{"id":"https://openalex.org/W7148415147","doi":"https://doi.org/10.1109/vr67842.2026.00052","title":"Multimodal Analysis of Speech-Gaze Fusion in Mixed Reality for the Detection of Neurodegenerative Disorders","display_name":"Multimodal Analysis of Speech-Gaze Fusion in Mixed Reality for the Detection of Neurodegenerative Disorders","publication_year":2026,"publication_date":"2026-03-21","ids":{"openalex":"https://openalex.org/W7148415147","doi":"https://doi.org/10.1109/vr67842.2026.00052"},"language":null,"primary_location":{"id":"doi:10.1109/vr67842.2026.00052","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vr67842.2026.00052","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012763683","display_name":"Mi\u0142osz Dudek","orcid":"https://orcid.org/0009-0008-4299-9162"},"institutions":[{"id":"https://openalex.org/I686019","display_name":"AGH University of Krakow","ror":"https://ror.org/00bas1c41","country_code":"PL","type":"education","lineage":["https://openalex.org/I686019"]}],"countries":["PL"],"is_corresponding":true,"raw_author_name":"Milosz Dudek","raw_affiliation_strings":["AGH University of Krakow,Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AGH University of Krakow,Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering","institution_ids":["https://openalex.org/I686019"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055776726","display_name":"Jakub Sikora","orcid":"https://orcid.org/0000-0003-4104-2023"},"institutions":[{"id":"https://openalex.org/I686019","display_name":"AGH University of Krakow","ror":"https://ror.org/00bas1c41","country_code":"PL","type":"education","lineage":["https://openalex.org/I686019"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Jakub Sikora","raw_affiliation_strings":["AGH University of Krakow,Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AGH University of Krakow,Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering","institution_ids":["https://openalex.org/I686019"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053011139","display_name":"Daria Hemmerling","orcid":"https://orcid.org/0000-0002-2193-7690"},"institutions":[{"id":"https://openalex.org/I686019","display_name":"AGH University of Krakow","ror":"https://ror.org/00bas1c41","country_code":"PL","type":"education","lineage":["https://openalex.org/I686019"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Daria Hemmerling","raw_affiliation_strings":["AGH University of Krakow,Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AGH University of Krakow,Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering","institution_ids":["https://openalex.org/I686019"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015611403","display_name":"Mateusz Danio\u0142","orcid":"https://orcid.org/0000-0003-2363-7912"},"institutions":[{"id":"https://openalex.org/I686019","display_name":"AGH University of Krakow","ror":"https://ror.org/00bas1c41","country_code":"PL","type":"education","lineage":["https://openalex.org/I686019"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Mateusz Daniol","raw_affiliation_strings":["AGH University of Krakow,Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AGH University of Krakow,Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering","institution_ids":["https://openalex.org/I686019"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015739274","display_name":"Marek Wodzi\u0144ski","orcid":"https://orcid.org/0000-0002-8076-6246"},"institutions":[{"id":"https://openalex.org/I686019","display_name":"AGH University of Krakow","ror":"https://ror.org/00bas1c41","country_code":"PL","type":"education","lineage":["https://openalex.org/I686019"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Marek Wodzinski","raw_affiliation_strings":["AGH University of Krakow,Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"AGH University of Krakow,Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering","institution_ids":["https://openalex.org/I686019"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037171772","display_name":"Magdalena W\u00f3jcik-P\u0119dziwiatr","orcid":"https://orcid.org/0000-0003-0600-6780"},"institutions":[{"id":"https://openalex.org/I4210148240","display_name":"Andrzej Frycz Modrzewski Krakow University","ror":"https://ror.org/03m9nwf24","country_code":"PL","type":"education","lineage":["https://openalex.org/I4210148240"]}],"countries":["PL"],"is_corresponding":false,"raw_author_name":"Magdalena Wojcik-Pedziwiatr","raw_affiliation_strings":["Andrzej Frycz-Modrzewski Krakow University,Department of Neurology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Andrzej Frycz-Modrzewski Krakow University,Department of Neurology","institution_ids":["https://openalex.org/I4210148240"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5012763683"],"corresponding_institution_ids":["https://openalex.org/I686019"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.68816718,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"305","last_page":"314"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.15719999372959137,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.15719999372959137,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.15240000188350677,"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"}},{"id":"https://openalex.org/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.10939999669790268,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/mixed-reality","display_name":"Mixed reality","score":0.42309999465942383},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4205000102519989},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.3303000032901764},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.2619999945163727}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.462799996137619},{"id":"https://openalex.org/C206776904","wikidata":"https://www.wikidata.org/wiki/Q1758389","display_name":"Mixed