{"links":{},"id":205673,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00205673","sets":["6504:10247:10250"]},"path":["10250"],"owner":"6748","recid":"205673","title":["脳波データの圧縮を考慮したスケーラブルな電極チャネルと特徴量の組み合わせ"],"pubdate":{"attribute_name":"公開日","attribute_value":"2020-02-20"},"_buckets":{"deposit":"0a077952-53d2-4271-8057-13f4e73c52d8"},"_deposit":{"id":"205673","pid":{"type":"depid","value":"205673","revision_id":0},"owners":[6748],"status":"published","created_by":6748},"item_title":"脳波データの圧縮を考慮したスケーラブルな電極チャネルと特徴量の組み合わせ","author_link":["510489","510491","510490","510492"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"脳波データの圧縮を考慮したスケーラブルな電極チャネルと特徴量の組み合わせ"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"インタフェース","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2020-02-20","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"青学大"},{"subitem_text_value":"青学大"},{"subitem_text_value":"青学大"},{"subitem_text_value":"青学大"}]},"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/205673/files/IPSJ-Z82-1ZB-08.pdf","label":"IPSJ-Z82-1ZB-08.pdf"},"date":[{"dateType":"Available","dateValue":"2020-06-19"}],"format":"application/pdf","filename":"IPSJ-Z82-1ZB-08.pdf","filesize":[{"value":"375.3 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"bdc9a919-972b-469b-a03c-96a6bf5eb1c6","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2020 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"鶴ケ崎, 裕真"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"田邊, 俊"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"田谷, 昭仁"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"戸辺, 義人"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年、2025年問題による影響の1つの、後期高齢者の増加による患者数の増加・少子高齢化による医師不足の影響が懸念されている。これらの問題を解決するために、サーバやクラウドに脳波データを転送することで、遠隔患者に対する診断の実現が期待される。脳波データをそのまま送るとサイズが大きいなどの問題があり、データ圧縮が必要となる。また、データ圧縮をしても診断の精度が下がらないことが要求される。本論文では、要求される診断の正解率を満たす、特徴量の数と電極数の指標を作成する。具体的には、tsfreshというライブラリを使用し、電極ごとに考えられる特徴量を作成し、要求された診断率を満たすよう、特徴量削減・電極数を増減する。","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"44","bibliographic_titles":[{"bibliographic_title":"第82回全国大会講演論文集"}],"bibliographicPageStart":"43","bibliographicIssueDates":{"bibliographicIssueDate":"2020-02-20","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2020"}]},"relation_version_is_last":true,"weko_creator_id":"6748"},"created":"2025-01-19T01:07:48.446996+00:00","updated":"2025-01-19T19:41:30.454036+00:00"}