{"id":"https://openalex.org/W2761552164","doi":"https://doi.org/10.3390/s17102328","title":"Smart Annotation of Cyclic Data Using Hierarchical Hidden Markov Models","display_name":"Smart Annotation of Cyclic Data Using Hierarchical Hidden Markov Models","publication_year":2017,"publication_date":"2017-10-13","ids":{"openalex":"https://openalex.org/W2761552164","doi":"https://doi.org/10.3390/s17102328","mag":"2761552164","pmid":"https://pubmed.ncbi.nlm.nih.gov/29027973"},"language":"en","primary_location":{"id":"doi:10.3390/s17102328","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s17102328","pdf_url":"https://www.mdpi.com/1424-8220/17/10/2328/pdf?version=1507901761","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/17/10/2328/pdf?version=1507901761","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073414196","display_name":"Christine F. Martindale","orcid":"https://orcid.org/0000-0002-9397-5944"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Christine Martindale","raw_affiliation_strings":["Machine Learning and Data Analytics Lab, Department of Computer Science, Friedrich-Alexander University Erlangen-N\u00fcrnberg (FAU), 91054 Erlangen, Germany"],"raw_orcid":"https://orcid.org/0000-0002-9397-5944","affiliations":[{"raw_affiliation_string":"Machine Learning and Data Analytics Lab, Department of Computer Science, Friedrich-Alexander University Erlangen-N\u00fcrnberg (FAU), 91054 Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018554865","display_name":"Florian Hoenig","orcid":null},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Florian Hoenig","raw_affiliation_strings":["Speech Group, Department of Computer Science, Friedrich-Alexander-University Erlangen-N\u00fcrnberg (FAU), 91054 Erlangen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Speech Group, Department of Computer Science, Friedrich-Alexander-University Erlangen-N\u00fcrnberg (FAU), 91054 Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067946069","display_name":"Christina Strohrmann","orcid":null},"institutions":[{"id":"https://openalex.org/I889804353","display_name":"Robert Bosch (Germany)","ror":"https://ror.org/01fe0jt45","country_code":"DE","type":"company","lineage":["https://openalex.org/I889804353"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christina Strohrmann","raw_affiliation_strings":["Bosch Sensortec GmbH, Gerhard-Kindler-Strasse 9, 72770 Reutlingen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Bosch Sensortec GmbH, Gerhard-Kindler-Strasse 9, 72770 Reutlingen, Germany","institution_ids":["https://openalex.org/I889804353"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014144494","display_name":"Bjoern M. Eskofier","orcid":"https://orcid.org/0000-0002-0417-0336"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Bjoern Eskofier","raw_affiliation_strings":["Machine Learning and Data Analytics Lab, Department of Computer Science, Friedrich-Alexander University Erlangen-N\u00fcrnberg (FAU), 91054 Erlangen, Germany"],"raw_orcid":"https://orcid.org/0000-0002-0417-0336","affiliations":[{"raw_affiliation_string":"Machine Learning and Data Analytics Lab, Department of Computer Science, Friedrich-Alexander University Erlangen-N\u00fcrnberg (FAU), 91054 Erlangen, Germany","institution_ids":["https://openalex.org/I181369854"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5073414196"],"corresponding_institution_ids":["https://openalex.org/I181369854"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":1392,"currency":"EUR","value_usd":1501},"fwci":0.8317,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.82767723,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"17","issue":"10","first_page":"2328","last_page":"2328"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9986000061035156,"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":0.9986000061035156,"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/T11667","display_name":"Advanced Chemical Sensor Technologies","score":0.996399998664856,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/annotation","display_name":"Annotation","score":0.7468736171722412},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7230585813522339},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.7004895806312561},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6071649193763733},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5659461617469788},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44476965069770813},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4416927695274353},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.42254140973091125}],"concepts":[{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.7468736171722412},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7230585813522339},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.7004895806312561},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6071649193763733},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5659461617469788},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44476965069770813},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4416927695274353},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.42254140973091125}],"mesh":[],"locations_count":7,"locations":[{"id":"doi:10.3390/s17102328","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s17102328","pdf_url":"https://www.mdpi.com/1424-8220/17/10/2328/pdf?version=1507901761","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:29027973","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/29027973","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":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:aleph.bib-bvb.de:BVB01-030302115","is_oa":false,"landing_page_url":"http://d-nb.info/1154596052/34","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"software, multimedia"},{"id":"pmh:oai:doaj.org/article:e4018a16df104357bd20dd35f70a785f","is_oa":true,"landing_page_url":"https://doaj.org/article/e4018a16df104357bd20dd35f70a785f","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 