{"id":"https://openalex.org/W2808568362","doi":null,"title":"Self-coach: an intelligent WBAN system for heart disease prediction using non-dominated sorting genetic algorithm","display_name":"Self-coach: an intelligent WBAN system for heart disease prediction using non-dominated sorting genetic algorithm","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2808568362","mag":"2808568362"},"language":"en","primary_location":{"id":"pmh:oai:research.library.mun.ca:12706","doi":null,"is_oa":true,"landing_page_url":"https://research.library.mun.ca/12706/1/thesis.pdf","pdf_url":"https://research.library.mun.ca/12706/1/thesis.pdf","source":{"id":"https://openalex.org/S4306401319","display_name":"Memorial University Research Repository (Memorial University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I130438778","host_organization_name":"Memorial University of Newfoundland","host_organization_lineage":["https://openalex.org/I130438778"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Thesis"},"volume":null,"type":"dissertation","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://research.library.mun.ca/12706/1/thesis.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5000432448","display_name":"Babak Emami-Abarghouei","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Babak Emami-Abarghouei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5000432448"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.6621000170707703,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11396","display_name":"Artificial Intelligence in Healthcare","score":0.6621000170707703,"subfield":{"id":"https://openalex.org/subfields/3605","display_name":"Health Information Management"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11932","display_name":"Wireless Body Area Networks","score":0.09759999811649323,"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.08889999985694885,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/wireless-body-area-networks","display_name":"wireless body area networks","score":0.8299999833106995},{"id":"https://openalex.org/keywords/heart-failure-prediction","display_name":"heart failure prediction","score":0.8960000276565552},{"id":"https://openalex.org/keywords/nsga-ii","display_name":"NSGA-II","score":0.8709999918937683},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"support vector machine","score":0.8429999947547913},{"id":"https://openalex.org/keywords/pareto-front","display_name":"Pareto front","score":0.7979999780654907},{"id":"https://openalex.org/keywords/patient-health-monitoring","display_name":"patient health monitoring","score":0.5730000138282776},{"id":"https://openalex.org/keywords/blood-pressure","display_name":"blood pressure","score":0.8460000157356262},{"id":"https://openalex.org/keywords/heart-rate","display_name":"heart rate","score":1.0},{"id":"https://openalex.org/keywords/tolerance-threshold","display_name":"tolerance threshold","score":0.6610000133514404},{"id":"https://openalex.org/keywords/multi-objective-optimization","display_name":"multi-objective optimization","score":0.7149999737739563},{"id":"https://openalex.org/keywords/wearable-sensors","display_name":"wearable sensors","score":0.6299999952316284},{"id":"https://openalex.org/keywords/early-diagnosis","display_name":"early diagnosis","score":0.5189999938011169},{"id":"https://openalex.org/keywords/health-status-classification","display_name":"health status classification","score":0.3190000057220459},{"id":"https://openalex.org/keywords/physiological-monitoring","display_name":"physiological monitoring","score":0.36500000953674316}],"concepts":[{"id":"https://openalex.org/C111696304","wikidata":"https://www.wikidata.org/wiki/Q2303697","display_name":"Sorting","level":2,"score":0.735194206237793},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.6906344890594482},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6462736129760742},{"id":"https://openalex.org/C8880873","wikidata":"https://www.wikidata.org/wiki/Q187787","display_name":"Genetic algorithm","level":2,"score":0.5608437061309814},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5321986079216003},{"id":"https://openalex.org/C88737568","wikidata":"https://www.wikidata.org/wiki/Q890056","display_name":"Body area