{"id":"https://openalex.org/W4387785492","doi":"https://doi.org/10.1109/ispa58351.2023.10279445","title":"Impact of Measurement Conditions on Classification of ADL using Surface EMG Signals","display_name":"Impact of Measurement Conditions on Classification of ADL using Surface EMG Signals","publication_year":2023,"publication_date":"2023-09-18","ids":{"openalex":"https://openalex.org/W4387785492","doi":"https://doi.org/10.1109/ispa58351.2023.10279445"},"language":"en","primary_location":{"id":"doi:10.1109/ispa58351.2023.10279445","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispa58351.2023.10279445","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Symposium on Image and Signal Processing and Analysis (ISPA)","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/A5092970494","display_name":"Vidya Sagar Venna","orcid":null},"institutions":[{"id":"https://openalex.org/I4387155292","display_name":"Indian Institute of Information Technology Sri City","ror":"https://ror.org/026873d40","country_code":null,"type":"education","lineage":["https://openalex.org/I4387155292"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Vidya Sagar Venna","raw_affiliation_strings":["IIIT Sri City,Biosignal Analysis Group,Sri City,India","Biosignal Analysis Group, IIIT Sri City, Sri City, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIIT Sri City,Biosignal Analysis Group,Sri City,India","institution_ids":["https://openalex.org/I4387155292"]},{"raw_affiliation_string":"Biosignal Analysis Group, IIIT Sri City, Sri City, India","institution_ids":["https://openalex.org/I4387155292"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080866384","display_name":"Anish C. Turlapaty","orcid":"https://orcid.org/0000-0003-0078-3845"},"institutions":[{"id":"https://openalex.org/I4387155292","display_name":"Indian Institute of Information Technology Sri City","ror":"https://ror.org/026873d40","country_code":null,"type":"education","lineage":["https://openalex.org/I4387155292"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Anish Turlapaty","raw_affiliation_strings":["IIIT Sri City,Biosignal Analysis Group,Sri City,India","Biosignal Analysis Group, IIIT Sri City, Sri City, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIIT Sri City,Biosignal Analysis Group,Sri City,India","institution_ids":["https://openalex.org/I4387155292"]},{"raw_affiliation_string":"Biosignal Analysis Group, IIIT Sri City, Sri City, India","institution_ids":["https://openalex.org/I4387155292"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113011948","display_name":"Surya Naidu","orcid":null},"institutions":[{"id":"https://openalex.org/I4387155292","display_name":"Indian Institute of Information Technology Sri City","ror":"https://ror.org/026873d40","country_code":null,"type":"education","lineage":["https://openalex.org/I4387155292"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Surya Naidu","raw_affiliation_strings":["IIIT Sri City,Biosignal Analysis Group,Sri City,India","Biosignal Analysis Group, IIIT Sri City, Sri City, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"IIIT Sri City,Biosignal Analysis Group,Sri City,India","institution_ids":["https://openalex.org/I4387155292"]},{"raw_affiliation_string":"Biosignal Analysis Group, IIIT Sri City, Sri City, India","institution_ids":["https://openalex.org/I4387155292"]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5092970494"],"corresponding_institution_ids":["https://openalex.org/I4387155292"],"apc_list":null,"apc_paid":null,"fwci":0.5345,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.61635087,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.9998999834060669,"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/T10338","display_name":"Advanced Sensor and Energy Harvesting Materials","score":0.9951000213623047,"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/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9872000217437744,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6097815036773682},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5969770550727844},{"id":"https://openalex.org/keywords/activities-of-daily-living","display_name":"Activities of daily living","score":0.5947018265724182},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5498582720756531},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4601929485797882},{"id":"https://openalex.org/keywords/electromyography","display_name":"Electromyography","score":0.43073606491088867},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.42364826798439026},{"id":"https://openalex.org/keywords/physical-medicine-and-rehabilitation","display_name":"Physical medicine and rehabilitation","score":0.22656983137130737},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16564884781837463},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.11447945237159729},{"id":"https://openalex.org/keywords/physical-therapy","display_name":"Physical therapy","score":0.09614291787147522}],"concepts":[{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6097815036773682},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5969770550727844},{"id":"https://openalex.org/C79544238","wikidata":"https://www.wikidata.org/wiki/Q423243","display_name":"Activities of daily living","level":2,"score":0.5947018265724182},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5498582720756531},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4601929485797882},{"id":"https://openalex.org/C2777515770","wikidata":"https://www.wikidata.org/wiki/Q507369","display_name":"Electromyography","level":2,"score":0.43073606491088867},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.42364826798439026},{"id":"https://openalex.org/C99508421","wikidata":"https://www.wikidata.org/wiki/Q2678675","display_name":"Physical