17, Iss 10, p 2328 (2017)","raw_type":"article"},{"id":"pmh:oai:europepmc.org:4602241","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/5676753","pdf_url":null,"source":{"id":"https://openalex.org/S4306400806","display_name":"Europe PMC (PubMed Central)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1303153112","host_organization_name":"European Bioinformatics Institute","host_organization_lineage":["https://openalex.org/I1303153112"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},{"id":"pmh:oai:mdpi.com:/1424-8220/17/10/2328/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s17102328","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 17; Issue 10; Pages: 2328","raw_type":"Text"},{"id":"pmh:oai:ub.uni-erlangen.de-opus:9526","is_oa":true,"landing_page_url":"https://opus4.kobv.de/opus4-fau/frontdoor/index/index/docId/9526","pdf_url":null,"source":{"id":"https://openalex.org/S4306402340","display_name":"OPUS FAU (Kooperativer Bibliotheksverbund Berlin-Brandenburg (KOBV), on behalf of the Universit\u00e4tsbibliothek Erlangen-N\u00fcrnberg)","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":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/s17102328","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s17102328","pdf_url":"https://www.mdpi.com/1424-8220/17/10/2328/pdf?version=1507901761","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1050948393","https://openalex.org/W1636244751","https://openalex.org/W1953802779","https://openalex.org/W1963796473","https://openalex.org/W1976628879","https://openalex.org/W1978383016","https://openalex.org/W1987068050","https://openalex.org/W2008891225","https://openalex.org/W2013337604","https://openalex.org/W2054665642","https://openalex.org/W2057395988","https://openalex.org/W2069397622","https://openalex.org/W2076266873","https://openalex.org/W2087048290","https://openalex.org/W2092012469","https://openalex.org/W2109485196","https://openalex.org/W2111737705","https://openalex.org/W2124823771","https://openalex.org/W2125838338","https://openalex.org/W2148010363","https://openalex.org/W2161562001","https://openalex.org/W2167274237","https://openalex.org/W2167866158","https://openalex.org/W2212776954","https://openalex.org/W2214422405","https://openalex.org/W2222399534","https://openalex.org/W2237739092","https://openalex.org/W2258968934","https://openalex.org/W2285292066","https://openalex.org/W2396658633","https://openalex.org/W2507418274","https://openalex.org/W2516027932","https://openalex.org/W2581129691","https://openalex.org/W3098293252","https://openalex.org/W4230452892","https://openalex.org/W6672218648","https://openalex.org/W6675412655"],"related_works":["https://openalex.org/W2361861616","https://openalex.org/W2263699433","https://openalex.org/W2377979023","https://openalex.org/W2218034408","https://openalex.org/W2392921965","https://openalex.org/W2053269318","https://openalex.org/W2358755282","https://openalex.org/W2364370872","https://openalex.org/W2097963413","https://openalex.org/W1974738623"],"abstract_inverted_index":{"Cyclic":[0],"signals":[1],"are":[2],"an":[3],"intrinsic":[4],"part":[5],"of":[6,19,68,86,98,107,109,130,159,188,208,217,222,225,236,241],"daily":[7],"life,":[8],"such":[9,26,35,228],"as":[10,27,36,229],"human":[11,198],"motion":[12],"and":[13,31,149],"heart":[14],"activity.":[15],"The":[16,102,140],"detailed":[17],"analysis":[18,30,240],"them":[20],"is":[21,92,123],"important":[22],"for":[23,32,42,88,197,206],"clinical":[24],"applications":[25,34],"pathological":[28],"gait":[29],"sports":[33],"performance":[37],"analysis.":[38],"Labeled":[39],"training":[40,207,218],"data":[41,48,70,95,111,165],"algorithms":[43],"that":[44,82],"analyze":[45,233],"these":[46],"cyclic":[47,110],"come":[49],"at":[50],"a":[51,78,113,126,137,169,219],"high":[52],"annotation":[53,80,190,215],"cost":[54,85,216],"due":[55],"to":[56,94,136,146,167,177,232],"only":[57],"limited":[58,164],"annotations":[59],"available":[60],"under":[61,71],"laboratory":[62,100],"conditions":[63],"or":[64,239],"requiring":[65],"manual":[66],"segmentation":[67,209],"the":[69,153,157,185,195,201,214,234],"less":[72],"restricted":[73],"conditions.":[74,101],"This":[75,172],"paper":[76],"presents":[77],"smart":[79],"method":[81,103,183],"reduces":[83,194],"this":[84],"labeling":[87,202],"sensor-based":[89],"data,":[90,155],"which":[91],"applicable":[93],"collected":[96],"outside":[97],"strict":[99],"uses":[104],"semi-supervised":[105,182],"learning":[106],"sections":[108],"with":[112],"known":[114],"cycle":[115,226],"number.":[116],"A":[117],"hierarchical":[118],"hidden":[119],"Markov":[120],"model":[121,142,220],"(hHMM)":[122],"used,":[124],"achieving":[125],"mean":[127],"absolute":[128],"error":[129,199],"0.041":[131],"\u00b1":[132],"0.020":[133],"s":[134],"relative":[135],"manually-annotated":[138],"reference.":[139],"resulting":[141],"was":[143],"also":[144,212],"used":[145],"simultaneously":[147],"segment":[148],"classify":[150],"continuous,":[151],"'in":[152],"wild'":[154],"demonstrating":[156],"applicability":[158],"using":[160],"hHMM,":[161],"trained":[162],"on":[163],"sections,":[166],"label":[168],"complete":[170],"dataset.":[171],"technique":[173],"achieved":[174],"comparable":[175],"results":[176],"its":[178],"fully-supervised":[179],"equivalent.":[180],"Our":[181],"has":[184],"significant":[186],"advantage":[187],"reduced":[189],"cost.":[191],"Furthermore,":[192],"it":[193],"opportunity":[196],"in":[200],"process":[203],"normally":[204],"required":[205],"algorithms.":[210],"It":[211],"lowers":[213],"capable":[221],"continuous":[223],"monitoring":[224],"characteristics":[227],"those":[230],"employed":[231],"progress":[235],"movement":[237],"disorders":[238],"running":[242],"technique.":[243]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":3}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
