{"id":"https://openalex.org/W2493585148","doi":"https://doi.org/10.1109/bsn.2016.7516226","title":"A framework for probabilistic segmentation of continuous sensor signals","display_name":"A framework for probabilistic segmentation of continuous sensor signals","publication_year":2016,"publication_date":"2016-06-01","ids":{"openalex":"https://openalex.org/W2493585148","doi":"https://doi.org/10.1109/bsn.2016.7516226","mag":"2493585148"},"language":"en","primary_location":{"id":"doi:10.1109/bsn.2016.7516226","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bsn.2016.7516226","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 13th International Conference on Wearable and Implantable Body Sensor Networks (BSN)","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/A5042052128","display_name":"Haik Kalantarian","orcid":"https://orcid.org/0000-0002-7107-7908"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Haik Kalantarian","raw_affiliation_strings":["Department of Computer Science, University of California, Los Angeles"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of California, Los Angeles","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055086608","display_name":"Costas Sideris","orcid":null},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Costas Sideris","raw_affiliation_strings":["Department of Computer Science, University of California, Los Angeles"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of California, Los Angeles","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102933377","display_name":"Tuan Le","orcid":"https://orcid.org/0000-0002-3374-5979"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tuan Le","raw_affiliation_strings":["Department of Computer Science, University of California, Los Angeles"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of California, Los Angeles","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072823939","display_name":"Christine King","orcid":"https://orcid.org/0000-0002-7646-1028"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Christine King","raw_affiliation_strings":["Department of Computer Science, University of California, Los Angeles"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of California, Los Angeles","institution_ids":["https://openalex.org/I161318765"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078132977","display_name":"Majid Sarrafzadeh","orcid":"https://orcid.org/0000-0001-8407-8689"},"institutions":[{"id":"https://openalex.org/I161318765","display_name":"University of California, Los Angeles","ror":"https://ror.org/046rm7j60","country_code":"US","type":"education","lineage":["https://openalex.org/I161318765"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Majid Sarrafzadeh","raw_affiliation_strings":["Department of Computer Science, University of California, Los Angeles"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of California, Los Angeles","institution_ids":["https://openalex.org/I161318765"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5042052128"],"corresponding_institution_ids":["https://openalex.org/I161318765"],"apc_list":null,"apc_paid":null,"fwci":0.5044,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.63617959,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"5","issue":null,"first_page":"19","last_page":"24"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.9914000034332275,"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"}},{"id":"https://openalex.org/T11309","display_name":"Music and Audio Processing","score":0.9789000153541565,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/probabilistic-logic","display_name":"Probabilistic logic","score":0.8325006365776062},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8130331039428711},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7007033824920654},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5677526593208313},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5339233875274658},{"id":"https://openalex.org/keywords/market-segmentation","display_name":"Market segmentation","score":0.5164427757263184},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5006704330444336},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4813845455646515},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.45521894097328186},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.45042359828948975},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.43498438596725464},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.42090967297554016},{"id":"https://openalex.org/keywords/window","display_name":"Window (computing)","score":0.4138090908527374},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3302155137062073}],"concepts":[{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.8325006365776062},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8130331039428711},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7007033824920654},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5677526593208313},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5339233875274658},{"id":"https://openalex.org/C125308379","wikidata":"https://www.wikidata.org/wiki/Q363057","display_name":"Market segmentation","level":2,"score":0.5164427757263184},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5006704330444336},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4813845455646515},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.45521894097328186},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.45042359828948975},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.43498438596725464},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.42090967297554016},{"id":"https://openalex.org/C2778751112","wikidata":"https://www.wikidata.org/wiki/Q835016","display_name":"Window (computing)","level":2,"score":0.4138090908527374},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3302155137062073},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bsn.2016.7516226","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bsn.2016.7516226","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 13th International Conference on Wearable and Implantable Body Sensor Networks (BSN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7699999809265137,"display_name":"Zero hunger","id":"https://metadata.un.org/sdg/2"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W95351861","https://openalex.org/W126990733","https://openalex.org/W273955616","https://openalex.org/W1497813392","https://openalex.org/W1510526001","https://openalex.org/W1579410832","https://openalex.org/W1598033630","https://openalex.org/W1618905105","https://openalex.org/W1907380269","https://openalex.org/W1934290066","https://openalex.org/W2003530571","https://openalex.org/W2013621764","https://openalex.org/W2020881829","https://openalex.org/W2020994185","https://openalex.org/W2066919446","https://openalex.org/W2069035105","https://openalex.org/W2081754796","https://openalex.org/W2085662862","https://openalex.org/W2097054885","https://openalex.org/W2103568877","https://openalex.org/W2119683921","https://openalex.org/W2125860913","https://openalex.org/W2133990480","https://openalex.org/W2150423658","https://openalex.org/W2483430316","https://openalex.org/W2794062433","https://openalex.org/W6603882360","https://openalex.org/W6605176256","https://openalex.org/W6610017368","https://openalex.org/W6630424276","https://openalex.org/W6634528665","https://openalex.org/W6635717444","https://openalex.org/W6636501900","https://openalex.org/W6639866694","https://openalex.org/W6678456019"],"related_works":["https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W2352448290","https://openalex.org/W2380820513","https://openalex.org/W2913146933","https://openalex.org/W2372385138","https://openalex.org/W4296359239","https://openalex.org/W2101155126","https://openalex.org/W2043093291","https://openalex.org/W2363545964"],"abstract_inverted_index":{"Among":[0],"the":[1,5,13,25,70,93,107],"major":[2],"challenges":[3],"in":[4,62],"realization":[6],"of":[7,15,27,32,72,95,102],"practical":[8],"health":[9],"monitoring":[10],"systems":[11],"is":[12,75,80],"identification":[14],"short-duration":[16],"events":[17],"from":[18,99],"larger":[19],"signals.":[20],"Time-series":[21],"segmentation":[22],"refers":[23],"to":[24,44,104],"challenge":[26],"subdividing":[28],"a":[29,55,100],"continuous":[30],"stream":[31],"data":[33],"into":[34],"discrete":[35],"windows,":[36],"which":[37,63],"are":[38,66],"individually":[39],"processed":[40],"using":[41,82,106],"statistical":[42],"classifiers":[43],"recognize":[45],"various":[46],"activities":[47],"or":[48],"events.":[49],"In":[50],"this":[51],"paper,":[52],"we":[53],"propose":[54],"probabilistic":[56],"algorithm":[57,91],"for":[58],"segmenting":[59],"time-series":[60],"signals,":[61],"window":[64],"boundaries":[65],"dynamically":[67],"adjusted":[68],"when":[69],"probability":[71],"correct":[73],"classification":[74],"low.":[76],"Our":[77,87],"proposed":[78],"scheme":[79],"benchmarked":[81],"an":[83],"audio-based":[84],"nutrition-monitoring":[85],"case-study.":[86],"evaluation":[88],"shows":[89],"that":[90],"improves":[92],"number":[94],"correctly":[96],"classified":[97],"instances":[98],"baseline":[101],"75%":[103],"94%":[105],"RandomForest":[108],"classifier.":[109]},"counts_by_year":[{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
