{"id":"https://openalex.org/W7130542443","doi":"https://doi.org/10.1109/ictc66702.2025.11388356","title":"Explainable Time-Series Feature Engineering for Sleep Quality Prediction Using Lifelog Data","display_name":"Explainable Time-Series Feature Engineering for Sleep Quality Prediction Using Lifelog Data","publication_year":2025,"publication_date":"2025-10-14","ids":{"openalex":"https://openalex.org/W7130542443","doi":"https://doi.org/10.1109/ictc66702.2025.11388356"},"language":null,"primary_location":{"id":"doi:10.1109/ictc66702.2025.11388356","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictc66702.2025.11388356","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 16th International Conference on Information and Communication Technology Convergence (ICTC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5087528051","display_name":"Gwangseop Lee","orcid":"https://orcid.org/0000-0001-7522-1113"},"institutions":[{"id":"https://openalex.org/I24541011","display_name":"Soonchunhyang University","ror":"https://ror.org/03qjsrb10","country_code":"KR","type":"education","lineage":["https://openalex.org/I24541011"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Gwangseop Lee","raw_affiliation_strings":["Soonchunhyang University,Dept. AI and Big Data,Asan,Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Soonchunhyang University,Dept. AI and Big Data,Asan,Republic of Korea","institution_ids":["https://openalex.org/I24541011"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126442512","display_name":"Sungmin Choi","orcid":null},"institutions":[{"id":"https://openalex.org/I24541011","display_name":"Soonchunhyang University","ror":"https://ror.org/03qjsrb10","country_code":"KR","type":"education","lineage":["https://openalex.org/I24541011"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Sungmin Choi","raw_affiliation_strings":["Soonchunhyang University,Dept. AI and Big Data,Asan,Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Soonchunhyang University,Dept. AI and Big Data,Asan,Republic of Korea","institution_ids":["https://openalex.org/I24541011"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027662394","display_name":"Jiyoung Woo","orcid":"https://orcid.org/0000-0001-8231-0018"},"institutions":[{"id":"https://openalex.org/I24541011","display_name":"Soonchunhyang University","ror":"https://ror.org/03qjsrb10","country_code":"KR","type":"education","lineage":["https://openalex.org/I24541011"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jiyoung Woo","raw_affiliation_strings":["Soonchunhyang University,Dept. AI and Big Data,Asan,Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Soonchunhyang University,Dept. AI and Big Data,Asan,Republic of Korea","institution_ids":["https://openalex.org/I24541011"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I24541011"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1733","last_page":"1738"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.1972000002861023,"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":0.1972000002861023,"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/T10316","display_name":"Sleep and related disorders","score":0.19629999995231628,"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/T10234","display_name":"Obstructive Sleep Apnea Research","score":0.14869999885559082,"subfield":{"id":"https://openalex.org/subfields/2737","display_name":"Physiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/lifelog","display_name":"Lifelog","score":0.9362000226974487},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7062000036239624},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.5432999730110168},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46000000834465027},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.44130000472068787},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.42579999566078186},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.40290001034736633},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.4000999927520752}],"concepts":[{"id":"https://openalex.org/C176168674","wikidata":"https://www.wikidata.org/wiki/Q763835","display_name":"Lifelog","level":2,"score":0.9362000226974487},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7434999942779541},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7062000036239624},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6323999762535095},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.5432999730110168},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46000000834465027},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.44130000472068787},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.42579999566078186},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4108000099658966},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.40290001034736633},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.4000999927520752},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.396699994802475},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3926999866962433},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.3637999892234802},{"id":"https://openalex.org/C101814296","wikidata":"https://www.wikidata.org/wiki/Q5439685","display_name":"Feature model","level":3,"score":0.35679998993873596},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.3292999863624573},{"id":"https://openalex.org/C54290928","wikidata":"https://www.wikidata.org/wiki/Q4845080","display_name":"Wearable technology","level":3,"score":0.3073999881744385},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.27619999647140503},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.27559998631477356},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2718999981880188},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.2572999894618988}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ictc66702.2025.11388356","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ictc66702.2025.11388356","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 16th International Conference on Information and Communication Technology Convergence (ICTC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":1,"referenced_works":["https://openalex.org/W2295598076"],"related_works":[],"abstract_inverted_index":{"This":[0,109],"study":[1,110],"proposes":[2],"a":[3,120],"model":[4,50,84],"for":[5],"predicting":[6],"human":[7],"sleep":[8],"and":[9,37,41,54,65,68],"health":[10],"states":[11],"using":[12],"lifelog":[13,128],"data":[14,21],"collected":[15],"from":[16],"wearable":[17],"sensors.":[18],"The":[19,56],"time-series":[20,62],"are":[22,42],"transformed":[23],"into":[24,99],"static":[25,114],"features":[26,58],"through":[27,74],"various":[28],"statistical":[29],"methods,":[30],"such":[31],"as":[32,44,119],"rolling":[33],"mean,":[34],"variance,":[35],"IQR,":[36],"exponential":[38],"moving":[39],"average,":[40],"used":[43],"input":[45,57],"to":[46,105],"an":[47],"ensemble":[48,83],"classification":[49],"that":[51,81,112],"combines":[52],"LightGBM":[53],"CatBoost.":[55],"consist":[59],"of":[60,102],"both":[61],"sensor":[63],"statistics":[64],"date-derived":[66],"variables,":[67],"the":[69,82,100,106],"model\u2019s":[70,107],"performance":[71],"is":[72],"evaluated":[73],"5-fold":[75],"stratified":[76],"cross-validation.":[77],"Experimental":[78],"results":[79],"demonstrate":[80],"outperforms":[85],"individual":[86],"models":[87],"in":[88,123],"prediction":[89,125],"accuracy.":[90],"Furthermore,":[91],"SHAP-based":[92],"feature":[93,104,115],"importance":[94],"analysis":[95],"provides":[96],"visual":[97],"insight":[98],"contribution":[101],"each":[103],"predictions.":[108],"confirms":[111],"traditional":[113],"engineering":[116],"can":[117],"serve":[118],"strong":[121],"method":[122],"multi-target":[124],"tasks":[126],"involving":[127],"data.":[129]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-02-20T00:00:00"}