案","author_link":["541862","541860","541863","541861"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"脳波・心拍変動解析による機械学習を用いたヒューマンエラーの予測手法の提案"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"分析・予測","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2021-08-26","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"芝浦工業大学"},{"subitem_text_value":"(株)日立製作所"},{"subitem_text_value":"芝浦工業大学"},{"subitem_text_value":"芝浦工業大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Shibaura Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Hitachi Ltd.","subitem_text_language":"en"},{"subitem_text_value":"Shibaura Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Shibaura Institute of Technology","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/212426/files/IPSJ-MBL21100007.pdf","label":"IPSJ-MBL21100007.pdf"},"date":[{"dateType":"Available","dateValue":"2023-08-26"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MBL21100007.pdf","filesize":[{"value":"2.1 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"35"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"3a7324d3-0db6-4b3d-983b-5df244a5fae7","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"齋藤, 勇斗"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"高田, 尚子"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Muhammad, Nur Adilin Bin Mohd Anuardi"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"菅谷, みどり"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11851388","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8817","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年，ヒューマンエラーによる労働災害が増加している．ヒューマンエラーの精神的状態の分析では，生体情報を用いた手法が様々提案されている．しかし，精神状態を生体情報で計測し，その結果に基づき正確な予測を行う研究はまだ十分ではない．本研究では，無意識的な精神状態として脳波・心拍で計測し，また疲労やストレス値をアンケートで補う事で，エラーの予測モデルの構築およびリアルタイム予測を行う事を目的とする．実験では，協力者に数日に渡りストループ課題を実施してもらい，その際に得られた脳波・心拍とアンケート結果を用いて，個人ごとのエラーの予測モデルを提案した．結果として，脳波・心拍とアンケート結果の一部指標において，エラーに関係するという事が得られ，これをエラーの予測モデルに組み込んだ．さらに，エラーの予測をリアルタイムで行い，ヒューマンエラーを未然に防止する事ができるかどうかを検証した．結果として，エラーと予測された際，74％ でエラーの発生が確認された．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"10","bibliographic_titles":[{"bibliographic_title":"研究報告モバイルコンピューティングと新社会システム（MBL）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2021-08-26","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"7","bibliographicVolumeNumber":"2021-MBL-100"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":212426,"updated":"2025-01-19T17:31:30.857054+00:00","links":{},"created":"2025-01-19T01:13:22.351513+00:00"}