{"_buckets": {"deposit": "d59f0567-1f92-4bbb-8327-563ece94771c"}, "_deposit": {"id": "20849", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "20849"}, "status": "published"}, "_oai": {"id": "oai:soar-ir.repo.nii.ac.jp:00020849"}, "item_6_biblio_info_6": {"attribute_name": "\u66f8\u8a8c\u60c5\u5831", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2017-11-22", "bibliographicIssueDateType": "Issued"}, "bibliographicIssueNumber": "12", "bibliographicPageStart": "2702", "bibliographicVolumeNumber": "17", "bibliographic_titles": [{"bibliographic_title": "SENSORS"}]}]}, "item_6_description_20": {"attribute_name": "\u6284\u9332", "attribute_value_mlt": [{"subitem_description": "This paper describes and verifies a non-invasive blood glucose measurement method using a fiber Bragg grating (FBG) sensor system. The FBG sensor is installed on the radial artery, and the strain (pulse wave) that is propagated from the heartbeat is measured. The measured pulse wave signal was used as a collection of feature vectors for multivariate analysis aiming to determine the blood glucose level. The time axis of the pulse wave signal was normalized by two signal processing methods: the shortest-time-cut process and 1-s-normalization process. The measurement accuracy of the calculated blood glucose level was compared with the accuracy of these signal processing methods. It was impossible to calculate a blood glucose level exceeding 200 mg/dL in the calibration curve that was constructed by the shortest-time-cut process. In the 1-s-normalization process, the measurement accuracy of the blood glucose level was improved, and a blood glucose level exceeding 200 mg/dL could be calculated. By verifying the loading vector of each calibration curve to calculate the blood glucose level with a high measurement accuracy, we found the gradient of the peak of the pulse wave at the acceleration plethysmogram greatly affected.", "subitem_description_type": "Abstract"}]}, "item_6_description_30": {"attribute_name": "\u8cc7\u6e90\u30bf\u30a4\u30d7\uff08\u30b3\u30f3\u30c6\u30f3\u30c4\u306e\u7a2e\u985e\uff09", "attribute_value_mlt": [{"subitem_description": "Article", "subitem_description_type": "Other"}]}, "item_6_description_5": {"attribute_name": "\u5f15\u7528", "attribute_value_mlt": [{"subitem_description": "SENSORS.17(12):2702(2017)", "subitem_description_type": "Other"}]}, "item_6_link_3": {"attribute_name": "\u4fe1\u5dde\u5927\u5b66\u7814\u7a76\u8005\u7dcf\u89a7\u3078\u306e\u30ea\u30f3\u30af", "attribute_value_mlt": [{"subitem_link_text": "Koyama, Shouhei", "subitem_link_url": "http://soar-rd.shinshu-u.ac.jp/profile/ja.uVDFbakF.html"}, {"subitem_link_text": "Ishizawa, Hiroaki", "subitem_link_url": "http://soar-rd.shinshu-u.ac.jp/profile/ja.yNnhjFkV.html"}, {"subitem_link_text": "Fujimoto, Keisaku", "subitem_link_url": "http://soar-rd.shinshu-u.ac.jp/profile/ja.yFfaHFkh.html"}]}, "item_6_link_67": {"attribute_name": "WoS", "attribute_value_mlt": [{"subitem_link_text": "Web of Science", "subitem_link_url": "http://gateway.isiknowledge.com/gateway/Gateway.cgi?\u0026GWVersion=2\u0026SrcAuth=ShinshuUniv\u0026SrcApp=ShinshuUniv\u0026DestLinkType=FullRecord\u0026DestApp=WOS\u0026KeyUT=000423285800002"}]}, "item_6_publisher_4": {"attribute_name": "\u51fa\u7248\u8005", "attribute_value_mlt": [{"subitem_publisher": "MDPI AG"}]}, "item_6_relation_47": {"attribute_name": "PubMed", "attribute_value_mlt": [{"subitem_relation_name": [{"subitem_relation_name_text": "29168773"}], "subitem_relation_type_id": {"subitem_relation_type_id_text": "https://www.ncbi.nlm.nih.gov/pubmed/29168773", "subitem_relation_type_select": "PMID"}}]}, "item_6_relation_48": {"attribute_name": "DOI", "attribute_value_mlt": [{"subitem_relation_name": [{"subitem_relation_name_text": "10.3390/s17122702"}], "subitem_relation_type_id": {"subitem_relation_type_id_text": "https://doi.org/10.3390/s17122702", "subitem_relation_type_select": "DOI"}}]}, "item_6_rights_62": {"attribute_name": "\u6a29\u5229", "attribute_value_mlt": [{"subitem_rights": "\u00a9 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)."