{"id":"https://openalex.org/W4417251821","doi":"https://doi.org/10.1109/tbiom.2025.3643169","title":"Transformer Network-Based Gait Identification Using WiFi","display_name":"Transformer Network-Based Gait Identification Using WiFi","publication_year":2025,"publication_date":"2025-12-11","ids":{"openalex":"https://openalex.org/W4417251821","doi":"https://doi.org/10.1109/tbiom.2025.3643169"},"language":"en","primary_location":{"id":"doi:10.1109/tbiom.2025.3643169","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tbiom.2025.3643169","pdf_url":null,"source":{"id":"https://openalex.org/S4210209367","display_name":"IEEE Transactions on Biometrics Behavior and Identity Science","issn_l":"2637-6407","issn":["2637-6407"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Biometrics, Behavior, and Identity Science","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1109/tbiom.2025.3643169","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5120776404","display_name":"Oliver Custance","orcid":"https://orcid.org/0009-0005-7245-0857"},"institutions":[{"id":"https://openalex.org/I133837150","display_name":"University of Huddersfield","ror":"https://ror.org/05t1h8f27","country_code":"GB","type":"education","lineage":["https://openalex.org/I133837150"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Oliver Custance","raw_affiliation_strings":["Department of Computer Science, University of Huddersfield, Huddersfield, U.K"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Huddersfield, Huddersfield, U.K","institution_ids":["https://openalex.org/I133837150"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053811883","display_name":"Saad Khan","orcid":"https://orcid.org/0000-0001-8613-8200"},"institutions":[{"id":"https://openalex.org/I133837150","display_name":"University of Huddersfield","ror":"https://ror.org/05t1h8f27","country_code":"GB","type":"education","lineage":["https://openalex.org/I133837150"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Saad Khan","raw_affiliation_strings":["Department of Computer Science, University of Huddersfield, Huddersfield, U.K"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Huddersfield, Huddersfield, U.K","institution_ids":["https://openalex.org/I133837150"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037686924","display_name":"Simon Parkinson","orcid":"https://orcid.org/0000-0002-1747-9914"},"institutions":[{"id":"https://openalex.org/I133837150","display_name":"University of Huddersfield","ror":"https://ror.org/05t1h8f27","country_code":"GB","type":"education","lineage":["https://openalex.org/I133837150"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Simon Parkinson","raw_affiliation_strings":["Department of Computer Science, University of Huddersfield, Huddersfield, U.K"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Huddersfield, Huddersfield, U.K","institution_ids":["https://openalex.org/I133837150"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5120776404"],"corresponding_institution_ids":["https://openalex.org/I133837150"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.41470851,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"8","issue":"2","first_page":"311","last_page":"326"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.546500027179718,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.546500027179718,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.4235999882221222,"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"}},{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.0031999999191612005,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6686000227928162},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5669999718666077},{"id":"https://openalex.org/keywords/gait","display_name":"Gait","score":0.5214999914169312},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4634999930858612},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4595000147819519},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.45249998569488525},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.3756999969482422},{"id":"https://openalex.org/keywords/accelerometer","display_name":"Accelerometer","score":0.3752000033855438},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.3573000133037567}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7653999924659729},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6686000227928162},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5669999718666077},{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.5214999914169312},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5142999887466431},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4634999930858612},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4595000147819519},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.45249998569488525},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42989999055862427},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4032000005245209},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3871000111103058},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3765999972820282},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.3756999969482422},{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.3752000033855438},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.3573000133037567},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.3492000102996826},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.3465999960899353},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3407000005245209},{"id":"https://openalex.org/C119247159","wikidata":"https://www.wikidata.org/wiki/Q1366192","display_name":"System