network","level":3,"score":0.49933385848999023},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4099096655845642},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.399684876203537},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3975648880004883},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.36732348799705505},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3499177098274231},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.338165283203125},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.23294347524642944},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.09202030301094055}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:research.library.mun.ca:12706","doi":null,"is_oa":true,"landing_page_url":"https://research.library.mun.ca/12706/1/thesis.pdf","pdf_url":"https://research.library.mun.ca/12706/1/thesis.pdf","source":{"id":"https://openalex.org/S4306401319","display_name":"Memorial University Research Repository (Memorial University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I130438778","host_organization_name":"Memorial University of Newfoundland","host_organization_lineage":["https://openalex.org/I130438778"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Thesis"},{"id":"mag:2808568362","doi":null,"is_oa":false,"landing_page_url":"https://research.library.mun.ca/12706/","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:research.library.mun.ca:12706","doi":null,"is_oa":true,"landing_page_url":"https://research.library.mun.ca/12706/1/thesis.pdf","pdf_url":"https://research.library.mun.ca/12706/1/thesis.pdf","source":{"id":"https://openalex.org/S4306401319","display_name":"Memorial University Research Repository (Memorial University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I130438778","host_organization_name":"Memorial University of Newfoundland","host_organization_lineage":["https://openalex.org/I130438778"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Thesis"},"sustainable_development_goals":[{"score":0.9476000070571899,"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2808568362.pdf","grobid_xml":"https://content.openalex.org/works/W2808568362.grobid-xml"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W1487105423","https://openalex.org/W1548955532","https://openalex.org/W1570448133","https://openalex.org/W1578324001","https://openalex.org/W1602472400","https://openalex.org/W1607660464","https://openalex.org/W1673075472","https://openalex.org/W1966253115","https://openalex.org/W1969733464","https://openalex.org/W1977398789","https://openalex.org/W1982052569","https://openalex.org/W2000189213","https://openalex.org/W2013466870","https://openalex.org/W2034371351","https://openalex.org/W2049768409","https://openalex.org/W2050003166","https://openalex.org/W2061236554","https://openalex.org/W2079885394","https://openalex.org/W2087347434","https://openalex.org/W2092286251","https://openalex.org/W2095736475","https://openalex.org/W2097571405","https://openalex.org/W2114725328","https://openalex.org/W2116997550","https://openalex.org/W2118246375","https://openalex.org/W2120932898","https://openalex.org/W2124458090","https://openalex.org/W2126105956","https://openalex.org/W2131496831","https://openalex.org/W2134881335","https://openalex.org/W2136744557","https://openalex.org/W2141975087","https://openalex.org/W2150046657","https://openalex.org/W2151274019","https://openalex.org/W2152127951","https://openalex.org/W2162043657","https://openalex.org/W2165884492","https://openalex.org/W2167159964","https://openalex.org/W2260458337","https://openalex.org/W2270635011","https://openalex.org/W2325943429","https://openalex.org/W2403909940","https://openalex.org/W2488139503","https://openalex.org/W2497178056","https://openalex.org/W2532517666","https://openalex.org/W3021842026"],"related_works":["https://openalex.org/W4404326449","https://openalex.org/W4376492258","https://openalex.org/W4213245821","https://openalex.org/W6903677875","https://openalex.org/W4385835590","https://openalex.org/W1586022874","https://openalex.org/W3041814321","https://openalex.org/W4398180555","https://openalex.org/W2566887282","https://openalex.org/W7119479571"],"abstract_inverted_index":{"Wireless":[0,16],"Body":[1],"Area":[2],"Network":[3,18],"(WBAN)":[4],"is":[5,79,109,127,155,239,282,341,428,438],"a":[6,82,110,158,196,202,240,265,303,429,439,447,452],"new":[7,111,159,306,343,353,430],"technology":[8,431],"based":[9,119,163,222,350],"on":[10,120,164,223,276,351,404],"an":[11,121,128],"\\nadvanced":[12],"healthcare":[13,463,475],"system":[14,71,131],"and":[15,45,84,102,184,213,216,228,255,324,330,383,395,419,470],"Sensor":[17],"(WSN).":[19],"This":[20,168],"domain":[21],"has":[22,89,250],"\\nbeen":[23],"designed":[24],"for