{"created":"2025-01-19T01:13:51.734130+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00212940","sets":["6164:6165:6640:10712"]},"path":["10712"],"owner":"44499","recid":"212940","title":["骨伝導音を用いた自動セグメンテーションによる食事行動検出手法の提案"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-06-23"},"_buckets":{"deposit":"d3f4849e-fa74-46ba-b155-1df299e86f3c"},"_deposit":{"id":"212940","pid":{"type":"depid","value":"212940","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"骨伝導音を用いた自動セグメンテーションによる食事行動検出手法の提案","author_link":["544026","544023","544025","544024"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"骨伝導音を用いた自動セグメンテーションによる食事行動検出手法の提案"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"行動認識","subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2021-06-23","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_18_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"青山学院大学"},{"subitem_text_value":"青山学院大学"},{"subitem_text_value":"青山学院大学"},{"subitem_text_value":"青山学院大学"}]},"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/212940/files/IPSJ-DICOMO2021042.pdf","label":"IPSJ-DICOMO2021042.pdf"},"date":[{"dateType":"Available","dateValue":"2023-06-23"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DICOMO2021042.pdf","filesize":[{"value":"1.5 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":"44"}],"accessrole":"open_date","version_id":"130cb271-c478-4b28-ac1a-3b3f2f51c203","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"近藤, 匠海"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"蒲地, 遥"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"横窪, 安奈"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Guillaume, Lopez"}],"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_18_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"食事中の咀嚼回数が少ないと肥満に繋がることが明らかになった．さらに，リアルタイムで咀嚼回数を食事者に提示することで，早食いを防ぎ，食事に対する意識を改善することが期待できる．また，食事行動の識別は実験環境下でしか行われていない．本研究では，自然な食事環境下での食事行動定量化による食事行動の意識改善を促すシステムを提供することを目的として，骨伝導音を利用した食事詳細行動を自動で正確にセグメントする手法の開発を行った．骨伝導マイクロフォンによって収集した食事音声データの食事詳細行動に該当する音声を抽出し，さらに本手法によって抽出された食事詳細行動の音声を分類するモデルの提案と咀嚼回数推定も行った．セグメンテーション評価では適合率は 88.1%，各クラスの再現率の平均は 70.5% となった．","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"316","bibliographic_titles":[{"bibliographic_title":"マルチメディア，分散協調とモバイルシンポジウム2021論文集"}],"bibliographicPageStart":"310","bibliographicIssueDates":{"bibliographicIssueDate":"2021-06-23","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2021"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":212940,"updated":"2025-01-19T17:19:34.311524+00:00","links":{}}