identification","level":3,"score":0.3393999934196472},{"id":"https://openalex.org/C173906292","wikidata":"https://www.wikidata.org/wiki/Q1493441","display_name":"Gait analysis","level":3,"score":0.33559998869895935},{"id":"https://openalex.org/C2988656282","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity detection","level":2,"score":0.31859999895095825},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.3061000108718872},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3027999997138977},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2994999885559082},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.29510000348091125},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.28529998660087585},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.2711000144481659},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.26809999346733093},{"id":"https://openalex.org/C120068334","wikidata":"https://www.wikidata.org/wiki/Q45343","display_name":"Polynomial regression","level":3,"score":0.25859999656677246},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.257099986076355},{"id":"https://openalex.org/C70770792","wikidata":"https://www.wikidata.org/wiki/Q7239848","display_name":"Preferred walking speed","level":2,"score":0.25209999084472656},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.25060001015663147}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tbiom.2025.3643169","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tbiom.2025.3643169","pdf_url":null,"source":{"id":"https://openalex.org/S4210209367","display_name":"IEEE Transactions on Biometrics Behavior and Identity Science","issn_l":"2637-6407","issn":["2637-6407"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Biometrics, Behavior, and Identity Science","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:publications/38f15e4d-251a-4f27-9278-462d57489a4e","is_oa":true,"landing_page_url":"https://pure.hud.ac.uk/en/publications/38f15e4d-251a-4f27-9278-462d57489a4e","pdf_url":null,"source":{"id":"https://openalex.org/S4306402508","display_name":"Huddersfield Research Portal (University of Huddersfield)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I133837150","host_organization_name":"University of Huddersfield","host_organization_lineage":["https://openalex.org/I133837150"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Custance, O, Khan, S & Parkinson, S 2026, 'Transformer Network-based Gait Identification using WiFi', IEEE Transactions on Biometrics, Behavior, and Identity Science, vol. 8, no. 2, 11298190, pp. 311-326. https://doi.org/10.1109/TBIOM.2025.3643169","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"doi:10.1109/tbiom.2025.3643169","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tbiom.2025.3643169","pdf_url":null,"source":{"id":"https://openalex.org/S4210209367","display_name":"IEEE Transactions on Biometrics Behavior and Identity Science","issn_l":"2637-6407","issn":["2637-6407"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Biometrics, Behavior, and Identity Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Wireless":[0],"sensing":[1],"has":[2],"become":[3],"a":[4,56,86,93,111,164],"prominent":[5],"choice":[6],"for":[7,12,70,89,138,169],"human":[8],"activity":[9],"recognition,":[10,91],"valued":[11],"its":[13],"non-intrusive":[14],"operation":[15],"and":[16,30,45,65,78,105,123,135,140,156],"privacy-conscious":[17],"design.":[18],"However,":[19],"it":[20],"grapples":[21],"with":[22,102],"environmental":[23],"challenges,":[24],"especially":[25],"from":[26,129],"static":[27],"(e.g.,":[28,33],"furniture)":[29],"dynamic":[31],"objects":[32],"people":[34],"walking),":[35],"as":[36,38,43],"well":[37],"how":[39],"demographic":[40],"factors":[41],"such":[42],"BMI":[44],"sensor":[46],"quantity":[47],"affect":[48],"accuracy.":[49],"This":[50],"paper":[51],"addresses":[52],"these":[53],"gaps":[54],"through":[55],"focused":[57],"experiment":[58],"on":[59],"gait-based":[60],"participant":[61],"identification.":[62],"Our":[63],"methods":[64],"techniques":[66,179],"encompass":[67],"variance":[68],"exploration":[69],"movement":[71],"detection,":[72],"Channel":[73],"Power":[74],"Distribution":[75],"(CPD)":[76],"analysis,":[77],"polynomial":[79],"fitting":[80],"to":[81],"determine":[82],"walking":[83],"direction.We":[84],"present":[85],"novel":[87],"model":[88],"gait":[90,116],"using":[92,119],"hybrid":[94],"architecture":[95],"that":[96,166],"combines":[97],"convolutional":[98],"layers,":[99],"LSTM":[100],"blocks":[101],"residual":[103],"connections,":[104],"multi-head":[106],"self-attention":[107],"mechanisms.":[108],"We":[109,132],"conducted":[110],"comprehensive":[112],"evaluation":[113],"of":[114,127,180],"our":[115,145,161],"identification":[117],"system":[118],"two":[120],"datasets:":[121],"MultiEnvironment":[122,139],"HWDD.":[124],"Both":[125],"consist":[126],"data":[128],"10":[130],"volunteers.":[131],"achieved":[133],"96.1%":[134],"96.66%":[136],"accuracy":[137,174],"HWDD,":[141],"respectively.":[142],"To":[143],"benchmark":[144,160],"system,":[146],"we":[147,159,167],"selected":[148],"four":[149],"state-of-the-art":[150,178],"pre-trained":[151],"models:":[152],"Transformer,":[153],"LSTM,":[154],"CNN":[155],"SVM.":[157],"Finally,":[158],"technique":[162],"against":[163],"dataset":[165],"collected":[168],"25":[170],"individuals,":[171],"demonstrating":[172],"an":[173],"better":[175],"than":[176],"other":[177],"97.9%.":[181]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-12-11T00:00:00"}
