{"id":"https://openalex.org/W4416965642","doi":"https://doi.org/10.1109/tai.2025.3639453","title":"Interpretable CNN\u2013LSTM Framework for Multiclass Neuromuscular Disorder Classification Using Clinically Relevant EMG Features","display_name":"Interpretable CNN\u2013LSTM Framework for Multiclass Neuromuscular Disorder Classification Using Clinically Relevant EMG Features","publication_year":2025,"publication_date":"2025-12-03","ids":{"openalex":"https://openalex.org/W4416965642","doi":"https://doi.org/10.1109/tai.2025.3639453"},"language":null,"primary_location":{"id":"doi:10.1109/tai.2025.3639453","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.2025.3639453","pdf_url":null,"source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Artificial Intelligence","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/A5098790283","display_name":"Anika Tasnim Ritu","orcid":null},"institutions":[{"id":"https://openalex.org/I183697816","display_name":"Bangladesh University of Engineering and Technology","ror":"https://ror.org/05a1qpv97","country_code":"BD","type":"education","lineage":["https://openalex.org/I183697816"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Anika Tasnim Ritu","raw_affiliation_strings":["Department of Electrical and Electronic Engineering, Bangladesh Army University of Engineering &#x0026; Technology, Natore, Bangladesh","Electrical and Electronic Engineering Department, Bangladesh Army University of Engineering &#x0026; Technology, Natore-6431, Bangladesh"],"raw_orcid":"https://orcid.org/0009-0009-7367-4712","affiliations":[{"raw_affiliation_string":"Department of Electrical and Electronic Engineering, Bangladesh Army University of Engineering &#x0026; Technology, Natore, Bangladesh","institution_ids":["https://openalex.org/I183697816"]},{"raw_affiliation_string":"Electrical and Electronic Engineering Department, Bangladesh Army University of Engineering &#x0026; Technology, Natore-6431, Bangladesh","institution_ids":["https://openalex.org/I183697816"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050674349","display_name":"Shahed Hossain","orcid":"https://orcid.org/0000-0003-0621-5582"},"institutions":[{"id":"https://openalex.org/I200606013","display_name":"Daffodil International University","ror":"https://ror.org/052t4a858","country_code":"BD","type":"education","lineage":["https://openalex.org/I200606013"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Shahed Hossain","raw_affiliation_strings":["Health Informatics Research Laboratory (HIRL), Department of Computer Science and Engineering, Daffodil International University, Dhaka, Bangladesh","Health Informatics Research Laboratory (HIRL), Department of Computer Science and Engineering, Daffodil International University, Dhaka-1341, Bangladesh"],"raw_orcid":"https://orcid.org/0000-0003-0621-5582","affiliations":[{"raw_affiliation_string":"Health Informatics Research Laboratory (HIRL), Department of Computer Science and Engineering, Daffodil International University, Dhaka, Bangladesh","institution_ids":["https://openalex.org/I200606013"]},{"raw_affiliation_string":"Health Informatics Research Laboratory (HIRL), Department of Computer Science and Engineering, Daffodil International University, Dhaka-1341, Bangladesh","institution_ids":["https://openalex.org/I200606013"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100637208","display_name":"Md. Zahid Hasan","orcid":"https://orcid.org/0000-0003-2137-6704"},"institutions":[{"id":"https://openalex.org/I200606013","display_name":"Daffodil International University","ror":"https://ror.org/052t4a858","country_code":"BD","type":"education","lineage":["https://openalex.org/I200606013"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Md. Zahid Hasan","raw_affiliation_strings":["Health Informatics Research Laboratory (HIRL), Department of Computer Science and Engineering, Daffodil International University, Dhaka, Bangladesh","Health Informatics Research Laboratory (HIRL), Department of Computer Science and Engineering, Daffodil International University, Dhaka-1341, Bangladesh"],"raw_orcid":"https://orcid.org/0000-0002-0132-1717","affiliations":[{"raw_affiliation_string":"Health Informatics Research Laboratory (HIRL), Department of Computer Science and Engineering, Daffodil International University, Dhaka, Bangladesh","institution_ids":["https://openalex.org/I200606013"]},{"raw_affiliation_string":"Health Informatics Research Laboratory (HIRL), Department of Computer Science and Engineering, Daffodil International University, Dhaka-1341, Bangladesh","institution_ids":["https://openalex.org/I200606013"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093917653","display_name":"Sushanto Bosak","orcid":null},"institutions":[{"id":"https://openalex.org/I4210155105","display_name":"Rajshahi University of Engineering and Technology","ror":null,"country_code":"BD","type":null,"lineage":["https://openalex.org/I4210155105"]},{"id":"https://openalex.org/I902853133","display_name":"University of Rajshahi","ror":"https://ror.org/05nnyr510","country_code":"BD","type":"education","lineage":["https://openalex.org/I902853133"]}],"countries":["BD"],"is_corresponding":false,"raw_author_name":"Sushanto Bosak","raw_affiliation_strings":["Department of Electrical &#x0026; Electronic Engineering, Rajshahi