{"id":"https://openalex.org/W4416876348","doi":"https://doi.org/10.1016/j.bspc.2026.110747","title":"Depression Severity Prediction using Multidimensional Eye and Head Features: A Lanczos-based Quaternion Singular Spectrum Analysis Approach","display_name":"Depression Severity Prediction using Multidimensional Eye and Head Features: A Lanczos-based Quaternion Singular Spectrum Analysis Approach","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4416876348","doi":"https://doi.org/10.1016/j.bspc.2026.110747"},"language":"en","primary_location":{"id":"doi:10.1016/j.bspc.2026.110747","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.bspc.2026.110747","pdf_url":null,"source":{"id":"https://openalex.org/S8427965","display_name":"Biomedical Signal Processing and Control","issn_l":"1746-8094","issn":["1746-8094","1746-8108"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Biomedical Signal Processing and Control","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1016/j.bspc.2026.110747","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5084150003","display_name":"Gary Man-Tat Man","orcid":"https://orcid.org/0009-0000-7822-8871"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gary Man-Tat Man","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051376589","display_name":"Kevin Hung","orcid":"https://orcid.org/0000-0002-5421-7622"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kevin Hung","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114138963","display_name":"Bingo Wing-Kuen Ling","orcid":"https://orcid.org/0000-0002-0633-7224"},"institutions":[{"id":"https://openalex.org/I139024713","display_name":"Guangdong University of Technology","ror":"https://ror.org/04azbjn80","country_code":"CN","type":"education","lineage":["https://openalex.org/I139024713"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bingo Wing-Kuen Ling","raw_affiliation_strings":["Guangdong University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Guangdong University of Technology","institution_ids":["https://openalex.org/I139024713"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085722138","display_name":"Daniel H. K. Chow","orcid":"https://orcid.org/0000-0001-9333-4920"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Daniel  Hung-Kay Chow","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048442222","display_name":"Sio Hang Pun","orcid":"https://orcid.org/0000-0002-8648-2092"},"institutions":[{"id":"https://openalex.org/I6469544","display_name":"City University of Macau","ror":"https://ror.org/04gpd4q15","country_code":"MO","type":"education","lineage":["https://openalex.org/I6469544"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Sio Hang Pun","raw_affiliation_strings":["City University of Macau"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"City University of Macau","institution_ids":["https://openalex.org/I6469544"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065567938","display_name":"John Kwok-Tai Chui","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"John  Kwok-Tai Chui","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027754070","display_name":"Tai-Wa Liu","orcid":"https://orcid.org/0000-0001-9055-5197"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tai-Wa Liu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082547911","display_name":"Shuqiang Wang","orcid":"https://orcid.org/0000-0003-1119-320X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuqiang Wang","raw_affiliation_strings":["Chinese Academy of Sciences (CAS)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chinese Academy of Sciences (CAS)","institution_ids":["https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071245446","display_name":"Qi Li","orcid":"https://orcid.org/0000-0002-8655-5781"},"institutions":[{"id":"https://openalex.org/I106645853","display_name":"Changchun University of Science and Technology","ror":"https://ror.org/007mntk44","country_code":"CN","type":"education","lineage":["https://openalex.org/I106645853"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Li","raw_affiliation_strings":["Changchun University of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Changchun University of Science and Technology","institution_ids":["https://openalex.org/I106645853"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2420,"currency":"USD","value_usd":2420},"apc_paid":{"value":2420,"currency":"USD","value_usd":2420},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.33241633,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"125","issue":null,"first_page":"110747","last_page":"110747"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.3294000029563904,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.3294000029563904,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.20309999585151672,"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"}},{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.06780000030994415,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.6092000007629395},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5353999733924866},{"id":"https://openalex.org/keywords/singular-spectrum-analysis","display_name":"Singular