}]}, "item_6_select_64": {"attribute_name": "\u8457\u8005\u7248\u30d5\u30e9\u30b0", "attribute_value_mlt": [{"subitem_select_item": "publisher"}]}, "item_6_source_id_35": {"attribute_name": "ISSN", "attribute_value_mlt": [{"subitem_source_identifier": "1424-8220", "subitem_source_identifier_type": "ISSN"}]}, "item_6_source_id_39": {"attribute_name": "NII ISSN", "attribute_value_mlt": [{"subitem_source_identifier": "1424-8220", "subitem_source_identifier_type": "ISSN"}]}, "item_6_text_69": {"attribute_name": "wosonly authkey", "attribute_value_mlt": [{"subitem_text_value": "SPECTROSCOPY"}]}, "item_6_text_70": {"attribute_name": "wosonly keywords", "attribute_value_mlt": [{"subitem_text_value": "This paper describes and verifies a non-invasive blood glucose measurement method using a fiber Bragg grating (FBG) sensor system. The FBG sensor is installed on the radial artery, and the strain (pulse wave) that is propagated from the heartbeat is measured. The measured pulse wave signal was used as a collection of feature vectors for multivariate analysis aiming to determine the blood glucose level. The time axis of the pulse wave signal was normalized by two signal processing methods: the shortest-time-cut process and 1-s-normalization process. The measurement accuracy of the calculated blood glucose level was compared with the accuracy of these signal processing methods. It was impossible to calculate a blood glucose level exceeding 200 mg/dL in the calibration curve that was constructed by the shortest-time-cut process. In the 1-s-normalization process, the measurement accuracy of the blood glucose level was improved, and a blood glucose level exceeding 200 mg/dL could be calculated. By verifying the loading vector of each calibration curve to calculate the blood glucose level with a high measurement accuracy, we found the gradient of the peak of the pulse wave at the acceleration plethysmogram greatly affected."}]}, "item_6_textarea_68": {"attribute_name": "wosonly abstract", "attribute_value_mlt": [{"subitem_textarea_value": "fiber Bragg grating; pulse wave signal; blood glucose level; non-invasive measurement; partial least squares regression; blood flow"}]}, "item_creator": {"attribute_name": "\u8457\u8005", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "Kurasawa, Shintaro"}], "nameIdentifiers": [{"nameIdentifier": "108355", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Koyama, Shouhei"}], "nameIdentifiers": [{"nameIdentifier": "108356", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Ishizawa, Hiroaki"}], "nameIdentifiers": [{"nameIdentifier": "108357", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Fujimoto, Keisaku"}], "nameIdentifiers": [{"nameIdentifier": "108358", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Chino, Shun"}], "nameIdentifiers": [{"nameIdentifier": "108359", "nameIdentifierScheme": "WEKO"}]}]}, "item_files": {"attribute_name": "\u30d5\u30a1\u30a4\u30eb\u60c5\u5831", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_date", "date": [{"dateType": "Available", "dateValue": "2019-09-09"}], "displaytype": "detail", "download_preview_message": "", "file_order": 0, "filename": "15K01281_04.pdf", "filesize": [{"value": "3.9 MB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensefree": "\u00a9 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).", "licensetype": "license_free", "mimetype": "application/pdf", "size": 3900000.0, "url": {"label": "15K01281_04.pdf", "url": "https://soar-ir.repo.nii.ac.jp/record/20849/files/15K01281_04.pdf"}, "version_id": "37a6bf3a-8232-4c4a-a314-0f522779db25"}]}, "item_keyword": {"attribute_name": "\u30ad\u30fc\u30ef\u30fc\u30c9", "attribute_value_mlt": [{"subitem_subject": "fiber Bragg grating", "subitem_subject_scheme": "Other"}, {"subitem_subject": "pulse wave signal", "subitem_subject_scheme": "Other"}, {"subitem_subject": "blood glucose level", "subitem_subject_scheme": "Other"}, {"subitem_subject": "non-invasive measurement", "subitem_subject_scheme": "Other"}, {"subitem_subject": "partial least squares regression", "subitem_subject_scheme": "Other"}, {"subitem_subject": "blood flow", "subitem_subject_scheme": "Other"}]}, "item_language": {"attribute_name": "\u8a00\u8a9e", "attribute_value_mlt": [{"subitem_language": "eng"}]}, "item_resource_type": {"attribute_name": "\u8cc7\u6e90\u30bf\u30a4\u30d7", "attribute_value_mlt": [{"resourcetype": "journal article", "resourceuri": "http://purl.org/coar/resource_type/c_6501"}]}, "item_title": "Verification of Non-Invasive Blood Glucose Measurement Method Based on Pulse Wave Signal Detected by FBG Sensor System", "item_titles": {"attribute_name": "\u30bf\u30a4\u30c8\u30eb", "attribute_value_mlt": [{"subitem_title": "Verification of Non-Invasive Blood Glucose Measurement Method Based on Pulse Wave Signal Detected by FBG Sensor System"}]}, "item_type_id": "6", "owner": "1", "path": ["461/462"], "permalink_uri": "http://hdl.handle.net/10091/00021606", "pubdate": {"attribute_name": "\u516c\u958b\u65e5", "attribute_name_i18n": "\u516c\u958b\u65e5", "attribute_value": "2019-09-09"}, "publish_date": "2019-09-09", "publish_status": "0", "recid": "20849", "relation": {}, "relation_version_is_last": true, "title": ["Verification of Non-Invasive Blood Glucose Measurement Method Based on Pulse Wave Signal Detected by FBG Sensor System"], "weko_shared_id": null}