University of Engineering &#x0026; Technology, Kazla, Rajshahi, Bangladesh","Electrical &#x0026; Electronic Engineering Department, Rajshahi University of Engineering &#x0026; Technology, Kazla, Rajshahi-6204, Bangladesh"],"raw_orcid":"https://orcid.org/0009-0003-7532-0359","affiliations":[{"raw_affiliation_string":"Department of Electrical &#x0026; Electronic Engineering, Rajshahi University of Engineering &#x0026; Technology, Kazla, Rajshahi, Bangladesh","institution_ids":["https://openalex.org/I4210155105","https://openalex.org/I902853133"]},{"raw_affiliation_string":"Electrical &#x0026; Electronic Engineering Department, Rajshahi University of Engineering &#x0026; Technology, Kazla, Rajshahi-6204, Bangladesh","institution_ids":["https://openalex.org/I4210155105","https://openalex.org/I902853133"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027038320","display_name":"Abubokor Hanip","orcid":null},"institutions":[{"id":"https://openalex.org/I4210161757","display_name":"Chancellor University","ror":"https://ror.org/05986z039","country_code":"US","type":"education","lineage":["https://openalex.org/I4210161757"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Abubokor Hanip","raw_affiliation_strings":["Chancellor&#x2019;s Office, Washington University of Science and Technology, Alexandria, VA, USA","Chancellor&#x2019;s Office, Washington University of Science and Technology, Virginia, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Chancellor&#x2019;s Office, Washington University of Science and Technology, Alexandria, VA, USA","institution_ids":["https://openalex.org/I4210161757"]},{"raw_affiliation_string":"Chancellor&#x2019;s Office, Washington University of Science and Technology, Virginia, USA","institution_ids":["https://openalex.org/I4210161757"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049525793","display_name":"Touhid Bhuiyan","orcid":"https://orcid.org/0000-0002-6747-0846"},"institutions":[{"id":"https://openalex.org/I865166595","display_name":"George Washington University Virginia Campus","ror":"https://ror.org/03ms79854","country_code":"US","type":"education","lineage":["https://openalex.org/I865166595"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Touhid Bhuiyan","raw_affiliation_strings":["School of Information Technology, Washington University of Science and Technology, Alexandria, VA, USA","School of Information Technology, Washington University of Science and Technology, Virginia, USA"],"raw_orcid":"https://orcid.org/0000-0002-6747-0846","affiliations":[{"raw_affiliation_string":"School of Information Technology, Washington University of Science and Technology, Alexandria, VA, USA","institution_ids":["https://openalex.org/I865166595"]},{"raw_affiliation_string":"School of Information Technology, Washington University of Science and Technology, Virginia, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3419,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.59207529,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"7","issue":"6","first_page":"3383","last_page":"3398"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10784","display_name":"Muscle activation and electromyography studies","score":0.9070000052452087,"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":0.9070000052452087,"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":0.011599999852478504,"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"}},{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.0071000000461936,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular 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/feature-selection","display_name":"Feature selection","score":0.5491999983787537},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4966000020503998},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45509999990463257},{"id":"https://openalex.org/keywords/binary-classification","display_name":"Binary classification","score":0.44290000200271606},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4251999855041504},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.3815000057220459},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.36649999022483826},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.32670000195503235},{"id":"https://openalex.org/keywords/electromyography","display_name":"Electromyography","score":0.3255999982357025}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6965000033378601},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6651999950408936},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.5491999983787537},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5430999994277954},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4966000020503998},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45509999990463257},{"id":"https://openalex.org/C66905080","wikidata":"https://www.wikidata.org/wiki/Q17005494","display_name":"Binary classification","level":3,"score":0.44290000200271606},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4251999855041504},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.3815000057220459},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.36649999022483826},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.32670000195503235},{"id":"https://openalex.org/C2777515770","wikidata":"https://www.wikidata.org/wiki/Q507369","display_name":"Electromyography","level":2,"score":0.3255999982357025},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.3215000033378601},{"id":"https://openalex.org/C123860398","wikidata":"https://www.wikidata.org/wiki/Q6934605","display_name":"Multiclass