{"id":"https://openalex.org/W3131932769","doi":"https://doi.org/10.4018/ijicthd.2021010103","title":"Study of Feature Extraction Techniques for Sensor Data Classification","display_name":"Study of Feature Extraction Techniques for Sensor Data Classification","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3131932769","doi":"https://doi.org/10.4018/ijicthd.2021010103","mag":"3131932769"},"language":"en","primary_location":{"id":"doi:10.4018/ijicthd.2021010103","is_oa":false,"landing_page_url":"https://doi.org/10.4018/ijicthd.2021010103","pdf_url":null,"source":{"id":"https://openalex.org/S106385052","display_name":"International Journal of Information Communication Technologies and Human Development","issn_l":"1935-5661","issn":["1935-5661","1935-567X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Information Communication Technologies and Human Development","raw_type":"journal-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/A5087389019","display_name":"Anupama Jawale","orcid":"https://orcid.org/0000-0002-9982-5218"},"institutions":[{"id":"https://openalex.org/I19986915","display_name":"Shreemati Nathibai Damodar Thackersey Women's University","ror":"https://ror.org/05fnn5020","country_code":"IN","type":"education","lineage":["https://openalex.org/I19986915"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Anupama Jawale","raw_affiliation_strings":["PG Department of Computer Science , SNDT University, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"PG Department of Computer Science , SNDT University, India","institution_ids":["https://openalex.org/I19986915"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090694292","display_name":"Ganesh Magar","orcid":null},"institutions":[{"id":"https://openalex.org/I19986915","display_name":"Shreemati Nathibai Damodar Thackersey Women's University","ror":"https://ror.org/05fnn5020","country_code":"IN","type":"education","lineage":["https://openalex.org/I19986915"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Ganesh Magar","raw_affiliation_strings":["PG Department of Computer Science, SNDT University, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"PG Department of Computer Science, SNDT University, India","institution_ids":["https://openalex.org/I19986915"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I19986915"],"apc_list":null,"apc_paid":null,"fwci":0.2827,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.52257218,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"13","issue":"1","first_page":"33","last_page":"46"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9991999864578247,"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":0.9991999864578247,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9988999962806702,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9980999827384949,"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/gyroscope","display_name":"Gyroscope","score":0.837253212928772},{"id":"https://openalex.org/keywords/accelerometer","display_name":"Accelerometer","score":0.7909626960754395},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7476287484169006},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.641853928565979},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6105022430419922},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5874547958374023},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5855821371078491},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.49442315101623535},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.45333749055862427},{"id":"https://openalex.org/keywords/statistical-classification","display_name":"Statistical classification","score":0.44920244812965393},{"id":"https://openalex.org/keywords/rotation","display_name":"Rotation (mathematics)","score":0.42566049098968506},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1521618664264679}],"concepts":[{"id":"https://openalex.org/C158488048","wikidata":"https://www.wikidata.org/wiki/Q483400","display_name":"Gyroscope","level":2,"score":0.837253212928772},{"id":"https://openalex.org/C89805583","wikidata":"https://www.wikidata.org/wiki/Q192940","display_name":"Accelerometer","level":2,"score":0.7909626960754395},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7476287484169006},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.641853928565979},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6105022430419922},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5874547958374023},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5855821371078491},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.49442315101623535},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.45333749055862427},{"id":"https://openalex.org/C110083411","wikidata":"https://www.wikidata.org/wiki/Q1744628","display_name":"Statistical