{"created":"2023-06-20T14:06:33.757310+00:00","id":35,"links":{},"metadata":{"_buckets":{"deposit":"02ce73f8-48af-43ec-98e9-71712c3da477"},"_deposit":{"created_by":2,"id":"35","owners":[2],"pid":{"revision_id":0,"type":"depid","value":"35"},"status":"published"},"_oai":{"id":"oai:maebashi-it.repo.nii.ac.jp:00000035","sets":["6:7"]},"author_link":["147","148","149"],"item_2_biblio_info_6":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2017-06-30","bibliographicIssueDateType":"Issued"},"bibliographic_titles":[{}]}]},"item_2_date_granted_63":{"attribute_name":"学位授与年月日","attribute_value_mlt":[{"subitem_dategranted":"2017-03-24"}]},"item_2_degree_grantor_61":{"attribute_name":"学位授与機関","attribute_value_mlt":[{"subitem_degreegrantor":[{"subitem_degreegrantor_name":"前橋工科大学"}],"subitem_degreegrantor_identifier":[{}]}]},"item_2_degree_name_60":{"attribute_name":"学位名","attribute_value_mlt":[{"subitem_degreename":"博士(工学)"}]},"item_2_description_39":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"subitem_description":"Thesis or Dissertation","subitem_description_type":"Other"}]},"item_2_description_4":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"近年、人の脳情報を活用したBrain Machine Interface （BMI）によるロボット操作技術の研究が進められている。本研究では、筋電の代わりに脳波から関節トルク情報を抽出し、障害者の脳波で外骨格パワーアシスト装置による日常生活を行うBMIパワーアシストシステムの構築を行う。本稿では、運動に関する脳波に対して新たな解析手法となる周期パワースペクトルによる解析を行い、特徴の抽出を行う。そして、主成分分析による脳波・関節トルク間の線形モデル作成手法を作成し、さらに、本手法を用いた脳波からの関節トルク推定、また得られたトルクからロボットアームを動かす実験を行い、その有効性を確認する。　　　　　　　　　Recently, the research on robot manipulation technology by Brain Machine Interface (BMI) utilizing human brain information is developed. In this study, our purpose is to estimate the force/torque information from the brain activity to help and support the human’s daily life. We analyze the measured EEGs (Electroencephalographys) in movement to extract the relationship between EEGs and EMG (Electromyography) signals, and further estimate the joint torque from the EEGs. The results show that the periodicity of alpha and beta wave variations at each measurement point have strong associations with the subject’s movement. Based on this, we build a linear model representing the relationship between EEGs and EMG by PCA (principal component analysis), and the EMG signals are successfully estimated from EEGs. From these results, the linear model between the EEGs and the joint torque which developed by PCA are confirmed and it is used to estimate the joint torque. The validity of this approach is verified by experiments. This implies a potential to use EEGs for supporting human’s activities.","subitem_description_type":"Abstract"}]},"item_2_dissertation_number_64":{"attribute_name":"学位授与番号","attribute_value_mlt":[{"subitem_dissertationnumber":"　甲第19号"}]},"item_2_text_66":{"attribute_name":"更新日","attribute_value_mlt":[{"subitem_text_value":"2019-10-28"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"吉岡, 将孝"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"ヨシオカ, マサタカ"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yoshioka, Masataka"}],"nameIdentifiers":[{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2020-09-18"}],"displaytype":"detail","filename":"Doctor_yoshioka.pdf","filesize":[{"value":"32.8 MB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"Doctor_yoshioka.pdf","url":"https://maebashi-it.repo.nii.ac.jp/record/35/files/Doctor_yoshioka.pdf"},"version_id":"73378264-dad6-4f1f-94b6-446f4322b37f"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ブレインマシンインターフェース"},{"subitem_subject":"Brain-machine interface"},{"subitem_subject":"脳波"},{"subitem_subject":"EEG"},{"subitem_subject":"筋活動"},{"subitem_subject":"Muscle activity"},{"subitem_subject":"主成分分析"},{"subitem_subject":"PCA"},{"subitem_subject":"推定"},{"subitem_subject":"Estimation"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_title":"脳波分析に基づいたBrain-Machine Interface パワーアシストシステム構築 ～周期性パワースペクトルによる運動に関する脳波の解析および関節トルクの推定～","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"脳波分析に基づいたBrain-Machine Interface パワーアシストシステム構築 ～周期性パワースペクトルによる運動に関する脳波の解析および関節トルクの推定～"}]},"item_type_id":"2","owner":"2","path":["7"],"pubdate":{"attribute_name":"公開日","attribute_value":"2017-06-30"},"publish_date":"2017-06-30","publish_status":"0","recid":"35","relation_version_is_last":true,"title":["脳波分析に基づいたBrain-Machine Interface パワーアシストシステム構築 ～周期性パワースペクトルによる運動に関する脳波の解析および関節トルクの推定～"],"weko_creator_id":"2","weko_shared_id":2},"updated":"2023-06-20T14:10:47.741904+00:00"}