{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00219698","sets":["6164:6165:6640:11008"]},"path":["11008"],"owner":"44499","recid":"219698","title":["脈拍変動を用いた暑熱快適快適性予測"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-07-06"},"_buckets":{"deposit":"8c2674c3-6a19-43e5-aba3-d070540ebec2"},"_deposit":{"id":"219698","pid":{"type":"depid","value":"219698","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"脈拍変動を用いた暑熱快適快適性予測","author_link":["573285","573284","573286","573282","573283"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"脈拍変動を用いた暑熱快適快適性予測"}]},"item_type_id":"18","publish_date":"2022-07-06","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"},{"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/219698/files/IPSJ-DICOMO2022124.pdf","label":"IPSJ-DICOMO2022124.pdf"},"date":[{"dateType":"Available","dateValue":"2024-07-06"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DICOMO2022124.pdf","filesize":[{"value":"1.0 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":"085e0089-ae4a-455e-957e-aeedb25d7756","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"ホサイン, タヘラ"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"川崎, 勇佑"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"本多, 一騎"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"横窪, 安奈"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"ロペズ, ギヨーム"}],"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":"熱的快適性とは，日常生活における人間の幸福や安全性，生産性に極めて重要な熱環境に満足している状態のことである．室内環境における熱的快適性は，様々な状況下，様々な活動を行うことで変動する．このような快適性の指標を理解可能なシステムは，人間の健康補助に役立つ．この論文では，自律神経系の活動データを収集するための様々なセンサを搭載した腕時計型のデバイスを想定する．本研究では，脈拍変動 (PRV)に基づく生理学的に調節された熱的快適性について，熱中症のリスクなどを予測できるかどうか，予備的な評価を行うものである．そこで，高温の熱環境に着目し，読書，転写，ラジオ体操という異なる作業条件下で温度と湿度を変化させデータを収集し，複数の機械学習を用いて人間の環境熱的快適性を予測することに重点を置いた．その結果，5 種類の機械学習モデルで平均 95% 以上の精度を示した．","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"892","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2022論文集"}],"bibliographicPageStart":"888","bibliographicIssueDates":{"bibliographicIssueDate":"2022-07-06","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2022"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":219698,"updated":"2025-01-19T14:48:26.629240+00:00","links":{},"created":"2025-01-19T01:19:45.765249+00:00"}