{"id":"https://openalex.org/W4379377751","doi":"https://doi.org/10.1101/2023.05.25.23290539","title":"Algorithm Refinement in the Non-Invasive Detection of Blood Glucose via Bio-RFID\u2122 Technology 1","display_name":"Algorithm Refinement in the Non-Invasive Detection of Blood Glucose via Bio-RFID\u2122 Technology 1","publication_year":2023,"publication_date":"2023-06-05","ids":{"openalex":"https://openalex.org/W4379377751","doi":"https://doi.org/10.1101/2023.05.25.23290539"},"language":"en","primary_location":{"id":"doi:10.1101/2023.05.25.23290539","doi":"https://doi.org/10.1101/2023.05.25.23290539","is_oa":true,"landing_page_url":"https://doi.org/10.1101/2023.05.25.23290539","pdf_url":"https://www.medrxiv.org/content/medrxiv/early/2023/07/06/2023.05.25.23290539.full.pdf","source":{"id":"https://openalex.org/S3005729997","display_name":"medRxiv","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":["https://openalex.org/P4310315909"],"host_organization_lineage_names":["Cold Spring Harbor Laboratory Press"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"medRxiv","raw_type":"posted-content"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://www.medrxiv.org/content/medrxiv/early/2023/07/06/2023.05.25.23290539.full.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026639653","display_name":"Dominic Klyve","orcid":"https://orcid.org/0000-0002-4424-3130","observed_orcids":["https://orcid.org/0000-0002-4424-3130"]},"institutions":[{"id":"https://openalex.org/I29867402","display_name":"Central Washington University","ror":"https://ror.org/049c8eh51","country_code":"US","type":"education","lineage":["https://openalex.org/I29867402"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Dominic Klyve","raw_affiliation_strings":["Department of Mathematics, Central Washington University Ellensburg 98926, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Central Washington University Ellensburg 98926, USA","institution_ids":["https://openalex.org/I29867402"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109911879","display_name":"Kaptain Currie","orcid":"https://orcid.org/0000-0003-4350-6338","observed_orcids":["https://orcid.org/0000-0003-4350-6338"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kaptain Currie","raw_affiliation_strings":["Know Labs, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Know Labs, Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"James H. Anderson","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"James H. Anderson","raw_affiliation_strings":["Know Labs, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Know Labs, Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Carl Ward","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Carl Ward","raw_affiliation_strings":["Edge Impulse, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Edge Impulse, Inc","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002079002","display_name":"David Schwarz","orcid":"https://orcid.org/0000-0001-8817-175X","observed_orcids":["https://orcid.org/0000-0001-8817-175X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"David Schwarz","raw_affiliation_strings":["Edge Impulse, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Edge Impulse, Inc","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5112929540","display_name":"Barry Shelton","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Barry Shelton","raw_affiliation_strings":["Know Labs, Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Know Labs, Inc","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5026639653"],"corresponding_institution_ids":["https://openalex.org/I29867402"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.7695000171661377,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.7695000171661377,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10560","display_name":"Diabetes Management and Research","score":0.08889999985694885,"subfield":{"id":"https://openalex.org/subfields/2712","display_name":"Endocrinology, Diabetes and Metabolism"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11607","display_name":"Microwave and Dielectric Measurement Techniques","score":0.02290000021457672,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/non-invasive-glucose-monitoring","display_name":"non-invasive glucose monitoring","score":0.9629999995231628},{"id":"https://openalex.org/keywords/rf-sensing","display_name":"radio frequency sensing","score":0.8889999985694885},{"id":"https://openalex.org/keywords/diabetes-mellitus","display_name":"diabetes mellitus","score":0.9620000123977661},{"id":"https://openalex.org/keywords/lightgbm","display_name":"LightGBM","score":0.6489999890327454},{"id":"https://openalex.org/keywords/dexcom-g6","display_name":"Dexcom G6","score":0.6959999799728394},{"id":"https://openalex.org/keywords/hyperglycemia","display_name":"hyperglycemia","score":0.7680000066757202},{"id":"https://openalex.org/keywords/sensor-validation","display_name":"sensor validation","score":0.6150000095367432},{"id":"https://openalex.org/keywords/algorithm-improvement","display_name":"algorithm improvement","score":0.5270000100135803}],"concepts":[{"id":"https://openalex.org/C555293320","wikidata":"https://www.wikidata.org/wiki/Q12206","display_name":"Diabetes mellitus","level":2,"score":0.6232283711433411},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.5364696383476257},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.4901900887489319},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.43604928255081177},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.428209125995636},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4235178828239441},{"id":"https://openalex.org/C2986379492","wikidata":"https://www.wikidata.org/wiki/Q1638492","display_name":"Continuous glucose