{"id":"https://openalex.org/W3134729468","doi":"https://doi.org/10.1109/ssd49366.2020.9364201","title":"Research on feature extraction method based on brain network and CSP for MI-EEG signals","display_name":"Research on feature extraction method based on brain network and CSP for MI-EEG signals","publication_year":2020,"publication_date":"2020-07-20","ids":{"openalex":"https://openalex.org/W3134729468","doi":"https://doi.org/10.1109/ssd49366.2020.9364201","mag":"3134729468"},"language":"en","primary_location":{"id":"doi:10.1109/ssd49366.2020.9364201","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssd49366.2020.9364201","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 17th International Multi-Conference on Systems, Signals &amp; Devices (SSD)","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/A5089739705","display_name":"Rui Yu","orcid":"https://orcid.org/0000-0001-7839-2890"},"institutions":[{"id":"https://openalex.org/I4210110458","display_name":"Institute of Electronics","ror":"https://ror.org/01z143507","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210110458"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Rui Yu","raw_affiliation_strings":["Nanjing Research Institute of Electronic Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing Research Institute of Electronic Technology, Nanjing, China","institution_ids":["https://openalex.org/I4210110458"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5031156587","display_name":"Kuiying Yin","orcid":"https://orcid.org/0000-0001-5637-8529"},"institutions":[{"id":"https://openalex.org/I4210110458","display_name":"Institute of Electronics","ror":"https://ror.org/01z143507","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210110458"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kuiying Yin","raw_affiliation_strings":["Nanjing Research Institute of Electronic Technology, Nanjing, China"],"affiliations":[{"raw_affiliation_string":"Nanjing Research Institute of Electronic Technology, Nanjing, China","institution_ids":["https://openalex.org/I4210110458"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5089739705"],"corresponding_institution_ids":["https://openalex.org/I4210110458"],"apc_list":null,"apc_paid":null,"fwci":0.3346,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.57063706,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"38","issue":null,"first_page":"668","last_page":"674"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9998999834060669,"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":0.9998999834060669,"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/T10241","display_name":"Functional Brain Connectivity Studies","score":0.9771000146865845,"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/T11601","display_name":"Neuroscience and Neural Engineering","score":0.9650999903678894,"subfield":{"id":"https://openalex.org/subfields/2804","display_name":"Cellular and Molecular 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/phase-synchronization","display_name":"Phase synchronization","score":0.7599846720695496},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6832822561264038},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6627885699272156},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6303087472915649},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.594099223613739},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.588144063949585},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5796530246734619},{"id":"https://openalex.org/keywords/rhythm","display_name":"Rhythm","score":0.5036720633506775},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4871901869773865},{"id":"https://openalex.org/keywords/synchronization","display_name":"Synchronization (alternating current)","score":0.48692262172698975},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.46044740080833435},{"id":"https://openalex.org/keywords/beta-rhythm","display_name":"Beta Rhythm","score":0.45652878284454346},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4333633482456207},{"id":"https://openalex.org/keywords/clustering-coefficient","display_name":"Clustering coefficient","score":0.43198686838150024},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.11234971880912781},{"id":"https://openalex.org/keywords/neuroscience","display_name":"Neuroscience","score":0.10627365112304688},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.09099507331848145}],"concepts":[{"id":"https://openalex.org/C194027367","wikidata":"https://www.wikidata.org/wiki/Q4420475","display_name":"Phase