{"id":"https://openalex.org/W2553929800","doi":"https://doi.org/10.1109/spcom.2016.7746694","title":"Automatic classification of toco-signals: An approach towards comprehensive monitoring of labour progress","display_name":"Automatic classification of toco-signals: An approach towards comprehensive monitoring of labour progress","publication_year":2016,"publication_date":"2016-06-01","ids":{"openalex":"https://openalex.org/W2553929800","doi":"https://doi.org/10.1109/spcom.2016.7746694","mag":"2553929800"},"language":"en","primary_location":{"id":"doi:10.1109/spcom.2016.7746694","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spcom.2016.7746694","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Signal Processing and Communications (SPCOM)","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/A5088088522","display_name":"R Jyothi","orcid":null},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"R. Jyothi","raw_affiliation_strings":["Dept. of Biomedical Engineering M.I.T., Manipal University, Manipal, Karnataka, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Biomedical Engineering M.I.T., Manipal University, Manipal, Karnataka, India","institution_ids":["https://openalex.org/I164861460"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026360574","display_name":"Rijul Saurabh Soans","orcid":"https://orcid.org/0000-0002-7338-6210"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rijul Saurabh Soans","raw_affiliation_strings":["Manipal Academy of Higher Education, Manipal, Karnataka, IN"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Manipal Academy of Higher Education, Manipal, Karnataka, IN","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038269414","display_name":"Parvati Bhat","orcid":"https://orcid.org/0000-0001-6066-1685"},"institutions":[{"id":"https://openalex.org/I164861460","display_name":"Manipal Academy of Higher Education","ror":"https://ror.org/02xzytt36","country_code":"IN","type":"education","lineage":["https://openalex.org/I164861460"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Parvati V. Bhat","raw_affiliation_strings":["Dept. of Biomedical Engineering M.I.T., Manipal University, Manipal, Karnataka, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Biomedical Engineering M.I.T., Manipal University, Manipal, Karnataka, India","institution_ids":["https://openalex.org/I164861460"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.3249,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.8774959,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9405999779701233,"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"}},"topics":[{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9405999779701233,"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/oversampling","display_name":"Oversampling","score":0.6404269933700562},{"id":"https://openalex.org/keywords/dilation","display_name":"Dilation (metric space)","score":0.5871767401695251},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5220056176185608},{"id":"https://openalex.org/keywords/cervical-dilation","display_name":"Cervical dilation","score":0.5086889863014221},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4896402955055237},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4742645025253296},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.47182971239089966},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.46869587898254395},{"id":"https://openalex.org/keywords/contraction","display_name":"Contraction (grammar)","score":0.43458595871925354},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4102638065814972},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.36043477058410645},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3304503262042999},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.24323758482933044},{"id":"https://openalex.org/keywords/internal-medicine","display_name":"Internal medicine","score":0.12043261528015137},{"id":"https://openalex.org/keywords/pregnancy","display_name":"Pregnancy","score":0.11801230907440186},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.11572882533073425},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10140720009803772},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.0915336012840271}],"concepts":[{"id":"https://openalex.org/C197323446","wikidata":"https://www.wikidata.org/wiki/Q331222","display_name":"Oversampling","level":3,"score":0.6404269933700562},{"id":"https://openalex.org/C2780757906","wikidata":"https://www.wikidata.org/wiki/Q5276676","display_name":"Dilation (metric space)","level":2,"score":0.5871767401695251},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5220056176185608},{"id":"https://openalex.org/C2776622691","wikidata":"https://www.wikidata.org/wiki/Q5065331","display_name":"Cervical dilation","level":4,"score":0.5086889863014221},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4896402955055237},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4742645025253296},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.47182971239089966},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.46869587898254395},{"id":"https://openalex.org/C163415756","wikidata":"https://www.wikidata.org/wiki/Q126473","display_name":"Contraction (grammar)","level":2,"score":0.43458595871925354},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4102638065814972},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.36043477058410645},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3304503262042999},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.24323758482933044},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.12043261528015137},{"id":"https://openalex.org/C2779234561","wikidata":"https://www.wikidata.org/wiki/Q11995","display_name":"Pregnancy","level":2,"score":0.11801230907440186},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.11572882533073425},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10140720009803772},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0915336012840271},{"id":"https://openalex.org/C46973012","wikidata":"https://www.wikidata.org/wiki/Q28627","display_name":"Gestation","level":3,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/spcom.2016.7746694","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spcom.2016.7746694","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Conference on Signal Processing and Communications (SPCOM)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth","score":0.699999988079071}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W781122535","https://openalex.org/W1594031697","https://openalex.org/W1963827675","https://openalex.org/W1978211736","https://openalex.org/W1982597776","https://openalex.org/W2066061443","https://openalex.org/W2126034719","https://openalex.org/W2148143831","https://openalex.org/W2150465831","https://openalex.org/W2164488595","https://openalex.org/W2169650937","https://openalex.org/W2171630164","https://openalex.org/W2610804688","https://openalex.org/W2751318774","https://openalex.org/W2990168612","https://openalex.org/W6737333587","https://openalex.org/W6843735874","https://openalex.org/W6991957103","https://openalex.org/W6999455789"],"related_works":["https://openalex.org/W2766503024","https://openalex.org/W4206637278","https://openalex.org/W4386005305","https://openalex.org/W3025954877","https://openalex.org/W2943876554","https://openalex.org/W2089253238","https://openalex.org/W1977800811","https://openalex.org/W2470748766","https://openalex.org/W4377292361","https://openalex.org/W2091693456"],"abstract_inverted_index":{"Childbirth":[0],"is":[1,6,48,62],"an":[2,9,53,152],"intricate":[3],"process":[4],"which":[5,40],"marked":[7],"by":[8,32,148],"increased":[10],"cervical":[11],"dilation":[12],"rate":[13],"caused":[14],"due":[15],"to":[16,50,78,106,133,178,226,237],"steady":[17],"increments":[18],"in":[19,112,124,157,164],"the":[20,46,57,60,80,92,118,127,135,138,185,197,207,215,223,239],"frequency":[21,37],"and":[22,36,52,75,87,130,159,173,204,220,229],"strength":[23],"of":[24,59,99,102,108,137,154,181,187,201],"uterine":[25],"contractions.":[26],"The":[27,140,161,211],"contractions":[28,61,81,183],"may":[29,234],"be":[30,235],"characterized":[31],"its":[33],"strength,":[34],"duration":[35],"(count)":[38],"\u2014":[39,110],"are":[41,163,217],"monitored":[42],"through":[43],"Tocography.":[44],"However,":[45],"procedure":[47],"prone":[49],"subjectivity":[51],"automated":[54],"approach":[55],"for":[56,143,206,214],"classification":[58],"needed.":[63],"In":[64],"this":[65],"paper,":[66],"we":[67,90,116],"use":[68,117],"three":[69,83,165],"different":[70],"Weighted":[71],"K-Nearest":[72],"Neighbor":[73],"classifiers":[74],"Decision":[76,131,192],"Trees":[77,132,193],"classify":[79],"into":[82],"types:":[84],"Mild,":[85],"Moderate":[86,170],"Strong.":[88],"Further,":[89],"note":[91],"fact":[93],"that":[94],"our":[95],"training":[96],"data":[97],"consists":[98],"fewer":[100],"samples":[101,189],"Contractions":[103],"as":[104],"compared":[105],"those":[107],"Non-contractions":[109],"resulting":[111],"\u201cClass":[113],"Imbalance\u201d.":[114],"Hence,":[115],"Synthetic":[119],"Minority":[120],"Oversampling":[121],"Technique":[122],"(SMOTE)":[123],"conjunction":[125],"with":[126,199],"K-NN":[128],"classifier":[129],"alleviate":[134],"problems":[136],"same.":[139],"ground":[141],"truth":[142],"Tocography":[144],"signals":[145],"was":[146,190],"established":[147],"a":[149,179],"doctor":[150],"having":[151],"experience":[153],"36":[155],"years":[156],"Obstetrics":[158],"Gynaecology.":[160],"annotations":[162],"categories:":[166],"Mild":[167],"(33":[168],"samples),":[169,176],"(64":[171],"samples)":[172],"Strong":[174],"(96":[175],"amounting":[177],"total":[180],"193":[182],"whereas":[184,222],"number":[186],"Non-contraction":[188],"1217.":[191],"using":[194],"SMOTE":[195],"performed":[196],"best":[198],"accuracies":[200],"95%,":[202],"98.25%":[203],"100%":[205,221,228],"aforementioned":[208],"categories,":[209],"respectively.":[210,231],"sensitivities":[212],"achieved":[213],"same":[216],"96.67%,":[218],"96.52%":[219],"specificities":[224],"amount":[225],"93.33%,":[227],"100%,":[230],"Our":[232],"method":[233],"used":[236],"monitor":[238],"labour":[240],"progress":[241],"efficiently.":[242]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}