{"id":"https://openalex.org/W2550461445","doi":"https://doi.org/10.1109/iccsce.2015.7482183","title":"Estimation of BMI status via speech signals using short-term cepstral features","display_name":"Estimation of BMI status via speech signals using short-term cepstral features","publication_year":2015,"publication_date":"2015-11-01","ids":{"openalex":"https://openalex.org/W2550461445","doi":"https://doi.org/10.1109/iccsce.2015.7482183","mag":"2550461445"},"language":"en","primary_location":{"id":"doi:10.1109/iccsce.2015.7482183","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccsce.2015.7482183","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Control System, Computing and Engineering (ICCSCE)","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/A5029366739","display_name":"Chawki Berkai","orcid":null},"institutions":[{"id":"https://openalex.org/I65079550","display_name":"Universiti Malaysia Perlis","ror":"https://ror.org/00xmkb790","country_code":"MY","type":"education","lineage":["https://openalex.org/I65079550"]}],"countries":["MY"],"is_corresponding":true,"raw_author_name":"Chawki Berkai","raw_affiliation_strings":["School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia"],"affiliations":[{"raw_affiliation_string":"School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia","institution_ids":["https://openalex.org/I65079550"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061968330","display_name":"M. Hariharan","orcid":"https://orcid.org/0000-0002-8929-3473"},"institutions":[{"id":"https://openalex.org/I65079550","display_name":"Universiti Malaysia Perlis","ror":"https://ror.org/00xmkb790","country_code":"MY","type":"education","lineage":["https://openalex.org/I65079550"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"M. Hariharan","raw_affiliation_strings":["School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia"],"affiliations":[{"raw_affiliation_string":"School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia","institution_ids":["https://openalex.org/I65079550"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109484446","display_name":"Sazali Yaacob","orcid":null},"institutions":[{"id":"https://openalex.org/I4528857","display_name":"University of Kuala Lumpur","ror":"https://ror.org/026wwrx19","country_code":"MY","type":"education","lineage":["https://openalex.org/I4528857"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Sazali Yaacob","raw_affiliation_strings":["Universiti Kuala Lumpur, Malaysian Spanish Institute, Kulim, Kedah, Malaysia"],"affiliations":[{"raw_affiliation_string":"Universiti Kuala Lumpur, Malaysian Spanish Institute, Kulim, Kedah, Malaysia","institution_ids":["https://openalex.org/I4528857"]}]},{"author_position":"last","author":{"id":null,"display_name":"Mohd Iqbal Omar","orcid":null},"institutions":[{"id":"https://openalex.org/I65079550","display_name":"Universiti Malaysia Perlis","ror":"https://ror.org/00xmkb790","country_code":"MY","type":"education","lineage":["https://openalex.org/I65079550"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Mohd Iqbal Omar","raw_affiliation_strings":["School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia"],"affiliations":[{"raw_affiliation_string":"School of Mechatronic Engineering, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia","institution_ids":["https://openalex.org/I65079550"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5029366739"],"corresponding_institution_ids":["https://openalex.org/I65079550"],"apc_list":null,"apc_paid":null,"fwci":0.331,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.73555611,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"363","issue":null,"first_page":"195","last_page":"199"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10866","display_name":"Nutritional Studies and Diet","score":0.9833999872207642,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10866","display_name":"Nutritional Studies and Diet","score":0.9833999872207642,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12647","display_name":"Traditional Chinese Medicine Studies","score":0.9139000177383423,"subfield":{"id":"https://openalex.org/subfields/2707","display_name":"Complementary and alternative medicine"},"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/mel-frequency-cepstrum","display_name":"Mel-frequency cepstrum","score":0.5869851112365723},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.547019362449646},{"id":"https://openalex.org/keywords/body-mass-index","display_name":"Body mass index","score":0.5183244943618774},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5096004009246826},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4768058955669403},{"id":"https://openalex.org/keywords/cepstrum","display_name":"Cepstrum","score":0.4767542779445648},{"id":"https://openalex.org/keywords/overweight","display_name":"Overweight","score":0.4708774983882904},{"id":"https://openalex.org/keywords/underweight","display_name":"Underweight","score":0.4650496244430542},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44882920384407043},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44450613856315613},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.19293031096458435}],"concepts":[{"id":"https://openalex.org/C151989614","wikidata":"https://www.wikidata.org/wiki/Q440370","display_name":"Mel-frequency