{"created":"2025-01-19T01:30:11.105377+00:00","updated":"2025-01-19T11:09:10.384649+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00230426","sets":["6504:11436:11441"]},"path":["11441"],"owner":"44499","recid":"230426","title":["インソール型歩容センサを用いた疲労推定方法の検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-16"},"_buckets":{"deposit":"7169a000-db0b-4496-b5b7-2d1dc04e4ae3"},"_deposit":{"id":"230426","pid":{"type":"depid","value":"230426","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"インソール型歩容センサを用いた疲労推定方法の検討","author_link":["620795","620797","620798","620796"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"インソール型歩容センサを用いた疲労推定方法の検討"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ネットワーク","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2023-02-16","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":"金沢工大"},{"subitem_text_value":"金沢工大"},{"subitem_text_value":"金沢工大"},{"subitem_text_value":"金沢工大"}]},"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/230426/files/IPSJ-Z85-4ZB-08.pdf","label":"IPSJ-Z85-4ZB-08.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-17"}],"format":"application/pdf","filename":"IPSJ-Z85-4ZB-08.pdf","filesize":[{"value":"549.5 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"1b5d4f19-3a95-488d-accf-691e805be537","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"深町, 京佑"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"成田, 力哉"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"佐藤, 進"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"河並, 崇"}],"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，健康寿命の延伸を目的に身体活動量の増加が推進されている．しかし，活動量の増加に伴い疲労が蓄積し，歩行時に足が上がりづらいなどの理由から，転倒の恐れが高くなると考えられる．本研究では，インソール型歩容センサを用いて通常時と疲労時の歩容データを計測し，歩容データから歩行者の疲労を機械学習により推定できるか検討した． 歩容データには，通常時に計測したデータと100㎞歩行後またはフルマラソン後に計測したデータを用いた．歩行者の主観的疲労度はVASを用いて評価し，5未満を通常，5以上を疲労と定めた．歩行者の疲労推定では，複数の機械学習モデルを作成し，疲労推定の精度をもとに評価した．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"320","bibliographic_titles":[{"bibliographic_title":"第85回全国大会講演論文集"}],"bibliographicPageStart":"319","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":230426,"links":{}}