synchronization","level":3,"score":0.7599846720695496},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6832822561264038},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6627885699272156},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6303087472915649},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.594099223613739},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.588144063949585},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5796530246734619},{"id":"https://openalex.org/C135343436","wikidata":"https://www.wikidata.org/wiki/Q170406","display_name":"Rhythm","level":2,"score":0.5036720633506775},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4871901869773865},{"id":"https://openalex.org/C2778562939","wikidata":"https://www.wikidata.org/wiki/Q1298791","display_name":"Synchronization (alternating current)","level":3,"score":0.48692262172698975},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.46044740080833435},{"id":"https://openalex.org/C2910144760","wikidata":"https://www.wikidata.org/wiki/Q831014","display_name":"Beta Rhythm","level":3,"score":0.45652878284454346},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4333633482456207},{"id":"https://openalex.org/C22047676","wikidata":"https://www.wikidata.org/wiki/Q898680","display_name":"Clustering coefficient","level":3,"score":0.43198686838150024},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.11234971880912781},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.10627365112304688},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.09099507331848145},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssd49366.2020.9364201","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssd49366.2020.9364201","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 17th International Multi-Conference on Systems, Signals &amp; Devices (SSD)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1969140390","https://openalex.org/W1992373870","https://openalex.org/W2106006415","https://openalex.org/W2115810652","https://openalex.org/W2121095426","https://openalex.org/W2142280324","https://openalex.org/W2148603752","https://openalex.org/W2328147906","https://openalex.org/W2344313839","https://openalex.org/W2376391444","https://openalex.org/W2523271418","https://openalex.org/W2883269930"],"related_works":["https://openalex.org/W3183948672","https://openalex.org/W3173606202","https://openalex.org/W3110381201","https://openalex.org/W1531601525","https://openalex.org/W2993550715","https://openalex.org/W4361792235","https://openalex.org/W2008609531","https://openalex.org/W1993098504","https://openalex.org/W2473611751","https://openalex.org/W1965449035"],"abstract_inverted_index":{"At":[0],"present,":[1],"most":[2],"of":[3,10,17,33,47,87,107,118,156,182,189,218],"the":[4,15,31,45,54,69,78,105,108,116,125,139,148,153,164,171,183,194,201,211,216],"classification":[5,16,173,198],"studies":[6],"on":[7,14,30],"EEG":[8,90],"signals":[9,63,91],"motor":[11,51],"imagination":[12],"focus":[13],"left":[18],"and":[19,37,60,67,98,113,134,138,152,170,200],"right":[20],"hands.":[21],"In":[22],"this":[23,190,204],"paper,":[24],"a":[25],"feature":[26,161],"analysis":[27,56],"method":[28,143,202],"based":[29],"combination":[32],"brain":[34,70,109],"functional":[35,71],"network":[36,72,126],"common":[38,140],"spatial":[39,149],"pattern":[40],"is":[41,64,74,95,102,121,144,175,178],"proposed":[42],"to":[43,77,123,146,209],"solve":[44],"dichotomy":[46],"unilateral":[48],"(right)":[49],"hand":[50],"imagination.":[52],"Firstly,":[53],"phase":[55,79,99],"between":[57],"Mu":[58,85],"rhythm":[59,62,86,94],"Beta":[61,93],"carried":[65],"out,":[66],"then":[68],"topology":[73],"drawn":[75],"according":[76],"synchronization":[80,100],"information":[81],"matrix.":[82],"Through":[83],"analysis,":[84],"MI":[88],"-":[89],"than":[92,180],"more":[96],"active,":[97],"oscillation":[101],"concentrated":[103],"in":[104,203],"center":[106],"area":[110],"C,":[111],"FC":[112],"CP.":[114],"Then,":[115],"concept":[117],"graph":[119],"theory":[120],"used":[122,145],"extract":[124,147],"attribute":[127],"features":[128,157,165],"under":[129],"two":[130,154,184],"rhythms:":[131],"clustering":[132],"coefficient":[133],"shortest":[135],"path":[136],"length,":[137],"space":[141],"mode":[142],"domain":[150],"features,":[151],"types":[155],"form":[158],"an":[159],"8-dimensional":[160],"vector.":[162],"Finally,":[163],"are":[166],"classified":[167],"by":[168],"SVM,":[169],"average":[172],"accuracy":[174],"94.69%,":[176],"which":[177],"higher":[179],"that":[181,220],"methods.":[185],"The":[186],"research":[187],"content":[188],"paper":[191,205],"breaks":[192],"through":[193],"traditional":[195],"right-handed":[196],"MI-EEG":[197],"problem,":[199],"does":[206],"not":[207],"need":[208],"consider":[210],"ERD/ERS":[212],"phenomenon,":[213],"thus":[214],"expanding":[215],"range":[217],"data":[219],"can":[221],"be":[222],"classified.":[223]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