spectrum analysis","score":0.4968000054359436},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.48890000581741333},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48750001192092896},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4674000144004822},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4359000027179718},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.41839998960494995}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6299999952316284},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6255000233650208},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.6092000007629395},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5353999733924866},{"id":"https://openalex.org/C136272165","wikidata":"https://www.wikidata.org/wiki/Q4048889","display_name":"Singular spectrum analysis","level":3,"score":0.4968000054359436},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.48890000581741333},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48750001192092896},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4674000144004822},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4359000027179718},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.41839998960494995},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4016999900341034},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.36329999566078186},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34119999408721924},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32190001010894775},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.32030001282691956},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.3131999969482422},{"id":"https://openalex.org/C200127275","wikidata":"https://www.wikidata.org/wiki/Q173853","display_name":"Quaternion","level":2,"score":0.29179999232292175},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.28780001401901245},{"id":"https://openalex.org/C2777885455","wikidata":"https://www.wikidata.org/wiki/Q5156615","display_name":"Complex wavelet transform","level":5,"score":0.2858000099658966},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.2759999930858612},{"id":"https://openalex.org/C153050134","wikidata":"https://www.wikidata.org/wiki/Q760256","display_name":"Eye movement","level":2,"score":0.26899999380111694},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.259799987077713},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.259799987077713},{"id":"https://openalex.org/C90652560","wikidata":"https://www.wikidata.org/wiki/Q11091747","display_name":"Minimum mean square error","level":3,"score":0.2542000114917755},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.2517000138759613}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1016/j.bspc.2026.110747","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.bspc.2026.110747","pdf_url":null,"source":{"id":"https://openalex.org/S8427965","display_name":"Biomedical Signal Processing and Control","issn_l":"1746-8094","issn":["1746-8094","1746-8108"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Biomedical Signal Processing and Control","raw_type":"journal-article"},{"id":"doi:10.2139/ssrn.5800171","is_oa":true,"landing_page_url":"https://doi.org/10.2139/ssrn.5800171","pdf_url":null,"source":{"id":"https://openalex.org/S4210172589","display_name":"SSRN Electronic Journal","issn_l":"1556-5068","issn":["1556-5068"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1318003438","host_organization_name":"RELX Group (Netherlands)","host_organization_lineage":["https://openalex.org/I1318003438"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"posted-content"}],"best_oa_location":{"id":"doi:10.1016/j.bspc.2026.110747","is_oa":true,"landing_page_url":"https://doi.org/10.1016/j.bspc.2026.110747","pdf_url":null,"source":{"id":"https://openalex.org/S8427965","display_name":"Biomedical Signal Processing and Control","issn_l":"1746-8094","issn":["1746-8094","1746-8108"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320990","host_organization_name":"Elsevier BV","host_organization_lineage":["https://openalex.org/P4310320990"],"host_organization_lineage_names":["Elsevier BV"],"type":"journal"},"license":"cc-by-nc-sa","license_id":"https://openalex.org/licenses/cc-by-nc-sa","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Biomedical Signal Processing and Control","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321592","display_name":"Research