{"id":"https://openalex.org/W4396705705","doi":"https://doi.org/10.1515/auto-2023-0207","title":"Muscle fatigue detection based on sEMG signal using autocorrelation function and neural networks","display_name":"Muscle fatigue detection based on sEMG signal using autocorrelation function and neural networks","publication_year":2024,"publication_date":"2024-05-01","ids":{"openalex":"https://openalex.org/W4396705705","doi":"https://doi.org/10.1515/auto-2023-0207"},"language":"en","primary_location":{"id":"doi:10.1515/auto-2023-0207","is_oa":false,"landing_page_url":"https://doi.org/10.1515/auto-2023-0207","pdf_url":null,"source":{"id":"https://openalex.org/S4210170077","display_name":"at - Automatisierungstechnik","issn_l":"0178-2312","issn":["0178-2312","2196-677X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319967","host_organization_name":"R. Oldenbourg Verlag","host_organization_lineage":["https://openalex.org/P4310319967"],"host_organization_lineage_names":["R. Oldenbourg Verlag"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"at - Automatisierungstechnik","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/A5038840800","display_name":"Fars Samann","orcid":"https://orcid.org/0000-0002-5797-4549"},"institutions":[{"id":"https://openalex.org/I45155027","display_name":"Technische Hochschule Mittelhessen","ror":"https://ror.org/02qdc9985","country_code":"DE","type":"education","lineage":["https://openalex.org/I45155027"]},{"id":"https://openalex.org/I6033180","display_name":"University of Duhok","ror":"https://ror.org/02g07ds81","country_code":"IQ","type":"education","lineage":["https://openalex.org/I6033180"]}],"countries":["DE","IQ"],"is_corresponding":true,"raw_author_name":"Fars Samann","raw_affiliation_strings":["Department of Biomedical Engineering , University of Duhok , Duhok , Kurdistan Region , Iraq","Technische Hochschule Mittelhessen (THM) \u2013 University of Applied Sciences, Faculty of Life Science Engineering (LSE) , Gie\u00dfen , Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering , University of Duhok , Duhok , Kurdistan Region , Iraq","institution_ids":["https://openalex.org/I6033180"]},{"raw_affiliation_string":"Technische Hochschule Mittelhessen (THM) \u2013 University of Applied Sciences, Faculty of Life Science Engineering (LSE) , Gie\u00dfen , Germany","institution_ids":["https://openalex.org/I45155027"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5096746188","display_name":"Friederike Hubich","orcid":null},"institutions":[{"id":"https://openalex.org/I45155027","display_name":"Technische Hochschule Mittelhessen","ror":"https://ror.org/02qdc9985","country_code":"DE","type":"education","lineage":["https://openalex.org/I45155027"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Friederike Hubich","raw_affiliation_strings":["Technische Hochschule Mittelhessen (THM) \u2013 University of Applied Sciences, Faculty of Life Science Engineering (LSE) , Gie\u00dfen , Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technische Hochschule Mittelhessen (THM) \u2013 University of Applied Sciences, Faculty of Life Science Engineering (LSE) , Gie\u00dfen , Germany","institution_ids":["https://openalex.org/I45155027"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020394043","display_name":"Tobias Ott","orcid":null},"institutions":[{"id":"https://openalex.org/I45155027","display_name":"Technische Hochschule Mittelhessen","ror":"https://ror.org/02qdc9985","country_code":"DE","type":"education","lineage":["https://openalex.org/I45155027"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Tobias Ott","raw_affiliation_strings":["Technische Hochschule Mittelhessen (THM) \u2013 University of Applied Sciences, Faculty of Life Science Engineering (LSE) , Gie\u00dfen , Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technische Hochschule Mittelhessen (THM) \u2013 University of Applied Sciences, Faculty of Life Science Engineering (LSE) , Gie\u00dfen , Germany","institution_ids":["https://openalex.org/I45155027"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061019230","display_name":"Thomas Schanze","orcid":null},"institutions":[{"id":"https://openalex.org/I45155027","display_name":"Technische Hochschule Mittelhessen","ror":"https://ror.org/02qdc9985","country_code":"DE","type":"education","lineage":["https://openalex.org/I45155027"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Thomas Schanze","raw_affiliation_strings":["Technische Hochschule Mittelhessen (THM) \u2013 University of Applied Sciences, Faculty of Life Science Engineering (LSE) , Gie\u00dfen , Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technische Hochschule Mittelhessen (THM) \u2013 University of Applied Sciences, Faculty of Life Science Engineering (LSE) , Gie\u00dfen , Germany","institution_ids":["https://openalex.org/I45155027"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5038840800"],"corresponding_institution_ids":["https://openalex.org/I45155027","https://openalex.org/I6033180"],"apc_list":null,"apc_paid":null,"fwci":0.168,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.42740733,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"72","issue":"5","first_page":"408","last_page":"416"},"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":0.9904000163078308,"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/T10157","display_name":"Sports Performance and Training","score":0.9611999988555908,"subfield":{"id":"https://openalex.org/subfields/2732","display_name":"Orthopedics and Sports 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/autocorrelation","display_name":"Autocorrelation","score":0.668479859828949},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6537700295448303},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6148439645767212},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5898084044456482},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5701677203178406},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5648679733276367},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5456507802009583},{"id":"https://openalex.org/keywords/time-domain","display_name":"Time