{"id":"https://openalex.org/W2967395846","doi":"https://doi.org/10.1109/cec.2019.8790249","title":"User and Task Identification of Smartwatch Data with an Ensemble of Nonlinear Symbolic Models","display_name":"User and Task Identification of Smartwatch Data with an Ensemble of Nonlinear Symbolic Models","publication_year":2019,"publication_date":"2019-06-01","ids":{"openalex":"https://openalex.org/W2967395846","doi":"https://doi.org/10.1109/cec.2019.8790249","mag":"2967395846"},"language":"en","primary_location":{"id":"doi:10.1109/cec.2019.8790249","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2019.8790249","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Congress on Evolutionary Computation (CEC)","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/A5101863280","display_name":"James Alexander Hughes","orcid":"https://orcid.org/0000-0003-1397-4317"},"institutions":[{"id":"https://openalex.org/I197191942","display_name":"St. Francis Xavier University","ror":"https://ror.org/01wcaxs37","country_code":"CA","type":"education","lineage":["https://openalex.org/I197191942"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"James Alexander Hughes","raw_affiliation_strings":["Mathematics, Statistics, and Computer Science, St. Francis Xavier University, Antigonish, Nova Scotia, Canada"],"affiliations":[{"raw_affiliation_string":"Mathematics, Statistics, and Computer Science, St. Francis Xavier University, Antigonish, Nova Scotia, Canada","institution_ids":["https://openalex.org/I197191942"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020474806","display_name":"Joseph Alexander Brown","orcid":"https://orcid.org/0000-0002-6513-4929"},"institutions":[{"id":"https://openalex.org/I197191942","display_name":"St. Francis Xavier University","ror":"https://ror.org/01wcaxs37","country_code":"CA","type":"education","lineage":["https://openalex.org/I197191942"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Joseph Alexander Brown","raw_affiliation_strings":["Mathematics, Statistics, and Computer Science, St. Francis Xavier University, Antigonish, Nova Scotia, Canada"],"affiliations":[{"raw_affiliation_string":"Mathematics, Statistics, and Computer Science, St. Francis Xavier University, Antigonish, Nova Scotia, Canada","institution_ids":["https://openalex.org/I197191942"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070522496","display_name":"Adil Khan","orcid":"https://orcid.org/0000-0003-2220-8518"},"institutions":[{"id":"https://openalex.org/I197191942","display_name":"St. Francis Xavier University","ror":"https://ror.org/01wcaxs37","country_code":"CA","type":"education","lineage":["https://openalex.org/I197191942"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Adil Mehmood Khan","raw_affiliation_strings":["Mathematics, Statistics, and Computer Science, St. Francis Xavier University, Antigonish, Nova Scotia, Canada"],"affiliations":[{"raw_affiliation_string":"Mathematics, Statistics, and Computer Science, St. Francis Xavier University, Antigonish, Nova Scotia, Canada","institution_ids":["https://openalex.org/I197191942"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101832436","display_name":"Asad Masood Khattak","orcid":"https://orcid.org/0000-0001-6949-3577"},"institutions":[{"id":"https://openalex.org/I197191942","display_name":"St. Francis Xavier University","ror":"https://ror.org/01wcaxs37","country_code":"CA","type":"education","lineage":["https://openalex.org/I197191942"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Asad Masood Khattak","raw_affiliation_strings":["Mathematics, Statistics, and Computer Science, St. Francis Xavier University, Antigonish, Nova Scotia, Canada"],"affiliations":[{"raw_affiliation_string":"Mathematics, Statistics, and Computer Science, St. Francis Xavier University, Antigonish, Nova Scotia, Canada","institution_ids":["https://openalex.org/I197191942"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5059512715","display_name":"Mark Daley","orcid":"https://orcid.org/0000-0002-6939-9772"},"institutions":[{"id":"https://openalex.org/I197191942","display_name":"St. Francis Xavier University","ror":"https://ror.org/01wcaxs37","country_code":"CA","type":"education","lineage":["https://openalex.org/I197191942"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Mark Daley","raw_affiliation_strings":["Mathematics, Statistics, and Computer Science, St. Francis Xavier University, Antigonish, Nova Scotia, Canada"],"affiliations":[{"raw_affiliation_string":"Mathematics, Statistics, and Computer Science, St. Francis Xavier University, Antigonish, Nova Scotia, Canada","institution_ids":["https://openalex.org/I197191942"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5101863280"],"corresponding_institution_ids":["https://openalex.org/I197191942"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07507388,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2506","last_page":"2513"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9955000281333923,"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"}},"topics":[{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9955000281333923,"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/T12222","display_name":"IoT-based Smart Home Systems","score":0.9736999869346619,"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9508000016212463,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7116845846176147},{"id":"https://openalex.org/keywords/nonlinear-system","display_name":"Nonlinear system","score":0.6404261589050293},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6019552946090698},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5810468196868896},{"id":"https://openalex.org/keywords/symbolic-regression","display_name":"Symbolic regression","score":0.5718896389007568},{"id":"https://openalex.org/keywords/genetic-programming","display_name":"Genetic programming","score":0.5652741193771362},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5645564198493958},{"id":"https://openalex.org/keywords/model-selection","display_name":"Model