monitoring","level":4,"score":0.4117394983768463},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40343350172042847},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3631187081336975},{"id":"https://openalex.org/C136229726","wikidata":"https://www.wikidata.org/wiki/Q327092","display_name":"Biomedical engineering","level":1,"score":0.3261410593986511},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2876683473587036},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.18264949321746826},{"id":"https://openalex.org/C134018914","wikidata":"https://www.wikidata.org/wiki/Q162606","display_name":"Endocrinology","level":1,"score":0.16965749859809875},{"id":"https://openalex.org/C2781232474","wikidata":"https://www.wikidata.org/wiki/Q124407","display_name":"Type 1 diabetes","level":3,"score":0.14442282915115356},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1101/2023.05.25.23290539","doi":"https://doi.org/10.1101/2023.05.25.23290539","is_oa":true,"landing_page_url":"https://doi.org/10.1101/2023.05.25.23290539","pdf_url":"https://www.medrxiv.org/content/medrxiv/early/2023/07/06/2023.05.25.23290539.full.pdf","source":{"id":"https://openalex.org/S3005729997","display_name":"medRxiv","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":["https://openalex.org/P4310315909"],"host_organization_lineage_names":["Cold Spring Harbor Laboratory Press"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"medRxiv","raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.1101/2023.05.25.23290539","doi":"https://doi.org/10.1101/2023.05.25.23290539","is_oa":true,"landing_page_url":"https://doi.org/10.1101/2023.05.25.23290539","pdf_url":"https://www.medrxiv.org/content/medrxiv/early/2023/07/06/2023.05.25.23290539.full.pdf","source":{"id":"https://openalex.org/S3005729997","display_name":"medRxiv","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core"],"host_organization":null,"host_organization_name":null,"host_organization_lineage":["https://openalex.org/P4310315909"],"host_organization_lineage_names":["Cold Spring Harbor Laboratory Press"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"medRxiv","raw_type":"posted-content"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/3","display_name":"Good health and well-being","score":0.9391000270843506}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4379377751.pdf","grobid_xml":"https://content.openalex.org/works/W4379377751.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W1972517967","https://openalex.org/W1986495510","https://openalex.org/W1990505168","https://openalex.org/W2047381276","https://openalex.org/W2124622959","https://openalex.org/W2150014941","https://openalex.org/W2199257259","https://openalex.org/W2768348081","https://openalex.org/W2800767950","https://openalex.org/W2945558902","https://openalex.org/W2991259835","https://openalex.org/W3006152626","https://openalex.org/W3014765295","https://openalex.org/W3032319542","https://openalex.org/W3106856419","https://openalex.org/W3134103659","https://openalex.org/W3168630898","https://openalex.org/W3200175084"],"related_works":["https://openalex.org/W4398185740","https://openalex.org/W4399310882","https://openalex.org/W4385257372","https://openalex.org/W4396727656","https://openalex.org/W4400183740","https://openalex.org/W4399690010","https://openalex.org/W4285259363","https://openalex.org/W2979423842","https://openalex.org/W7124448586","https://openalex.org/W2949271166"],"abstract_inverted_index":{"Abstract":[0],"Diabetes":[1],"Mellitus":[2],"(DM)":[3],"is":[4,40,94,163,187],"a":[5,44,47,68,106,122,164,191],"highly":[6],"prevalent":[7],"and":[8,33,35,134,152,178,183],"increasingly":[9],"common":[10],"disorder":[11],"that":[12,179],"can":[13,30],"have":[14],"dire":[15],"health":[16],"consequences":[17],"if":[18],"not":[19],"properly":[20],"managed.":[21],"Managing":[22],"DM":[23],"involves":[24],"monitoring":[25],"blood":[26,53],"glucose":[27,54],"levels,":[28],"which":[29],"be":[31],"cumbersome":[32],"invasive,":[34],"adherence":[36],"to":[37,51,74,189],"this":[38,63,112,162,176],"practice":[39],"poor.":[41],"We":[42],"present":[43],"validation":[45],"for":[46],"novel":[48],"sensor":[49,102],"designed":[50],"measure":[52],"(BG)":[55],"non-invasively":[56],"using":[57,78],"Radio":[58],"Frequency":[59],"(RF)":[60],"waves.":[61],"In":[62],"n=5":[64],"study,":[65],"we":[66,114],"trained":[67],"Light":[69],"Gradient-Boosting":[70],"Machine":[71],"(lightGBM)":[72],"model":[73],"predict":[75],"BG":[76,116],"values":[77],"1,555":[79],"observations":[80],"from":[81,88,99],"over":[82],"130":[83],"hours":[84],"of":[85,128,142,148,157,175,195],"data":[86,97],"collection":[87],"five":[89],"participants,":[90],"where":[91],"an":[92],"observation":[93],"defined":[95],"as":[96],"collected":[98],"13":[100],"Bio-RFID":[101],"sweeps":[103],"paired":[104],"with":[105,121,180],"single":[107],"Dexcom":[108],"G6\u00ae":[109],"value.":[110,160],"Using":[111],"model,":[113],"predicted":[115],"in":[117,130,136],"the":[118,131,137,143,149,158,173],"test":[119],"set":[120],"Mean":[123],"Absolute":[124],"Relative":[125],"Difference":[126],"(MARD)":[127],"12.7%":[129],"normoglycemic":[132],"range":[133],"14.0%":[135],"hyperglycemic":[138],"range.":[139],"Overall,":[140],"70.7%":[141],"estimates":[144],"fell":[145,154],"within":[146,155],"15%":[147],"reference":[150,159],"value,":[151],"79.1%":[153],"20%":[156],"While":[161],"small":[165],"participant":[166],"sample,":[167],"these":[168],"strong":[169],"initial":[170],"results":[171],"indicate":[172],"efficacy":[174],"technique,":[177],"further":[181],"refinement":[182],"more":[184],"data,":[185],"there":[186],"promise":[188],"achieve":[190],"clinically":[192],"relevant":[193],"level":[194],"accuracy.":[196]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2026-11-09T13:22:03.289127","created_date":"2023-06-06T00:00:00"}