classification","level":2,"score":0.44920244812965393},{"id":"https://openalex.org/C74050887","wikidata":"https://www.wikidata.org/wiki/Q848368","display_name":"Rotation (mathematics)","level":2,"score":0.42566049098968506},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1521618664264679},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.4018/ijicthd.2021010103","is_oa":false,"landing_page_url":"https://doi.org/10.4018/ijicthd.2021010103","pdf_url":null,"source":{"id":"https://openalex.org/S106385052","display_name":"International Journal of Information Communication Technologies and Human Development","issn_l":"1935-5661","issn":["1935-5661","1935-567X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320424","host_organization_name":"IGI Global","host_organization_lineage":["https://openalex.org/P4310320424"],"host_organization_lineage_names":["IGI Global"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Information Communication Technologies and Human Development","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:igg:jicthd:v:13:y:2021:i:1:p:33-46","is_oa":false,"landing_page_url":"http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJICTHD.2021010103","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1556975153","https://openalex.org/W2035787713","https://openalex.org/W2056392803","https://openalex.org/W2066338981","https://openalex.org/W2088371259","https://openalex.org/W2132549764","https://openalex.org/W2132691216","https://openalex.org/W2153635508","https://openalex.org/W2761234876","https://openalex.org/W2790484447","https://openalex.org/W2898080689","https://openalex.org/W2898089263","https://openalex.org/W2915239740","https://openalex.org/W2964830414","https://openalex.org/W2965904675","https://openalex.org/W2978172742","https://openalex.org/W2979279607","https://openalex.org/W2982175547","https://openalex.org/W2989300047","https://openalex.org/W3034712888"],"related_works":["https://openalex.org/W2981560089","https://openalex.org/W2802839053","https://openalex.org/W2111602176","https://openalex.org/W2979855513","https://openalex.org/W3013515612","https://openalex.org/W2136184105","https://openalex.org/W2336974148","https://openalex.org/W2345184372","https://openalex.org/W2011131726","https://openalex.org/W3023303176"],"abstract_inverted_index":{"Human":[0],"activity":[1,110],"recognition":[2],"is":[3,56,118],"a":[4],"rapidly":[5],"growing":[6],"area":[7],"in":[8],"healthcare":[9],"systems.":[10],"The":[11,36,120],"applications":[12],"include":[13],"fall":[14],"detection,":[15],"ambiguous":[16],"activity,":[17],"dangerous":[18],"behavior,":[19],"etc.":[20],"It":[21],"has":[22,69],"become":[23],"one":[24],"of":[25,47,50,63,95,138],"the":[26,30,106,135],"important":[27],"requirements":[28],"for":[29,53],"elderly":[31],"or":[32],"neurological":[33],"disorder":[34],"patients.":[35],"devices":[37],"included":[38],"are":[39,89,102],"accelerometer":[40,96,107],"and":[41,61,125,131],"gyroscope,":[42],"which":[43],"generate":[44],"large":[45],"amounts":[46],"data.":[48,97],"Accuracy":[49],"classification":[51,100,113],"algorithms":[52],"this":[54],"data":[55,64,87,133],"highly":[57],"dependent":[58],"upon":[59],"extraction":[60],"selection":[62],"features.":[65],"This":[66],"research":[67],"study":[68],"extracted":[70],"time":[71],"domain":[72],"features,":[73],"based":[74],"on":[75],"statistical":[76],"functions":[77],"as":[78,80],"well":[79],"rotational":[81],"features":[82,88],"around":[83],"three":[84],"axes.":[85],"Gyroscope":[86],"also":[90],"used":[91,103,128],"to":[92,104],"enhance":[93],"accuracy":[94,137],"Three":[98],"popular":[99],"techniques":[101],"classify":[105],"dataset":[108],"into":[109],"categories.":[111],"Binary":[112],"(run":[114],"-1":[115],"/":[116],"walk-0)":[117],"considered.":[119],"results":[121],"have":[122],"shown":[123],"SVM":[124],"LDA":[126],"when":[127],"with":[129],"rotation":[130],"gyroscope":[132],"gives":[134],"highest":[136],"92.0%":[139],"whereas":[140],"FDA":[141],"shows":[142],"84%":[143],"accuracy.":[144]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-11T06:19:23.411458","created_date":"2025-10-10T00:00:00"}