{"id":"https://openalex.org/W2217702198","doi":"https://doi.org/10.1109/urai.2015.7358838","title":"The analysis of decoding parameter selection of hand movements based on brain function network","display_name":"The analysis of decoding parameter selection of hand movements based on brain function network","publication_year":2015,"publication_date":"2015-10-01","ids":{"openalex":"https://openalex.org/W2217702198","doi":"https://doi.org/10.1109/urai.2015.7358838","mag":"2217702198"},"language":"en","primary_location":{"id":"doi:10.1109/urai.2015.7358838","is_oa":false,"landing_page_url":"https://doi.org/10.1109/urai.2015.7358838","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 12th 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/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":true,"raw_author_name":"Jinhua Zhang","raw_affiliation_strings":["School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062801392","display_name":"Baozeng Wang","orcid":"https://orcid.org/0000-0003-4031-2327"},"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":"Baozeng Wang","raw_affiliation_strings":["School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","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, Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101728621","display_name":"Ting Li","orcid":"https://orcid.org/0000-0003-4962-6875"},"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":"Ting Li","raw_affiliation_strings":["School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100393287"],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.1039687,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"587","last_page":"592"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10429","display_name":"EEG and Brain-Computer Interfaces","score":0.9995999932289124,"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":0.9995999932289124,"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/T10320","display_name":"Neural Networks and Applications","score":0.987500011920929,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10581","display_name":"Neural dynamics and brain function","score":0.9663000106811523,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.8220048546791077},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.565369725227356},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5212555527687073},{"id":"https://openalex.org/keywords/correlation-coefficient","display_name":"Correlation coefficient","score":0.4942631721496582},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4928140938282013},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.46993738412857056},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45613864064216614},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.42822733521461487},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.4247032403945923},{"id":"https://openalex.org/keywords/standard-deviation","display_name":"Standard deviation","score":0.421329528093338},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36878058314323425},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.3274473249912262},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.11835712194442749}],"concepts":[{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.8220048546791077},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.565369725227356},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5212555527687073},{"id":"https://openalex.org/C2780092901","wikidata":"https://www.wikidata.org/wiki/Q3433612","display_name":"Correlation coefficient","level":2,"score":0.4942631721496582},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4928140938282013},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.46993738412857056},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45613864064216614},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.42822733521461487},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.4247032403945923},{"id":"https://openalex.org/C22679943","wikidata":"https://www.wikidata.org/wiki/Q159375","display_name":"Standard deviation","level":2,"score":0.421329528093338},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36878058314323425},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.3274473249912262},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.11835712194442749},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/urai.2015.7358838","is_oa":false,"landing_page_url":"https://doi.org/10.1109/urai.2015.7358838","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 12th 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":19,"referenced_works":["https://openalex.org/W1033587997","https://openalex.org/W1963729129","https://openalex.org/W1966583968","https://openalex.org/W1974764791","https://openalex.org/W1989326748","https://openalex.org/W2001898013","https://openalex.org/W2032806855","https://openalex.org/W2036493180","https://openalex.org/W2040590444","https://openalex.org/W2043031633","https://openalex.org/W2045893417","https://openalex.org/W2057504626","https://openalex.org/W2097744687","https://openalex.org/W2115805615","https://openalex.org/W2125757815","https://openalex.org/W2270601315","https://openalex.org/W6626868812","https://openalex.org/W6647555702","https://openalex.org/W6693674538"],"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/W3203142394","https://openalex.org/W1964082513"],"abstract_inverted_index":{"In":[0,53],"order":[1],"to":[2,48,127,151],"improve":[3],"the":[4,16,19,40,69,84,87,117,143],"noninvasive":[5],"decoding":[6,22,94,118,164],"precision":[7],"of":[8,18,21,43,62,80,89,102,106,120,130,166],"hand":[9,121,153,168],"movement":[10,122],"parameters":[11,23,95,101,119,165],"from":[12],"continuous":[13],"electroencephalogram":[14],"(EEG),":[15],"laws":[17],"influence":[20,88],"such":[24],"as":[25],"brain":[26,55],"rhythms":[27],"and":[28,75,98,138,142],"channel":[29,50],"combination":[30,146],"based":[31,67],"on":[32,68,72,93,159],"multiple":[33],"linear":[34],"regression":[35],"models":[36],"were":[37,51,123],"investigated.":[38],"Firstly,":[39],"wavelet":[41,81],"coefficients":[42,82],"EEG":[44,136],"characteristic":[45],"frequencies":[46],"corresponding":[47],"each":[49],"extracted.":[52],"addition,":[54],"function":[56],"network":[57],"(BFN),":[58],"which":[59],"possessed":[60],"characteristics":[61],"small-world":[63],"network,":[64],"was":[65,96],"constructed":[66],"filter":[70],"threshold":[71],"Network":[73],"Cost":[74],"Spearman":[76],"correlation":[77],"coefficient":[78],"matrixes":[79],"among":[83],"channels.":[85],"Then,":[86],"different":[90],"task":[91],"states":[92],"studied":[97],"analyzed":[99],"through":[100],"BFNs":[103],"(standard":[104],"deviation":[105],"average":[107,109,112],"degree,":[108],"path":[110],"length,":[111],"clustering":[113],"coefficient).":[114],"At":[115],"last,":[116],"singled":[124],"out":[125],"according":[126],"P":[128],"value":[129],"Kruskal-Wallis.":[131],"The":[132,155],"results":[133],"showed":[134],"that":[135],"low":[137],"intermediate":[139],"frequency":[140],"bands":[141],"8":[144],"channels":[145],"set":[147],"have":[148],"greater":[149],"contribution":[150],"decode":[152],"movement.":[154],"paper":[156],"sheds":[157],"light":[158],"new":[160],"ideas":[161],"for":[162],"choosing":[163],"subsequent":[167],"movements.":[169]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}