selection","score":0.5509096384048462},{"id":"https://openalex.org/keywords/linear-model","display_name":"Linear model","score":0.5334630012512207},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.532687246799469},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.52596116065979},{"id":"https://openalex.org/keywords/kinematics","display_name":"Kinematics","score":0.4915178716182709},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.48119503259658813},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4793734848499298},{"id":"https://openalex.org/keywords/nonlinear-model","display_name":"Nonlinear model","score":0.469287246465683},{"id":"https://openalex.org/keywords/system-identification","display_name":"System identification","score":0.41533324122428894},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1508520245552063}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7116845846176147},{"id":"https://openalex.org/C158622935","wikidata":"https://www.wikidata.org/wiki/Q660848","display_name":"Nonlinear system","level":2,"score":0.6404261589050293},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6019552946090698},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5810468196868896},{"id":"https://openalex.org/C2776400721","wikidata":"https://www.wikidata.org/wiki/Q18171762","display_name":"Symbolic regression","level":3,"score":0.5718896389007568},{"id":"https://openalex.org/C110332635","wikidata":"https://www.wikidata.org/wiki/Q629498","display_name":"Genetic programming","level":2,"score":0.5652741193771362},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5645564198493958},{"id":"https://openalex.org/C93959086","wikidata":"https://www.wikidata.org/wiki/Q6888345","display_name":"Model selection","level":2,"score":0.5509096384048462},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.5334630012512207},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.532687246799469},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.52596116065979},{"id":"https://openalex.org/C39920418","wikidata":"https://www.wikidata.org/wiki/Q11476","display_name":"Kinematics","level":2,"score":0.4915178716182709},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.48119503259658813},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4793734848499298},{"id":"https://openalex.org/C2984755018","wikidata":"https://www.wikidata.org/wiki/Q17118374","display_name":"Nonlinear model","level":3,"score":0.469287246465683},{"id":"https://openalex.org/C119247159","wikidata":"https://www.wikidata.org/wiki/Q1366192","display_name":"System identification","level":3,"score":0.41533324122428894},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1508520245552063},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cec.2019.8790249","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cec.2019.8790249","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Congress on Evolutionary Computation (CEC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W164465396","https://openalex.org/W1819536205","https://openalex.org/W1964814818","https://openalex.org/W1966580198","https://openalex.org/W1969787194","https://openalex.org/W2009135422","https://openalex.org/W2018157642","https://openalex.org/W2035787713","https://openalex.org/W2052186553","https://openalex.org/W2097204767","https://openalex.org/W2115629999","https://openalex.org/W2137604415","https://openalex.org/W2149695944","https://openalex.org/W2158441306","https://openalex.org/W2168490357","https://openalex.org/W2170808194","https://openalex.org/W2199551460","https://openalex.org/W2201408361","https://openalex.org/W2554023393","https://openalex.org/W2559620539","https://openalex.org/W2856467269","https://openalex.org/W6683036876"],"related_works":["https://openalex.org/W2968285896","https://openalex.org/W2381504162","https://openalex.org/W1567571923","https://openalex.org/W2472646430","https://openalex.org/W2610450612","https://openalex.org/W2549153708","https://openalex.org/W1964607451","https://openalex.org/W2897801744","https://openalex.org/W2147355282","https://openalex.org/W2005642789"],"abstract_inverted_index":{"Smart":[0],"devices":[1],"are":[2],"becoming":[3],"more":[4,113,149,187],"universally":[5],"adopted":[6],"and":[7,13,17,78,116],"can":[8,42],"be":[9],"used":[10],"to":[11,52,80,112,162,185],"track":[12],"model":[14,120,141,174,189],"user":[15],"activity":[16],"monitor":[18,53],"for":[19,123,177],"abnormalities.":[20],"Deviations":[21],"from":[22],"what":[23],"is":[24,31],"expected":[25],"may":[26],"indicate":[27],"that":[28,34,171],"a":[29,50,139,172,186],"fall":[30],"imminent":[32],"or":[33],"an":[35],"injury":[36],"has":[37],"been":[38],"sustained.":[39],"Healthcare":[40],"practitioners":[41],"use":[43],"descriptive":[44,63],"models":[45,66,75,87,109,134,150,159],"of":[46,67,103,107,133],"human":[47,68],"kinematics":[48,69],"as":[49],"tool":[51],"patient":[54],"recovery.":[55],"This":[56],"work":[57,60],"extends":[58],"previous":[59],"which":[61],"generated":[62],"nonlinear":[64,82,98,108],"symbolic":[65],"with":[70],"genetic":[71],"programming.":[72],"Previously,":[73],"linear":[74,86],"were":[76,93,110,126,135,160],"developed":[77],"compared":[79,184],"the":[81,85,89,97,104,124,152,178],"models.":[83,99],"Although":[84],"fit":[88,115],"data":[90],"well,":[91],"they":[92],"significantly":[94,136,164],"worse":[95],"than":[96,138],"In":[100],"this":[101],"phase":[102],"project,":[105],"ensembles":[106,125,132,179],"created":[111],"accurately":[114],"classify":[117],"data.":[118],"Different":[119],"selection":[121,175,190],"strategies":[122],"investigated.":[127],"As":[128],"one":[129],"would":[130],"expect,":[131],"better":[137,155,165],"single":[140],"classifier.":[142],"It":[143,167],"was":[144,168],"also":[145,169],"observed":[146,170],"that,":[147],"although":[148],"in":[151],"ensemble":[153],"yielded":[154],"results,":[156],"only":[157],"2":[158],"required":[161],"obtain":[163],"results.":[166],"random":[173],"strategy":[176],"produced":[180],"competitive":[181],"results":[182],"when":[183],"rigorous":[188],"strategy.":[191]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}