{"id":"https://openalex.org/W2554471982","doi":"https://doi.org/10.1109/urai.2016.7734021","title":"Classification of EEG signals using multiple gait features based on Small-world Neural Network","display_name":"Classification of EEG signals using multiple gait features based on Small-world Neural Network","publication_year":2016,"publication_date":"2016-08-01","ids":{"openalex":"https://openalex.org/W2554471982","doi":"https://doi.org/10.1109/urai.2016.7734021","mag":"2554471982"},"language":"en","primary_location":{"id":"doi:10.1109/urai.2016.7734021","is_oa":false,"landing_page_url":"https://doi.org/10.1109/urai.2016.7734021","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)","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/A5100439626","display_name":"Cheng Zhang","orcid":"https://orcid.org/0000-0002-2972-7639"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Cheng Zhang","raw_affiliation_strings":["School of Mechanical Engineering, Xian Jiaotong University, Xian, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Xian Jiaotong University, Xian, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100393287","display_name":"Jinhua Zhang","orcid":"https://orcid.org/0000-0002-1178-2058"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jinhua Zhang","raw_affiliation_strings":["School of Mechanical Engineering, Xian Jiaotong University, Xian, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Xian Jiaotong University, Xian, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027754907","display_name":"Jun Hong","orcid":"https://orcid.org/0000-0001-9556-9619"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Hong","raw_affiliation_strings":["School of Mechanical Engineering, Xian Jiaotong University, Xian, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Xian Jiaotong University, Xian, China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100439626"],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":0.325,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.625227,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"41","issue":null,"first_page":"61","last_page":"66"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9990000128746033,"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":0.9990000128746033,"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9868999719619751,"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/T11447","display_name":"Blind Source Separation Techniques","score":0.9803000092506409,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.7343039512634277},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7104001641273499},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.673188328742981},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6500254273414612},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.6319610476493835},{"id":"https://openalex.org/keywords/gait","display_name":"Gait","score":0.5908128619194031},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.499814510345459},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4799492657184601},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.44472986459732056},{"id":"https://openalex.org/keywords/physical-medicine-and-rehabilitation","display_name":"Physical medicine and rehabilitation","score":0.05799564719200134}],"concepts":[{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.7343039512634277},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7104001641273499},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.673188328742981},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6500254273414612},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.6319610476493835},{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.5908128619194031},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.499814510345459},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4799492657184601},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.44472986459732056},{"id":"https://openalex.org/C99508421","wikidata":"https://www.wikidata.org/wiki/Q2678675","display_name":"Physical medicine and rehabilitation","level":1,"score":0.05799564719200134},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/urai.2016.7734021","is_oa":false,"landing_page_url":"https://doi.org/10.1109/urai.2016.7734021","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)","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":30,"referenced_works":["https://openalex.org/W1527457848","https://openalex.org/W1530626944","https://openalex.org/W1547702425","https://openalex.org/W1888792655","https://openalex.org/W1979426401","https://openalex.org/W1986208911","https://openalex.org/W2026355936","https://openalex.org/W2035868320","https://openalex.org/W2069710849","https://openalex.org/W2075044701","https://openalex.org/W2075647286","https://openalex.org/W2077246054","https://openalex.org/W2099509424","https://openalex.org/W2104149879","https://openalex.org/W2114029543","https://openalex.org/W2115622682","https://openalex.org/W2117263102","https://openalex.org/W2133651939","https://openalex.org/W2139212933","https://openalex.org/W2148068496","https://openalex.org/W2149320105","https://openalex.org/W2150281486","https://openalex.org/W2154421185","https://openalex.org/W2159318219","https://openalex.org/W2160867523","https://openalex.org/W2167388003","https://openalex.org/W2181719885","https://openalex.org/W2266999259","https://openalex.org/W2413276917","https://openalex.org/W6715363118"],"related_works":["https://openalex.org/W2922348724","https://openalex.org/W200322357","https://openalex.org/W2130428257","https://openalex.org/W4308951944","https://openalex.org/W2057366091","https://openalex.org/W4312960290","https://openalex.org/W2049513647","https://openalex.org/W2988848585","https://openalex.org/W2032664813","https://openalex.org/W2386960251"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,27,45,60],"novel":[4],"classification":[5,136,156],"method":[6,23,107,146],"among":[7],"running,":[8,158],"walking":[9,159],"and":[10,18,25,50,108,160],"standing":[11],"by":[12,59,101,118],"combining":[13,102],"common":[14],"spatial":[15,111],"patterns":[16],"(CSP)":[17],"the":[19,34,80,84,91,103,144,152],"fastICA":[20],"feature":[21,36,97],"extraction":[22,98,106],"together":[24],"constructing":[26],"Small-world":[28],"Neural":[29],"Network(SWNN,":[30],"for":[31],"short)":[32],"through":[33],"gait":[35,96],"extracted":[37],"is":[38,57,147],"proposed.":[39],"We":[40],"conducted":[41],"our":[42],"experiments":[43],"on":[44,132],"treadmill":[46],"at":[47],"0km/h,":[48],"1.6km/h":[49],"3km/h":[51],"speed":[52],"separately.":[53],"The":[54],"EEG":[55,77],"data":[56],"accompanied":[58],"large":[61],"number":[62],"of":[63,67,82,94,135,157],"motion":[64,85,154],"artifacts.":[65],"First":[66],"all,":[68],"in":[69,87,149],"order":[70],"to":[71,141],"recover":[72],"independent":[73,104],"components":[74],"from":[75],"raw":[76],"signals":[78],"under":[79],"premise":[81],"removing":[83],"artifacts":[86],"an":[88],"effective":[89],"way,":[90],"research":[92],"idea":[93],"multiple":[95],"was":[99,116,139],"proposed":[100,145],"component":[105],"One-Versus-Rest":[109],"Common":[110],"pattern":[112],"analysis.":[113],"Next,":[114],"SWNN":[115],"constructed":[117],"merging":[119],"complex":[120],"network":[121],"mechanism":[122],"into":[123],"traditional":[124],"multi-layer":[125],"feed-forward":[126],"back":[127],"propagation":[128],"neural":[129],"network.":[130],"Based":[131],"comparing":[133],"results":[134],"efficiency,":[137],"it":[138],"clearly":[140],"conclude":[142],"that":[143],"feasible":[148],"dealing":[150],"with":[151],"three":[153],"states":[155],"standing.":[161]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
