{"id":"https://openalex.org/W4200212632","doi":"https://doi.org/10.1109/embc46164.2021.9629737","title":"Clustering and Feature Analysis of Smartphone Data for Depression Monitoring","display_name":"Clustering and Feature Analysis of Smartphone Data for Depression Monitoring","publication_year":2021,"publication_date":"2021-11-01","ids":{"openalex":"https://openalex.org/W4200212632","doi":"https://doi.org/10.1109/embc46164.2021.9629737","pmid":"https://pubmed.ncbi.nlm.nih.gov/34891251"},"language":"en","primary_location":{"id":"doi:10.1109/embc46164.2021.9629737","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc46164.2021.9629737","pdf_url":null,"source":{"id":"https://openalex.org/S4363607750","display_name":"2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","pubmed"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Binh Nguyen","orcid":null},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Binh Nguyen","raw_affiliation_strings":["Ryerson Univerity, Toronto, ON"],"affiliations":[{"raw_affiliation_string":"Ryerson Univerity, Toronto, ON","institution_ids":["https://openalex.org/I530967"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Sharadha Kolappan","orcid":null},"institutions":[{"id":"https://openalex.org/I1297363086","display_name":"St. Michael's Hospital","ror":"https://ror.org/04skqfp25","country_code":"CA","type":"healthcare","lineage":["https://openalex.org/I1297363086","https://openalex.org/I4399598460"]},{"id":"https://openalex.org/I4210163656","display_name":"St Michaels Hospital","ror":"https://ror.org/02459py43","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I4210163656"]}],"countries":["CA","GB"],"is_corresponding":false,"raw_author_name":"Sharadha Kolappan","raw_affiliation_strings":["Interventional Psychiatry Program, St. Michael\u2019s Hospital, Toronto"],"affiliations":[{"raw_affiliation_string":"Interventional Psychiatry Program, St. Michael\u2019s Hospital, Toronto","institution_ids":["https://openalex.org/I1297363086","https://openalex.org/I4210163656"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Venkat Bhat","orcid":null},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]},{"id":"https://openalex.org/I4210163656","display_name":"St Michaels Hospital","ror":"https://ror.org/02459py43","country_code":"GB","type":"healthcare","lineage":["https://openalex.org/I4210163656"]},{"id":"https://openalex.org/I1297363086","display_name":"St. Michael's Hospital","ror":"https://ror.org/04skqfp25","country_code":"CA","type":"healthcare","lineage":["https://openalex.org/I1297363086","https://openalex.org/I4399598460"]}],"countries":["CA","GB"],"is_corresponding":false,"raw_author_name":"Venkat Bhat","raw_affiliation_strings":["Interventional Psychiatry Program, St. Michael\u2019s Hospital, Toronto","University of Toronto, Toronto, ON"],"affiliations":[{"raw_affiliation_string":"Interventional Psychiatry Program, St. Michael\u2019s Hospital, Toronto","institution_ids":["https://openalex.org/I1297363086","https://openalex.org/I4210163656"]},{"raw_affiliation_string":"University of Toronto, Toronto, ON","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"last","author":{"id":null,"display_name":"Sridhar Krishnan","orcid":null},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Sridhar Krishnan","raw_affiliation_strings":["Ryerson Univerity, Toronto, ON"],"affiliations":[{"raw_affiliation_string":"Ryerson Univerity, Toronto, ON","institution_ids":["https://openalex.org/I530967"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I530967"],"apc_list":null,"apc_paid":null,"fwci":2.7574,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.90140845,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"2021","issue":null,"first_page":"113","last_page":"116"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11519","display_name":"Digital Mental Health Interventions","score":0.9344000220298767,"subfield":{"id":"https://openalex.org/subfields/3202","display_name":"Applied 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/T11519","display_name":"Digital Mental Health Interventions","score":0.9344000220298767,"subfield":{"id":"https://openalex.org/subfields/3202","display_name":"Applied 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/T12488","display_name":"Mental Health via Writing","score":0.024399999529123306,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social 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/T10667","display_name":"Emotion and Mood Recognition","score":0.023000000044703484,"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/cluster-analysis","display_name":"Cluster analysis","score":0.5327000021934509},{"id":"https://openalex.org/keywords/categorization","display_name":"Categorization","score":0.5101000070571899},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.47909998893737793},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.4555000066757202},{"id":"https://openalex.org/keywords/redundancy","display_name":"Redundancy (engineering)","score":0.44679999351501465},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.41589999198913574},{"id":"https://openalex.org/keywords/data-collection","display_name":"Data collection","score":0.40529999136924744},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.40400001406669617}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6955000162124634},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5327000021934509},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5181000232696533},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.5101000070571899},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5040000081062317},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.47909998893737793},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.4555000066757202},{"id":"https://openalex.org/C152124472","wikidata":"https://www.wikidata.org/wiki/Q1204361","display_name":"Redundancy (engineering)","level":2,"score":0.44679999351501465},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.41589999198913574},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.40529999136924744},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.40400001406669617},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4004000127315521},{"id":"https://openalex.org/C2777615720","wikidata":"https://www.wikidata.org/wiki/Q11888847","display_name":"Prioritization","level":2,"score":0.3880000114440918},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37529999017715454},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.37400001287460327},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.32710000872612},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3160000145435333},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.3046000003814697},{"id":"https://openalex.org/C7545210","wikidata":"https://www.wikidata.org/wiki/Q838123","display_name":"Data redundancy","level":2,"score":0.2720000147819519},{"id":"https://openalex.org/C2780724565","wikidata":"https://www.wikidata.org/wiki/Q5227256","display_name":"Data classification","level":2,"score":0.262800008058548},{"id":"https://openalex.org/C66882249","wikidata":"https://www.wikidata.org/wiki/Q169336","display_name":"Homogeneous","level":2,"score":0.2597000002861023},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.257999986410141}],"mesh":[{"descriptor_ui":"D000068997","descriptor_name":"Smartphone","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000068997","descriptor_name":"Smartphone","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000068997","descriptor_name":"Smartphone","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D003863","descriptor_name":"Depression","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D003863","descriptor_name":"Depression","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D003863","descriptor_name":"Depression","qualifier_ui":"Q000175","qualifier_name":"diagnosis","is_major_topic":true},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D006801","descriptor_name":"Humans","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008603","descriptor_name":"Mental Health","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008603","descriptor_name":"Mental Health","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D008603","descriptor_name":"Mental Health","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011795","descriptor_name":"Surveys and Questionnaires","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011795","descriptor_name":"Surveys and Questionnaires","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D011795","descriptor_name":"Surveys and Questionnaires","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D016000","descriptor_name":"Cluster Analysis","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/embc46164.2021.9629737","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc46164.2021.9629737","pdf_url":null,"source":{"id":"https://openalex.org/S4363607750","display_name":"2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:34891251","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/34891251","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320310153","display_name":"Ryerson University","ror":"https://ror.org/05g13zd79"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1894490285","https://openalex.org/W1921929190","https://openalex.org/W2005069458","https://openalex.org/W2010708932","https://openalex.org/W2021970732","https://openalex.org/W2066806488","https://openalex.org/W2154053567","https://openalex.org/W2154690800","https://openalex.org/W2156567116","https://openalex.org/W2592965535","https://openalex.org/W2738199199","https://openalex.org/W2794997027","https://openalex.org/W2912654919","https://openalex.org/W3000225498","https://openalex.org/W3012534461","https://openalex.org/W3034246939","https://openalex.org/W3177026772","https://openalex.org/W6726606036","https://openalex.org/W6729425918"],"related_works":[],"abstract_inverted_index":{"Modern":[0],"advancements":[1],"have":[2,123],"allowed":[3],"society":[4],"to":[5,74,84,112,130,153,157,172,174,202],"be":[6,131],"at":[7],"the":[8,16,62,110,154,159,164,176,193],"most":[9],"innovative":[10],"stages":[11],"of":[12,18,40,64,93,139,144,200,207],"technology":[13],"which":[14],"involves":[15],"possibility":[17],"multimodal":[19],"data":[20,41,51,73,95,120],"collection.":[21],"Dartmouth":[22],"dataset":[23,27,36],"is":[24,82,151],"a":[25,53,135,197,232],"rich":[26],"collected":[28],"over":[29],"10":[30,47],"weeks":[31],"from":[32,71],"60":[33],"participants.":[34],"The":[35,98,167],"includes":[37],"different":[38,48,165],"types":[39],"but":[42],"this":[43,142],"paper":[44,67],"focuses":[45],"on":[46,137,218],"smartphone":[49,72],"sensor":[50],"and":[52,105,115,222],"Patient":[54],"Health":[55],"Questionnaire":[56],"(PHQ)":[57],"9":[58],"survey":[59],"that":[60,161,186],"monitors":[61],"severity":[63],"depression.":[65,76],"This":[66,133],"extracts":[68],"key":[69],"features":[70,129,156,160,201,214],"identify":[75],"A":[77],"multi-view":[78],"bi-clustering":[79],"(MVBC)":[80],"algorithm":[81,99],"applied":[83,152],"categorize":[85],"homogeneous":[86],"behaviour":[87],"subgroups.":[88],"MVBC":[89,108,169],"takes":[90],"multiple":[91],"views":[92],"sensing":[94,155],"as":[96],"input.":[97],"inputs":[100],"three":[101],"views:":[102],"average,":[103],"trend,":[104],"location":[106],"views.":[107],"categorizes":[109],"subjects":[111],"low,":[113],"medium":[114],"high":[116,210],"PHQ-9":[117],"scores.":[118],"Real-world":[119],"collection":[121],"may":[122],"fewer":[124],"sensors,":[125],"allowing":[126],"for":[127,216,226],"less":[128],"extracted.":[132],"creates":[134],"focus":[136,217],"prioritization":[138],"features.":[140],"In":[141],"body":[143],"work,":[145],"minimum":[146],"redundancy":[147],"maximum":[148],"relevance":[149],"(mRMR)":[150],"prioritize":[158],"better":[162],"distinguish":[163],"groups.":[166],"resulting":[168],"are":[170],"compared":[171],"literature":[173],"support":[175],"categorized":[177],"clusters.":[178],"Decision":[179],"Tree":[180],"(DT)":[181],"10-fold":[182],"cross":[183],"validation":[184],"shows":[185],"our":[187],"method":[188],"can":[189],"classify":[190],"individuals":[191],"into":[192],"correct":[194],"subgroups":[195],"using":[196,231],"reduced":[198,213],"number":[199],"achieve":[203],"an":[204],"overall":[205],"accuracy":[206],"94.7\u00b11.62%.":[208],"Achieving":[209],"accuracies":[211],"with":[212],"allows":[215],"low":[219],"power":[220],"analysis":[221],"edge":[223],"computing":[224],"applications":[225],"long-term":[227],"mental":[228],"health":[229],"monitoring":[230],"smartphone.":[233]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2021-12-31T00:00:00"}