":[25,38,113,201,338,346,387,416,432,450,465],"monitoring":[26,41,63,130,414,474],"patients":[27],"using":[28,95,145],"their":[29],"physical":[30,46],"signals":[31],"by":[32,186,365],"providing":[33],"lowcost,":[34],"\\nwearable,":[35],"unobtrusive":[36],"solutions":[37],"the":[39,53,67,134,146,171,187,205,217,246,258,271,283,290,294,298,318,342,352,359,374,398,405,459,462],"continuous":[40],"of":[42,55,59,75,99,242,302,369,442,455,461],"cardiovascular":[43],"\\nhealth":[44],"activity":[47],"status.":[48],"Recent":[49],"studies":[50],"have":[51,231,390,423],"addressed":[52],"use":[54],"WBAN,":[56],"\\nby":[57],"means":[58],"real-time":[60,141],"comprehensive":[61],"health":[62,142,198,220,300,344,354,413],"systems":[64,78,118],"such":[65],"as":[66,157,264,270,471],"Personal":[68],"\\nHealth":[69],"Monitoring":[70],"(PHM).":[72],"The":[73,106,236],"aim":[74],"utilizing":[76,332],"these":[77,316,370],"to":[80,133,176],"provide":[81,411],"\\nfast":[83],"early":[85,114],"diagnosis;":[86],"however,":[87],"WBAN":[88,123],"not":[90],"fulfilled":[91],"its":[92,179,377],"potential":[93,197,299,335],"while":[94],"\\nthe":[96,165,211,277],"existing":[97],"methods":[98],"machine":[100],"learning":[101],"data":[103,436],"mining":[104],"techniques.":[105],"proposed":[107,156],"\\nmethod":[108],"framework":[112],"heart":[115,229,325,425],"failure":[116],"prediction":[117],"\\nintelligent":[122],"named":[124],"Self-Coach.":[125],"Self-Coach":[126,154],"intelligent":[129],"\\ndue":[132],"detection/prediction":[135],"method":[136,162,409],"it":[137],"uses,":[138],"which":[139,287,356,444],"provides":[140],"status":[143],"\\nmonitoring":[144],"Non-Dominated":[147],"Sorting":[148,190],"Genetic":[149,191],"Algorithm.":[150],"\\nIn":[151],"this":[152,281,408],"study,":[153],"medical":[160],"diagnosis":[161],"hybrid":[166],"approach.":[167],"approach":[169],"applies":[170],"Support":[172],"Vector":[173],"Machine":[174],"(SVM)":[175],"\\nclassification,":[177],"where":[178],"parameter":[180],"values":[181],"are":[182],"optimized":[183],"visualized":[185],"Non-":[188],"\\nDominated":[189],"Algorithm-II":[192],"(NSGA-II).":[193],"To":[194,314],"predict":[195],"\\ntolerance":[199],"threshold":[200,337],"particular":[203,304,348],"patient,":[204,305],"optimal":[206,237,272,360],"boundary":[207,238,273,381],"curve":[208,268,286],"between":[209],"both":[210],"healthy":[212],"unhealthy":[214,247],"class":[215,248,292],"patient's":[218,319],"possible":[219,307],"positions":[221,308],"\\nnew":[224],"conditions":[225,355],"(blood":[226,322],"pressure":[227,323],"rate)":[230,326],"been":[232,251,391],"explored":[233,384],"with":[234,253,257,312,397],"NSGA-II.":[235,313],"set":[241],"non-dominated":[243],"offspring":[244],"from":[245,293],"\\nthat":[249,347],"generated":[252,311],"NSGA-II":[254],"verified":[256,392],"SVM.":[259],"These":[260],"members":[261],"\\nare":[262],"plotted":[263],"Pareto":[266],"Front":[267],"known":[269],"curve.":[274],"Based":[275,403],"SVM":[278,394],"classification":[279,401],"results,":[280,407],"most":[284],"fitted":[285],"can":[288,410],"separate":[289],"\\nhealthy":[291],"unhealthy.":[295],"\\nTo":[296,372],"explore":[297],"position":[301,345],"\\nwill":[309],"be":[310,328,363],"generate":[315],"points,":[317],"dynamic":[320],"\\ndata":[321],"will":[327,357],"increased":[329],"simulated":[331],"NSGAII.":[333],"\\nThe":[334],"tolerance":[336,385],"each":[339,388],"patient":[340,349],"cross":[358],"\\nboundary":[361],"or":[362],"dominated":[364],"at":[366],"least":[367],"one":[368],"members.":[371],"evaluate":[373],"Self-Coach's":[375],"performance,":[376],"experimental":[378],"results":[379],"(optimal":[380],"\\nmembers":[382],"thresholds":[386],"individual)":[389],"\\nusing":[393],"compared":[396],"raw":[399],"dataset":[400],"results.":[402],"\\nsimulated":[406],"24-hour":[412],"care":[415],"elderly":[417],"\\npeople":[418],"those":[420],"who":[421],"might":[422],"coronary":[424],"disease.":[426],"It":[427],"\\nthis":[433],"domain.":[434],"Real-time":[435],"analysis":[437],"significant":[440],"part":[441],"Self-Coach,":[443],"makes":[445],"\\nit":[446],"good":[448],"candidate":[449],"supporting":[451],"broad":[453],"array":[454],"high-impact":[456],"applications":[457],"in":[458],"\\ndomain":[460],"system,":[464],"training,":[466],"rehabilitation,":[467],"surgical":[468],"recovery":[469],"\\na":[472],"home-based":[473],"system.":[476]},"counts_by_year":[],"updated_date":"2026-11-04T10:54:05.112534","created_date":"2018-06-21T00:00:00"}