medicine and rehabilitation","level":1,"score":0.22656983137130737},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16564884781837463},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.11447945237159729},{"id":"https://openalex.org/C1862650","wikidata":"https://www.wikidata.org/wiki/Q186005","display_name":"Physical therapy","level":1,"score":0.09614291787147522},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ispa58351.2023.10279445","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispa58351.2023.10279445","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 International Symposium on Image and Signal Processing and Analysis (ISPA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.7900000214576721,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1963745554","https://openalex.org/W2013463953","https://openalex.org/W2413089822","https://openalex.org/W2581530419","https://openalex.org/W2583625835","https://openalex.org/W2736021341","https://openalex.org/W2741846309","https://openalex.org/W2749794192","https://openalex.org/W2794934809","https://openalex.org/W2892206633","https://openalex.org/W2909970681","https://openalex.org/W2970498288","https://openalex.org/W2991198759","https://openalex.org/W3047413521","https://openalex.org/W3127327224","https://openalex.org/W3130663237","https://openalex.org/W3133817630","https://openalex.org/W3181506109","https://openalex.org/W3182174967","https://openalex.org/W3183966593","https://openalex.org/W3185201038","https://openalex.org/W4205653212","https://openalex.org/W4214579445","https://openalex.org/W4226383899","https://openalex.org/W4256346332","https://openalex.org/W4306850564","https://openalex.org/W4398435177","https://openalex.org/W6641764375","https://openalex.org/W6651434277","https://openalex.org/W6732420469","https://openalex.org/W6805262983","https://openalex.org/W6868925887"],"related_works":["https://openalex.org/W2376139493","https://openalex.org/W2071210425","https://openalex.org/W2911808920","https://openalex.org/W2141253262","https://openalex.org/W3156756500","https://openalex.org/W4251090744","https://openalex.org/W2386293158","https://openalex.org/W2433638048","https://openalex.org/W4282981700","https://openalex.org/W2006061919"],"abstract_inverted_index":{"Studying":[0],"Activities":[1],"of":[2,31,51,67,73,82,99,104,139,212,237,270],"Daily":[3],"Living":[4],"(ADL)":[5],"is":[6,76,91,176,280],"crucial":[7],"for":[8,214,239,244],"evaluating":[9],"an":[10,209,234,267],"individual's":[11],"health":[12],"and":[13,19,47,61,115,130,156,164,173,221,242,263,272],"well-being,":[14],"quantifying":[15],"their":[16,42,49],"functional":[17],"status,":[18],"identifying":[20],"limitations.":[21],"The":[22,71,160],"research":[23],"in":[24,125,227,259],"ADL":[25,46,57,95,117],"has":[26],"led":[27],"to":[28,44,58,93,134,289,294],"the":[29,65,144,149,174,179,191,202,205,216,228,261,283],"development":[30],"various":[32,199],"applications,":[33],"such":[34],"as":[35],"prostheses,":[36],"which":[37],"can":[38,195],"help":[39],"individuals":[40],"restore":[41],"ability":[43],"perform":[45],"enhance":[48],"quality":[50],"life.":[52],"Moreover,":[53],"rehabilitation":[54],"engineering":[55],"studies":[56],"create":[59],"solutions":[60],"devices":[62],"that":[63,90,118,190,282],"improve":[64],"well-being":[66],"people":[68],"with":[69,166,178,266],"disabilities.":[70],"focus":[72],"this":[74],"study":[75],"on":[77],"EMAHA-DB4,":[78],"a":[79,97,136,182],"new":[80],"collection":[81],"multi-channel":[83],"surface":[84],"electromyography":[85],"<tex":[86,105],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[87,106],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$(\\mathbf{sEMG})$</tex>":[88],"signals":[89,108],"designed":[92],"evaluate":[94],"under":[96,198],"variety":[98],"measurement":[100,140],"conditions.":[101,141,200,246],"It":[102,187],"consists":[103],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">$\\mathbf{sEMG}$</tex>":[107],"from":[109,148],"10":[110],"subjects":[111],"performing":[112],"8":[113],"unique":[114],"practical":[116],"are":[119,162,286],"essential.":[120],"Each":[121],"activity":[122],"was":[123,188],"performed":[124],"three":[126],"different":[127,168],"body":[128,224,240,290],"postures":[129,291],"four":[131,167],"arm":[132,219,245,295],"positions":[133,220],"ensure":[135],"diverse":[137],"range":[138],"For":[142],"constructing":[143],"framework,":[145],"features":[146,161],"derived":[147],"time":[150],"domain,":[151,153,155],"frequency":[152],"wavelet":[154],"Eigenvalues":[157],"were":[158],"utilized.":[159],"trained":[163],"tested":[165],"classical":[169],"machine":[170],"learning":[171,185],"models":[172,285],"performance":[175],"compared":[177],"CNN":[180,206,231],"Bi-LSTM,":[181],"hybrid":[183],"deep":[184],"architecture.":[186],"found":[189],"proposed":[192],"ML":[193,284],"framework":[194],"effectively":[196],"classify":[197],"In":[201,247,275],"aggregate":[203,262],"scenario,":[204,230],"Bi-LSTM":[207,232],"achieved":[208,233,252],"average":[210,235,268],"accuracy":[211,236,254,269],"85.37%":[213],"classifying":[215],"activities":[217],"versus":[218,223],"82.1%":[222],"postures.":[225],"Similarly,":[226],"subject-wise":[229],"84.4%":[238],"conditions":[241,257],"90.11%":[243],"contrast,":[248],"D":[249],"NN":[250],"consistently":[251],"higher":[253],"across":[255],"all":[256],"experiment":[258],"both":[260],"subject-specific":[264],"scenarios,":[265],"90.9%":[271],"90.3%":[273],"respectively.":[274],"these":[276],"classification":[277],"experiments,":[278],"it":[279],"observed":[281],"fairly":[287],"robust":[288],"but":[292],"sensitive":[293],"positions.":[296]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3}],"updated_date":"2026-04-30T09:15:22.047038","created_date":"2025-10-10T00:00:00"}