{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00181963","sets":["1164:3865:9090:9156"]},"path":["9156"],"owner":"11","recid":"181963","title":["Stacked convolutional denoising autoencodersを用いた2誘導心電図からの特徴抽出および不整脈分類"],"pubdate":{"attribute_name":"公開日","attribute_value":"2017-05-25"},"_buckets":{"deposit":"e1c691f9-7efc-48a6-9ec9-ae2ac16619d7"},"_deposit":{"id":"181963","pid":{"type":"depid","value":"181963","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"Stacked convolutional denoising autoencodersを用いた2誘導心電図からの特徴抽出および不整脈分類","author_link":["394947","394945","394948","394950","394946","394949"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Stacked convolutional denoising autoencodersを用いた2誘導心電図からの特徴抽出および不整脈分類"},{"subitem_title":"Feature extraction and arrhythmia classification from 2-lead ECG using stacked convolutional denoising autoencoders","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"センサネットワーク","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2017-05-25","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"NTTドコモ"},{"subitem_text_value":"NTTドコモ"},{"subitem_text_value":"NTTドコモ"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"NTT DOCOMO, INC.","subitem_text_language":"en"},{"subitem_text_value":"NTT DOCOMO, INC.","subitem_text_language":"en"},{"subitem_text_value":"NTT DOCOMO, INC.","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/181963/files/IPSJ-MBL17083025.pdf","label":"IPSJ-MBL17083025.pdf"},"date":[{"dateType":"Available","dateValue":"2019-05-25"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MBL17083025.pdf","filesize":[{"value":"955.2 kB"}],"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":"26abf6a3-1533-4ba6-8fc1-052a621f2f59","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2017 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"高橋, 柊"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"落合, 桂一"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"深澤, 佑介"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Shu, Takahashi","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Keiichi, Ochiai","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yusuke, Fukazawa","creatorNameLang":"en"}],"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，さまざまなモノおよびコトをインターネットに接続することで，ログ収集および相互制御を行う Internet of Things (IoT) に注目が集まっている．IoT の活用により，今までセンシングが困難であった情報がリアルタイムに取得可能となることが期待されている．心電図 (ECG) をリアルタイムに解析することができれば，IoT デバイスの活用によりリアルタイムに不整脈などを検出することが可能となる．本研究では，Stacked Convolutional Denoising Autoencoders (SCDAE) を用いた，ECG 波形からの高レベルな特徴抽出について検討する．また，事前学習した SCDAE の構造および重みを抽出し，全結合層を追加した分類器を再学習する不整脈分類手法を提案する．未知の ECG 波形からの不整脈分類において，提案手法が既存手法 (Accuracy : 92.7%) に対し高精度 (Accuracy : 95.1%) であることを示す．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告モバイルコンピューティングとパーベイシブシステム（MBL）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2017-05-25","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"25","bibliographicVolumeNumber":"2017-MBL-83"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"updated":"2025-01-20T04:15:33.953047+00:00","created":"2025-01-19T00:49:39.815211+00:00","links":{},"id":181963}