Grants Council, University Grants Committee","ror":"https://ror.org/00djwmt25"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W154790888","https://openalex.org/W1985765492","https://openalex.org/W2035804753","https://openalex.org/W2114765937","https://openalex.org/W2140321956","https://openalex.org/W2154456984","https://openalex.org/W2252180568","https://openalex.org/W2348144522","https://openalex.org/W2550419422","https://openalex.org/W2558919063","https://openalex.org/W2751214333","https://openalex.org/W2766122029","https://openalex.org/W2766194567","https://openalex.org/W2792096032","https://openalex.org/W2800279828","https://openalex.org/W2803017656","https://openalex.org/W2807126412","https://openalex.org/W2913656727","https://openalex.org/W2960672642","https://openalex.org/W2962762902","https://openalex.org/W2978855205","https://openalex.org/W2981660166","https://openalex.org/W3027457525","https://openalex.org/W3121941930","https://openalex.org/W3124623599","https://openalex.org/W3166254754","https://openalex.org/W3198098992","https://openalex.org/W3208497351","https://openalex.org/W4200524172","https://openalex.org/W4226065410","https://openalex.org/W4280624167","https://openalex.org/W4288704366","https://openalex.org/W4313443450","https://openalex.org/W4366087621","https://openalex.org/W4384916583","https://openalex.org/W4386523188","https://openalex.org/W4399517994","https://openalex.org/W4401221196","https://openalex.org/W4405707338","https://openalex.org/W4406753812","https://openalex.org/W4408258589","https://openalex.org/W4412567989","https://openalex.org/W4413754720","https://openalex.org/W7124131577"],"related_works":[],"abstract_inverted_index":{"Depression":[0],"is":[1,11],"a":[2,77,170,179],"pervasive":[3],"mental":[4,247],"health":[5,248],"disorder":[6],"affecting":[7],"millions":[8],"worldwide.":[9],"There":[10],"an":[12,197,202,214,219],"urgent":[13],"need":[14],"for":[15,19,57,65,85,207],"objective":[16],"automated":[17,26],"tools":[18],"early":[20],"detection":[21],"and":[22,38,46,87,108,125,127,144,178,201,218,238],"severity":[23,160],"prediction.":[24],"Current":[25],"approaches":[27,157],"often":[28],"fail":[29],"to":[30,41,101],"adequately":[31],"address":[32],"temporal":[33],"dependencies":[34],"between":[35],"data":[36,245],"channels":[37],"remain":[39,60],"vulnerable":[40],"noise":[42,124],"interference.":[43],"Notably,":[44],"eye":[45,107],"head":[47,109],"dynamics":[48],"-":[49,59],"among":[50],"the":[51,121,136,145,150,164,167,187,191,194,208,211,224,235],"most":[52],"accessible":[53],"non-verbal":[54],"behavioral":[55],"biomarkers":[56],"depression":[58,132,159],"understudied":[61],"despite":[62],"their":[63,114],"suitability":[64],"collection":[66],"via":[67],"consumer":[68],"smart":[69],"eyewear":[70],"in":[71,158,246],"home":[72],"environments.":[73],"This":[74],"paper":[75],"presents":[76],"novel":[78],"Lanczos-based":[79],"quaternion-based":[80],"Singular":[81],"Spectrum":[82],"Analysis":[83,139],"approach":[84],"fast":[86],"robust":[88],"feature":[89],"extraction":[90],"from":[91,105,123],"eye-head":[92],"movement":[93,110],"patterns.":[94],"The":[95],"method":[96,152],"employs":[97],"quaternion":[98],"signal":[99],"processing":[100],"extract":[102],"features":[103,119],"holistically":[104],"multidimensional":[106],"signals":[111],"while":[112],"preserving":[113],"intrinsic":[115],"spatiotemporal":[116],"relationships.":[117],"These":[118],"remove":[120],"interference":[122],"outlier,":[126],"enable":[128],"accurate":[129],"machine":[130],"learning-based":[131],"assessment.":[133],"Validated":[134],"on":[135,186,223],"benchmark":[137],"Distress":[138],"Interview":[140],"Corpus":[141],"(DAIC)":[142],"dataset":[143],"extended":[146],"DAIC":[147,165],"(E-DAIC)":[148],"dataset,":[149,166,210],"proposed":[151],"outperforms":[153],"conventional":[154],"visual":[155],"modality-based":[156],"prediction":[161],"task.":[162],"For":[163],"system":[168,195,212],"achieved":[169,196,213],"root":[171],"mean":[172,180],"square":[173],"error":[174,182],"(RMSE)":[175],"of":[176,184,199,204,216,221,242],"5.26,":[177],"absolute":[181],"(MAE)":[183],"4.08":[185],"development":[188,225],"set.":[189,226],"On":[190],"testing":[192],"set,":[193],"RMSE":[198,215],"4.74,":[200],"MAE":[203,220],"3.83.":[205],"Furthermore,":[206],"E-DAIC":[209],"4.26,":[217],"3.53":[222],"Detailed":[227],"analysis,":[228],"including":[229],"various":[230],"ablation":[231],"studies,":[232],"further":[233],"demonstrates":[234],"method's":[236],"effectiveness":[237],"highlights":[239],"promising":[240],"applications":[241],"wearable":[243],"sensor":[244],"diagnostics.":[249]},"counts_by_year":[],"updated_date":"2026-07-07T14:30:12.667765","created_date":"2025-12-01T00:00:00"}