{"id":"https://openalex.org/W4413074228","doi":"https://doi.org/10.1186/s40537-025-01238-y","title":"Optimization of EEG-based wheelchair control: machine learning, feature selection, outlier management, and explainable AI","display_name":"Optimization of EEG-based wheelchair control: machine learning, feature selection, outlier management, and explainable AI","publication_year":2025,"publication_date":"2025-07-17","ids":{"openalex":"https://openalex.org/W4413074228","doi":"https://doi.org/10.1186/s40537-025-01238-y"},"language":"en","primary_location":{"id":"doi:10.1186/s40537-025-01238-y","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-025-01238-y","pdf_url":"https://link.springer.com/content/pdf/10.1186/s40537-025-01238-y.pdf","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1186/s40537-025-01238-y.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5107825104","display_name":"A. Hamed","orcid":"https://orcid.org/0009-0005-2454-5966"},"institutions":[{"id":"https://openalex.org/I130309236","display_name":"Kafrelsheikh University","ror":"https://ror.org/04a97mm30","country_code":"EG","type":"education","lineage":["https://openalex.org/I130309236"]}],"countries":["EG"],"is_corresponding":true,"raw_author_name":"Amr M. Hamed","raw_affiliation_strings":["Department of Computer Engineering and Systems, Faculty of Engineering, Kafrelsheikh University, Kafrelsheikh, Egypt"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering and Systems, Faculty of Engineering, Kafrelsheikh University, Kafrelsheikh, Egypt","institution_ids":["https://openalex.org/I130309236"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008171171","display_name":"Abdel-Fattah Attia","orcid":"https://orcid.org/0000-0002-3621-5033"},"institutions":[{"id":"https://openalex.org/I130309236","display_name":"Kafrelsheikh University","ror":"https://ror.org/04a97mm30","country_code":"EG","type":"education","lineage":["https://openalex.org/I130309236"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Abdel-Fattah Attia","raw_affiliation_strings":["Department of Computer Engineering and Systems, Faculty of Engineering, Kafrelsheikh University, Kafrelsheikh, Egypt"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering and Systems, Faculty of Engineering, Kafrelsheikh University, Kafrelsheikh, Egypt","institution_ids":["https://openalex.org/I130309236"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084189603","display_name":"Heba El-Behery","orcid":null},"institutions":[{"id":"https://openalex.org/I130309236","display_name":"Kafrelsheikh University","ror":"https://ror.org/04a97mm30","country_code":"EG","type":"education","lineage":["https://openalex.org/I130309236"]}],"countries":["EG"],"is_corresponding":false,"raw_author_name":"Heba El-Behery","raw_affiliation_strings":["Department of Computer Engineering and Systems, Faculty of Engineering, Kafrelsheikh University, Kafrelsheikh, Egypt"],"affiliations":[{"raw_affiliation_string":"Department of Computer Engineering and Systems, Faculty of Engineering, Kafrelsheikh University, Kafrelsheikh, Egypt","institution_ids":["https://openalex.org/I130309236"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5107825104"],"corresponding_institution_ids":["https://openalex.org/I130309236"],"apc_list":{"value":1060,"currency":"GBP","value_usd":1300},"apc_paid":{"value":1060,"currency":"GBP","value_usd":1300},"fwci":3.8785,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.93682937,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"12","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":1.0,"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T11184","display_name":"Neonatal and fetal brain pathology","score":0.9879000186920166,"subfield":{"id":"https://openalex.org/subfields/2735","display_name":"Pediatrics, Perinatology and Child Health"},"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/outlier","display_name":"Outlier","score":0.8210707306861877},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.743238627910614},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6784823536872864},{"id":"https://openalex.org/keywords/receiver-operating-characteristic","display_name":"Receiver operating characteristic","score":0.6094855666160583},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.603911280632019},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.580296516418457},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5174379944801331},{"id":"https://openalex.org/keywords/wheelchair","display_name":"Wheelchair","score":0.4646773934364319},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4352347254753113},{"id":"https://openalex.org/keywords/precision-and-recall","display_name":"Precision and recall","score":0.4270305633544922},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.41784948110580444},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3953104019165039},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.335022509098053}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.8210707306861877},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.743238627910614},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6784823536872864},{"id":"https://openalex.org/C58471807","wikidata":"https://www.wikidata.org/wiki/Q327120","display_name":"Receiver operating