cepstrum","level":3,"score":0.5869851112365723},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.547019362449646},{"id":"https://openalex.org/C2780221984","wikidata":"https://www.wikidata.org/wiki/Q131191","display_name":"Body mass index","level":2,"score":0.5183244943618774},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5096004009246826},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4768058955669403},{"id":"https://openalex.org/C88485024","wikidata":"https://www.wikidata.org/wiki/Q1054571","display_name":"Cepstrum","level":2,"score":0.4767542779445648},{"id":"https://openalex.org/C2780586474","wikidata":"https://www.wikidata.org/wiki/Q332428","display_name":"Overweight","level":3,"score":0.4708774983882904},{"id":"https://openalex.org/C2781121325","wikidata":"https://www.wikidata.org/wiki/Q1146902","display_name":"Underweight","level":4,"score":0.4650496244430542},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44882920384407043},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44450613856315613},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.19293031096458435},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccsce.2015.7482183","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccsce.2015.7482183","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Control System, Computing and Engineering (ICCSCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7200000286102295,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W45106830","https://openalex.org/W1480487340","https://openalex.org/W1513833217","https://openalex.org/W1578856370","https://openalex.org/W1990946425","https://openalex.org/W2000216715","https://openalex.org/W2016880896","https://openalex.org/W2032423026","https://openalex.org/W2063673766","https://openalex.org/W2065265916","https://openalex.org/W2074712547","https://openalex.org/W2076451517","https://openalex.org/W2086106204","https://openalex.org/W2089011168","https://openalex.org/W2107599451","https://openalex.org/W2110226980","https://openalex.org/W2111348359","https://openalex.org/W2135346934","https://openalex.org/W2135965496","https://openalex.org/W2328015002","https://openalex.org/W4248880341"],"related_works":["https://openalex.org/W1897789714","https://openalex.org/W2520113602","https://openalex.org/W130814904","https://openalex.org/W2103497017","https://openalex.org/W2054438685","https://openalex.org/W2911488237","https://openalex.org/W798735226","https://openalex.org/W2166137611","https://openalex.org/W2411918094","https://openalex.org/W1752902896"],"abstract_inverted_index":{"Fatness":[0],"is":[1,32],"a":[2],"serious":[3],"health":[4],"problem":[5],"worldwide":[6],"because":[7],"of":[8,62,122,142,155],"the":[9,33,57,60,72,120,123,140,143,148,158],"danger":[10],"factors":[11],"associated":[12],"with":[13],"diseases":[14],"which":[15],"cause":[16],"permanent":[17],"psychological":[18],"effect.":[19],"To":[20],"classify":[21],"normal":[22],"weight,":[23],"overweight,":[24],"underweight":[25],"and":[26,36,52,83,87,89,103,113,129],"obesity,":[27],"body":[28],"mass":[29,65],"index":[30],"(BMI)":[31],"most":[34],"recognized":[35],"extensively":[37],"used":[38,118,137],"measurement.":[39],"BMI":[40,63,125,151],"measurement":[41],"has":[42],"its":[43,84],"limits":[44],"in":[45,50,54],"some":[46],"cases":[47],"like":[48],"overstatements":[49],"athletes,":[51],"underestimates":[53],"elderly.":[55],"Thus,":[56],"paper":[58],"reports":[59],"estimation":[61],"(body":[64],"index)":[66],"status":[67,152],"via":[68],"speech":[69,75],"signals":[70],"using":[71,157],"short-term":[73,159],"cesptral":[74],"feature":[76],"extraction":[77],"methods,":[78],"Mel-frequency":[79],"cepstral":[80,100,160],"coefficients":[81,101],"(MFCCs)":[82],"deltas":[85],"(Delta":[86],"Delta-Delta)":[88],"Linear":[90],"Prediction":[91],"Coding":[92],"(LPC)":[93],"based":[94],"Cepstral":[95],"parameters":[96],"(LPCs,":[97],"linear":[98],"prediction":[99],"-LPCCs":[102],"weighted":[104],"LPCCs).":[105],"Two":[106],"different":[107],"classifiers,":[108],"probabilistic":[109],"neural":[110],"network":[111],"(PNN)":[112],"k-nearest":[114],"neighbor":[115],"(KNN)":[116],"were":[117],"for":[119],"classification":[121,153],"three":[124],"statuses":[126],"(normal,":[127],"overweight":[128],"obese).":[130],"The":[131],"10-fold":[132],"cross":[133],"validation":[134],"method":[135],"was":[136],"to":[138],"validate":[139],"reliability":[141],"classifier":[144],"results.":[145],"PNN":[146],"gives":[147],"best":[149],"average":[150],"accuracy":[154],"87%":[156],"features.":[161]},"counts_by_year":[{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":1}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}