classification","level":3,"score":0.30059999227523804},{"id":"https://openalex.org/C102392041","wikidata":"https://www.wikidata.org/wiki/Q592860","display_name":"Sliding window protocol","level":3,"score":0.29980000853538513},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.29919999837875366},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.28369998931884766},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2825999855995178},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2736999988555908},{"id":"https://openalex.org/C2776356578","wikidata":"https://www.wikidata.org/wiki/Q2246789","display_name":"Neuromuscular disease","level":3,"score":0.2705000042915344},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.26969999074935913},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.265500009059906},{"id":"https://openalex.org/C2780385302","wikidata":"https://www.wikidata.org/wiki/Q367158","display_name":"Protocol (science)","level":3,"score":0.2639000117778778},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.2621000111103058},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2612000107765198},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.2590000033378601},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.25429999828338623},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.2522999942302704},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tai.2025.3639453","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tai.2025.3639453","pdf_url":null,"source":{"id":"https://openalex.org/S4210169448","display_name":"IEEE Transactions on Artificial Intelligence","issn_l":"2691-4581","issn":["2691-4581"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"and":[1,10,18,44,65,121,130,148,158,168,174,191,220,235],"timely":[2],"diagnosis":[3],"of":[4,207],"neuromuscular":[5],"disorders":[6],"(NMDs),":[7],"including":[8,138],"myopathy":[9],"neuropathy,":[11],"is":[12,92,114],"essential":[13],"for":[14,27,80,223],"initiating":[15],"effective":[16],"treatment":[17],"mitigating":[19],"disease":[20],"progression.":[21],"Despite":[22],"advances":[23],"in":[24,124,232],"machine":[25],"learning":[26,78],"NMD":[28,82,226],"analysis,":[29],"existing":[30],"models":[31],"often":[32],"rely":[33],"on":[34,41,164,171],"datasets":[35],"with":[36,101,202],"limited":[37],"subject":[38],"diversity,":[39],"focus":[40],"binary":[42],"classification,":[43],"lack":[45],"clinical":[46,131],"interpretability,":[47],"which":[48,153],"limits":[49],"their":[50],"applicability.":[51],"Classification":[52],"remains":[53],"challenging":[54],"due":[55],"to":[56,116],"overlapping":[57],"electromyographic":[58],"(EMG)":[59],"signal":[60],"patterns,":[61],"high":[62],"inter-patient":[63],"variability,":[64],"subjective":[66],"interpretation.":[67],"To":[68,127],"address":[69],"these":[70],"challenges,":[71],"this":[72],"paper":[73],"presents":[74],"an":[75],"interpretable":[76,221],"deep":[77],"framework":[79,182,216],"multiclass":[81],"classification":[83],"using":[84],"intramuscular":[85],"EMG":[86,125,179],"signals.":[87],"A":[88,105],"robust":[89],"feature":[90,98],"set":[91],"constructed":[93],"by":[94],"combining":[95],"three":[96],"statistical":[97],"selection":[99],"methods":[100],"clinically":[102,229],"validated":[103,170],"descriptors.":[104],"hybrid":[106],"Convolutional":[107],"Neural":[108],"Network\u2013Long":[109],"Short\u2013Term":[110],"Memory":[111],"(CNNLSTM)":[112],"model":[113,134],"proposed":[115],"capture":[117],"both":[118,155,233],"spatial":[119],"patterns":[120],"temporal":[122],"dynamics":[123],"data.":[126],"ensure":[128],"transparency":[129],"trust,":[132],"the":[133,165,172,181,189,215],"integrates":[135],"explainability":[136],"techniques,":[137],"Permutation":[139],"Feature":[140],"Importance,":[141],"SHapley":[142],"Additive":[143],"exPlanations,":[144],"Partial":[145],"Dependence":[146],"Plots,":[147],"Local":[149],"Interpretable":[150],"Model-Agnostic":[151],"Explanations,":[152],"provide":[154],"global":[156],"relevance":[157],"case-specific":[159],"diagnostic":[160],"reasoning.":[161],"Evaluated":[162],"primarily":[163],"Mendeley":[166],"dataset":[167],"further":[169],"EMGLAB":[173],"a":[175,203,218],"private":[176],"non-invasive":[177],"surface":[178],"cohort,":[180],"achieves":[183],"95.83%":[184],"accuracy,":[185],"98.61%":[186],"area":[187],"under":[188],"curve,":[190],"strong":[192],"agreement":[193],"scores":[194],"(Cohen\u2019s":[195],"kappa:":[196],"93.75%,":[197],"Matthews":[198],"Correlation":[199],"Coefficient:":[200],"93.82%)":[201],"median":[204],"inference":[205],"latency":[206],"59.56":[208],"ms":[209],"per":[210],"sample.":[211],"These":[212],"findings":[213],"validate":[214],"as":[217],"practical":[219],"tool":[222],"near":[224],"real-time":[225],"diagnosis,":[227],"enabling":[228],"actionable":[230],"decisions":[231],"highdemand":[234],"resource-constrained":[236],"healthcare":[237],"settings.":[238]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-12-03T00:00:00"}