domain","score":0.5354276895523071},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.519119918346405},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.5066717267036438},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5030235648155212},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.48348575830459595},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.45314037799835205},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.41100582480430603},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.17777058482170105},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1534895896911621},{"id":"https://openalex.org/keywords/digital-signal-processing","display_name":"Digital signal processing","score":0.08537274599075317},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.06603285670280457}],"concepts":[{"id":"https://openalex.org/C5297727","wikidata":"https://www.wikidata.org/wiki/Q786970","display_name":"Autocorrelation","level":2,"score":0.668479859828949},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6537700295448303},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6148439645767212},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5898084044456482},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5701677203178406},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5648679733276367},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5456507802009583},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.5354276895523071},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.519119918346405},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.5066717267036438},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5030235648155212},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.48348575830459595},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.45314037799835205},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.41100582480430603},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.17777058482170105},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1534895896911621},{"id":"https://openalex.org/C84462506","wikidata":"https://www.wikidata.org/wiki/Q173142","display_name":"Digital signal processing","level":2,"score":0.08537274599075317},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.06603285670280457},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1515/auto-2023-0207","is_oa":false,"landing_page_url":"https://doi.org/10.1515/auto-2023-0207","pdf_url":null,"source":{"id":"https://openalex.org/S4210170077","display_name":"at - Automatisierungstechnik","issn_l":"0178-2312","issn":["0178-2312","2196-677X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319967","host_organization_name":"R. Oldenbourg Verlag","host_organization_lineage":["https://openalex.org/P4310319967"],"host_organization_lineage_names":["R. Oldenbourg Verlag"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"at - Automatisierungstechnik","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W2015696822","https://openalex.org/W2080670264","https://openalex.org/W2095705004","https://openalex.org/W2110119146","https://openalex.org/W2139273142","https://openalex.org/W2993341382","https://openalex.org/W3022116041","https://openalex.org/W3185652166","https://openalex.org/W4200484809","https://openalex.org/W4200585891","https://openalex.org/W4234173777","https://openalex.org/W4291004899","https://openalex.org/W4386925317"],"related_works":["https://openalex.org/W2782295999","https://openalex.org/W2162306796","https://openalex.org/W1970292246","https://openalex.org/W2016162169","https://openalex.org/W4247952185","https://openalex.org/W1895367623","https://openalex.org/W1642462315","https://openalex.org/W2015118744","https://openalex.org/W2005619368","https://openalex.org/W1879092539"],"abstract_inverted_index":{"Abstract":[0],"Feature":[1],"extraction":[2],"from":[3,42,121],"an":[4,11,127,147],"recorded":[5],"surface":[6],"electromyography":[7],"(sEMG)":[8],"signal":[9,44,59,80],"plays":[10],"important":[12],"role":[13],"in":[14,57,88,166],"identifying":[15],"and":[16,64,81,101,114,159,171,178],"quantifying":[17],"the":[18,58,96,118,167],"characteristics":[19],"of":[20,76,98,126,136,149,155,162,169],"muscle":[21,32,35],"activities.":[22],"These":[23],"features":[24,40,51],"can":[25,131],"be":[26,67,132],"used":[27],"for":[28],"various":[29,137],"applications":[30],"like":[31,60],"function":[33,70],"assessment,":[34],"fatigue":[36,113,170],"detection,":[37],"etc.":[38],"Common":[39],"extracted":[41],"sEMG":[43,122,173],"are":[45,53],"time-domain":[46],"or":[47],"frequency-domain":[48],"features.":[49],"However,":[50],"which":[52,72],"sensitive":[54],"to":[55,94,110],"uncertainties":[56],"noise,":[61,99],"movement":[62],"artifacts,":[63,100],"outliers":[65],"should":[66],"avoided.":[68],"Autocorrelation":[69],"(ACF),":[71],"is":[73,86,108],"a":[74,79,92,153,160],"measure":[75],"similarity":[77],"between":[78,112],"its":[82],"time":[83],"delayed":[84],"version,":[85],"considered":[87],"this":[89],"work":[90],"as":[91,186],"feature":[93],"overcome":[95],"impact":[97],"outliers.":[102],"An":[103],"artificial":[104],"neural":[105],"network":[106],"(ANN)":[107],"developed":[109],"differentiate":[111],"non-fatigue":[115,172],"conditions":[116],"using":[117],"calculated":[119],"ACF":[120],"segments.":[123],"The":[124,142],"performance":[125],"ANN":[128,144],"model":[129,145],"that":[130,184],"adapted":[133],"by":[134],"means":[135],"regularization":[138],"methods":[139],"was":[140],"investigated.":[141],"proposed":[143],"achieved":[146],"accuracy":[148],"about":[150,156,163],"97.62":[151],"%,":[152],"precision":[154],"95.50":[157],"%":[158,165],"sensitivity":[161],"100":[164],"classification":[168],"segments,":[174],"outperforming":[175],"k":[176],"-means":[177],"linear":[179],"support":[180],"vector":[181],"machine":[182],"approaches":[183],"served":[185],"references.":[187]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}