reality","level":3,"score":0.42309999465942383},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4205000102519989},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3984000086784363},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.34700000286102295},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.3303000032901764},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.3131999969482422},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2619999945163727},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.25529998540878296},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.25429999828338623}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vr67842.2026.00052","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vr67842.2026.00052","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE Conference on Virtual Reality and 3D User Interfaces (VR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5338918566703796,"display_name":"Gender equality","id":"https://metadata.un.org/sdg/5"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320337504","display_name":"Research and Development","ror":"https://ror.org/027s68j25"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W1965305672","https://openalex.org/W2014552602","https://openalex.org/W2061504941","https://openalex.org/W2087388117","https://openalex.org/W2101807845","https://openalex.org/W2109606373","https://openalex.org/W2110065044","https://openalex.org/W2132193994","https://openalex.org/W2140978740","https://openalex.org/W2165758561","https://openalex.org/W2518841925","https://openalex.org/W2945531494","https://openalex.org/W2973515423","https://openalex.org/W2995382111","https://openalex.org/W3138052705","https://openalex.org/W3200973239","https://openalex.org/W3205690112","https://openalex.org/W3212450652","https://openalex.org/W3213736482","https://openalex.org/W4205563072","https://openalex.org/W4210892412","https://openalex.org/W4304633197","https://openalex.org/W4321122916","https://openalex.org/W4322772975","https://openalex.org/W4385383358","https://openalex.org/W4385822293","https://openalex.org/W4389273131","https://openalex.org/W4402111606","https://openalex.org/W4402115333","https://openalex.org/W4403548131","https://openalex.org/W4403844948","https://openalex.org/W4404901853","https://openalex.org/W4405489440","https://openalex.org/W4409002405","https://openalex.org/W4409335852"],"related_works":[],"abstract_inverted_index":{"Mixed":[0],"reality":[1],"(MR)":[2],"headsets":[3],"can":[4,265],"synchronously":[5],"capture":[6,252,266],"eye":[7],"movements":[8],"and":[9,28,39,56,63,84,91,102,105,132,136,138,206,237,247,255,270,289,301],"speech":[10,29,110,238],"during":[11,44],"ecological":[12,245],"tasks,":[13],"enabling":[14],"interpretable,":[15],"multimodal":[16],"behavioural":[17],"assessment.":[18],"This":[19],"study":[20],"introduces":[21],"an":[22,218],"MR-native":[23],"pipeline":[24],"that":[25,261],"fuses":[26],"gaze":[27,97,100,109,162,236],"to":[30,185,298],"characterize":[31],"Parkinson\u2019s":[32],"disease":[33],"(PD)":[34],"in":[35,123,146,160,175,188,239,253,292],"10":[36],"PD":[37,268],"patients":[38],"18":[40],"healthy":[41],"controls":[42],"(HC)":[43],"a":[45,118,140,178,272],"40":[46],"s":[47],"picture":[48],"description":[49],"on":[50],"Microsoft":[51],"HoloLens":[52],"2.Audio":[53],"is":[54,89,173,296],"transcribed":[55],"force-aligned":[57],"with":[58],"word-level":[59],"timestamps,":[60],"linguistically":[61],"annotated":[62],"converted":[64],"into":[65,93],"lexical":[66,74],"(tokens,":[67],"unique":[68,155],"tokens,":[69,154,156],"MTLD":[70],"(measure":[71],"of":[72,181],"textual":[73],"diversity)),":[75],"syntactic":[76],"(proper":[77],"nouns":[78,169],"per":[79,152,170],"100":[80,171],"tokens),":[81],"fluency":[82],"(words-per-minute),":[83],"pause-based":[85],"temporal":[86],"features.":[87],"Gaze":[88],"filtered":[90],"summarized":[92],"kinematic":[94],"measures":[95],"(mean":[96],"speed,":[98],"mean":[99],"acceleration,":[101],"acceleration":[103],"variability)":[104],"fixation":[106,163],"rate.":[107],"Aligned":[108],"segments":[111],"were":[112],"independently":[113],"rated":[114],"for":[115],"correspondence,":[116],"yielding":[117],"per-participant":[119],"alignment":[120,145,216],"accuracy":[121,209,225],"used":[122],"downstream":[124],"analysis.Group":[125],"contrasts":[126],"use":[127],"Mann\u2013Whitney":[128],"U,":[129],"Cliff\u2019s":[130],"\u03b4,":[131],"FDR":[133],"control":[134],"(global":[135],"family-wise)":[137],"show":[139],"distributional":[141],"shift":[142],"toward":[143,275],"lower":[144],"PD.":[147],"Speech-derived":[148],"markers":[149],"(total/voiced":[150],"words":[151],"minute,":[153],"MTLD)":[157],"are":[158,282],"reduced":[159],"PD,":[161,176],"rate":[164,180],"also":[165],"trends":[166],"lower;":[167],"proper":[168],"tokens":[172],"higher":[174,179],"indicating":[177],"proper-noun":[182],"usage":[183],"relative":[184],"transcript":[186],"length":[187],"this":[189],"task.":[190],"A":[191],"compact":[192],"Top-K":[193],"set":[194],"(K=7)":[195],"yields":[196],"meaningful":[197],"multivariate":[198],"separability":[199],"(centroid":[200],"distance":[201],"2.826,":[202],"95%":[203],"CI":[204,223],"[1.900,4.113])":[205],"nearest-centroid":[207],"balanced":[208],"0.733,":[210],"which":[211],"further":[212],"improves":[213],"when":[214],"adding":[215],"as":[217],"8th":[219],"feature":[220],"(distance":[221],"2.854,":[222],"[1.981,4.149];":[224],"0.783).MR":[226],"offers":[227],"clear":[228],"advantages":[229],"over":[230],"conventional":[231],"setups:":[232],"the":[233,280,285],"headset":[234],"co-registers":[235],"situ":[240],"without":[241],"external":[242],"rigs,":[243],"preserves":[244],"validity,":[246],"supports":[248],"repeatable,":[249],"low-burden,":[250],"time-synchronized":[251],"clinics":[254],"at":[256],"home.":[257],"These":[258],"findings":[259],"indicate":[260],"MR":[262],"gaze\u2013speech":[263],"fusion":[264],"complementary":[267],"deficits":[269],"suggests":[271],"scalable":[273],"path":[274],"interpretable":[276],"digital":[277],"biomarkers.":[278],"However,":[279],"conclusions":[281],"constrained":[283],"by":[284],"limited":[286],"sample":[287],"size,":[288],"future":[290],"validation":[291],"larger,":[293],"independent":[294],"cohorts":[295],"required":[297],"confirm":[299],"generalizability":[300],"clinical":[302],"utility.":[303]},"counts_by_year":[],"updated_date":"2026-05-05T08:41:31.759640","created_date":"2026-04-03T00:00:00"}