characteristic","level":2,"score":0.6094855666160583},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.603911280632019},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.580296516418457},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5174379944801331},{"id":"https://openalex.org/C2781042323","wikidata":"https://www.wikidata.org/wiki/Q191931","display_name":"Wheelchair","level":2,"score":0.4646773934364319},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4352347254753113},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.4270305633544922},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.41784948110580444},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3953104019165039},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.335022509098053},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1186/s40537-025-01238-y","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-025-01238-y","pdf_url":"https://link.springer.com/content/pdf/10.1186/s40537-025-01238-y.pdf","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:3483fa17b4c24de0b88df81141b1e85c","is_oa":true,"landing_page_url":"https://doaj.org/article/3483fa17b4c24de0b88df81141b1e85c","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Big Data, Vol 12, Iss 1, Pp 1-30 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1186/s40537-025-01238-y","is_oa":true,"landing_page_url":"https://doi.org/10.1186/s40537-025-01238-y","pdf_url":"https://link.springer.com/content/pdf/10.1186/s40537-025-01238-y.pdf","source":{"id":"https://openalex.org/S2737955091","display_name":"Journal Of Big Data","issn_l":"2196-1115","issn":["2196-1115"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Big Data","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321655","display_name":"Science and Technology Development Fund","ror":"https://ror.org/044vr6g03"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4413074228.pdf"},"referenced_works_count":42,"referenced_works":["https://openalex.org/W2020089616","https://openalex.org/W2295124130","https://openalex.org/W2794345050","https://openalex.org/W2908315377","https://openalex.org/W2963355311","https://openalex.org/W2978943609","https://openalex.org/W3033186461","https://openalex.org/W3036573352","https://openalex.org/W3096930897","https://openalex.org/W3115616859","https://openalex.org/W3123257367","https://openalex.org/W3128254639","https://openalex.org/W3135784346","https://openalex.org/W4210646500","https://openalex.org/W4288404646","https://openalex.org/W4290725485","https://openalex.org/W4293580221","https://openalex.org/W4317930160","https://openalex.org/W4319990225","https://openalex.org/W4322495262","https://openalex.org/W4323365483","https://openalex.org/W4378084132","https://openalex.org/W4380988715","https://openalex.org/W4384557778","https://openalex.org/W4385874477","https://openalex.org/W4389313356","https://openalex.org/W4392544633","https://openalex.org/W4392741075","https://openalex.org/W4393155652","https://openalex.org/W4394726751","https://openalex.org/W4396242195","https://openalex.org/W4396771238","https://openalex.org/W4400861571","https://openalex.org/W4401205956","https://openalex.org/W4401992495","https://openalex.org/W4402347462","https://openalex.org/W4403049238","https://openalex.org/W4403701654","https://openalex.org/W4404473230","https://openalex.org/W4405553247","https://openalex.org/W4406890483","https://openalex.org/W4408056034"],"related_works":["https://openalex.org/W4378364071","https://openalex.org/W2399287283","https://openalex.org/W1998563140","https://openalex.org/W2742303892","https://openalex.org/W4406026467","https://openalex.org/W2724219770","https://openalex.org/W2076341217","https://openalex.org/W2065035327","https://openalex.org/W2718635042","https://openalex.org/W1975017672"],"abstract_inverted_index":{"Abstract":[0],"Classifying":[1],"Electroencephalogram":[2],"(EEG)":[3],"signals":[4],"for":[5,119,142,151],"wheelchair":[6,144],"navigation":[7],"presents":[8],"significant":[9],"challenges":[10],"due":[11],"to":[12],"high":[13],"dimensionality,":[14],"noise,":[15],"outliers,":[16],"and":[17,40,48,58,114,147],"class":[18,92],"imbalances.":[19],"This":[20,132],"study":[21],"proposes":[22],"an":[23],"optimized":[24],"classification":[25],"framework":[26],"that":[27,102],"evaluates":[28],"ten":[29],"machine":[30],"learning":[31],"(ML)":[32],"models,":[33],"emphasizing":[34],"ensemble":[35],"methods,":[36],"feature":[37],"selection":[38],"(FS),":[39],"outlier":[41],"utilization.":[42],"The":[43],"dataset,":[44],"comprising":[45],"2869":[46],"samples":[47],"141":[49],"features,":[50],"was":[51],"processed":[52],"using":[53],"Recursive":[54],"Feature":[55],"Elimination":[56],"(RFE)":[57],"correlation":[59],"thresholds":[60],"(CTs),":[61],"achieving":[62],"a":[63,106,139],"peak":[64],"accuracy":[65,81],"of":[66,88,112,117],"69%":[67],"with":[68],"Extra":[69,103],"Trees":[70,104],"after":[71],"FS.":[72],"Notably,":[73],"training":[74],"on":[75],"outlier-only":[76],"data":[77],"yielded":[78],"even":[79],"higher":[80],"(Extra":[82],"Trees:":[83],"82%),":[84],"underscoring":[85],"the":[86,120,149],"value":[87],"outliers":[89],"in":[90],"enhancing":[91],"separability.":[93],"Receiver":[94],"Operating":[95],"Characteristic\u2013Precision":[96],"Recall":[97],"(ROC-PR)":[98],"curve":[99],"analysis":[100],"confirmed":[101],"achieved":[105],"ROC":[107],"AUC":[108,116],"(Area":[109],"Under":[110],"Curve)":[111],"0.92":[113],"PR":[115],"0.82":[118],"best-classified":[121],"movement":[122],"command,":[123],"while":[124],"other":[125],"models":[126],"exhibited":[127],"lower":[128],"precision-recall":[129],"(PR)":[130],"balance.":[131],"approach,":[133],"complemented":[134],"by":[135],"explainability":[136],"techniques,":[137],"offers":[138],"robust":[140],"solution":[141],"EEG-based":[143],"control":[145],"systems":[146],"paves":[148],"way":[150],"interpretable":[152],"brain-computer":[153],"interfaces":[154],"(BCIs).":[155]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-04-21T08:09:41.155169","created_date":"2025-10-10T00:00:00"}
