{"id":"https://openalex.org/W4200023619","doi":"https://doi.org/10.1145/3487075.3487099","title":"The Finger Flexion Related Feature Extraction Method Based on Wavelet Time-Frequency Analysis in ECoG Signals","display_name":"The Finger Flexion Related Feature Extraction Method Based on Wavelet Time-Frequency Analysis in ECoG Signals","publication_year":2021,"publication_date":"2021-10-19","ids":{"openalex":"https://openalex.org/W4200023619","doi":"https://doi.org/10.1145/3487075.3487099"},"language":"en","primary_location":{"id":"doi:10.1145/3487075.3487099","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3487075.3487099","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Computer Science and Application Engineering","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/A5110817174","display_name":"Haokun Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haokun Shi","raw_affiliation_strings":["School of Information Science and Engineering, Yunnan University, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Yunnan University, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037665380","display_name":"Pengfei Yu","orcid":"https://orcid.org/0000-0002-1881-1245"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengfei Yu","raw_affiliation_strings":["School of Information Science and Engineering, Yunnan University, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Yunnan University, China","institution_ids":["https://openalex.org/I189210763"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021895719","display_name":"Haiyan Li","orcid":"https://orcid.org/0000-0003-3193-1687"},"institutions":[{"id":"https://openalex.org/I189210763","display_name":"Yunnan University","ror":"https://ror.org/0040axw97","country_code":"CN","type":"education","lineage":["https://openalex.org/I189210763"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiyan Li","raw_affiliation_strings":["School of Information Science and Engineering, Yunnan University, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Yunnan University, China","institution_ids":["https://openalex.org/I189210763"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5110817174"],"corresponding_institution_ids":["https://openalex.org/I189210763"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.15939562,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"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/T11601","display_name":"Neuroscience and Neural Engineering","score":0.9843999743461609,"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"}},{"id":"https://openalex.org/T11447","display_name":"Blind Source Separation Techniques","score":0.9819999933242798,"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":0.7985783815383911},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.737188458442688},{"id":"https://openalex.org/keywords/principal-component-analysis","display_name":"Principal component analysis","score":0.7100731730461121},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6712908744812012},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6563619375228882},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6275660991668701},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.6173986196517944},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5355225801467896},{"id":"https://openalex.org/keywords/time\u2013frequency-analysis","display_name":"Time\u2013frequency analysis","score":0.535250723361969},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.5158116817474365},{"id":"https://openalex.org/keywords/brain\u2013computer-interface","display_name":"Brain\u2013computer interface","score":0.48926421999931335},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4858798384666443},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.4732825458049774},{"id":"https://openalex.org/keywords/time-domain","display_name":"Time domain","score":0.4673011302947998},{"id":"https://openalex.org/keywords/frequency-band","display_name":"Frequency band","score":0.45713552832603455},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.4442007541656494},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.42474472522735596},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4149213135242462},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26430216431617737},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.23927593231201172}],"concepts":[{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.7985783815383911},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.737188458442688},{"id":"https://openalex.org/C27438332","wikidata":"https://www.wikidata.org/wiki/Q2873","display_name":"Principal component analysis","level":2,"score":0.7100731730461121},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6712908744812012},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6563619375228882},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6275660991668701},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.6173986196517944},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5355225801467896},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.535250723361969},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.5158116817474365},{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.48926421999931335},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4858798384666443},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.4732825458049774},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.4673011302947998},{"id":"https://openalex.org/C2778116611","wikidata":"https://www.wikidata.org/wiki/Q25110567","display_name":"Frequency band","level":3,"score":0.45713552832603455},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4442007541656494},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.42474472522735596},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4149213135242462},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26430216431617737},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.23927593231201172},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3487075.3487099","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3487075.3487099","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 5th International Conference on Computer Science and Application Engineering","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7666854593","display_name":null,"funder_award_id":"61462094,62066046","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W1971488363","https://openalex.org/W1980066084","https://openalex.org/W1984137274","https://openalex.org/W1995255811","https://openalex.org/W1999389071","https://openalex.org/W2044543358","https://openalex.org/W2052482368","https://openalex.org/W2103032521","https://openalex.org/W2368917325","https://openalex.org/W2526864005","https://openalex.org/W2577511158","https://openalex.org/W2775675829","https://openalex.org/W2913508639","https://openalex.org/W2924796941","https://openalex.org/W2947735132","https://openalex.org/W3028933378","https://openalex.org/W3030394593","https://openalex.org/W3037047196","https://openalex.org/W3126102196"],"related_works":["https://openalex.org/W2001192538","https://openalex.org/W2907827771","https://openalex.org/W2467810721","https://openalex.org/W2097245238","https://openalex.org/W3126234533","https://openalex.org/W2808909649","https://openalex.org/W1671198760","https://openalex.org/W2548521477","https://openalex.org/W3014345450","https://openalex.org/W4362681827"],"abstract_inverted_index":{"In":[0,126],"the":[1,5,17,27,31,35,42,48,52,55,62,68,91,127,130,137,152,157,171,175,179,186,194,214,219,224],"brain-computer":[2],"interface":[3],"system,":[4],"feature":[6,53,92,196,226],"extraction":[7,50],"of":[8,47,54,61,73,140],"brain":[9,19],"signals":[10,20,132,208],"is":[11,41,144,154,165,183],"a":[12,95,109,203,229],"crucial":[13],"procedure.":[14],"Especially":[15],"in":[16,83,87,213,218],"multi-channel":[18,131],"such":[21,103],"as":[22,104,185],"Electroencephalogram":[23],"(EEG),":[24],"Electrocorticography":[25],"(ECoG),":[26],"channel":[28],"which":[29,93,173,197],"has":[30,94,174,202],"most":[32,60],"correlation":[33,98,177,205,231],"with":[34,99,232],"goal":[36],"human":[37,56],"activity":[38,72],"and":[39,77,115,156,209],"intention":[40],"priority":[43],"concern.":[44],"However,":[45],"because":[46],"complicated":[49],"to":[51,89,120,178],"fine":[57,100],"part":[58,102],"movements,":[59],"previous":[63,215],"studies":[64],"are":[65,80],"aiming":[66],"at":[67],"imaginary":[69],"or":[70],"real":[71],"large":[74],"body":[75,101],"parts,":[76],"their":[78],"features":[79,212],"usually":[81],"used":[82],"classification":[84],"tasks.":[85],"Thus,":[86],"order":[88],"extract":[90,121],"higher":[96,204],"linear":[97,230],"fingers,":[105],"this":[106],"paper":[107],"proposes":[108],"method":[110,201],"combining":[111],"wavelet":[112,148,159],"time-frequency":[113,138,160],"analysis":[114,118],"principal":[116,162],"component":[117,163],"(PCA)":[119],"finger":[122,181,221,234],"flexion":[123,222],"related":[124],"feature.":[125,188],"first":[128,158],"step,":[129],"will":[133],"be":[134],"pre-processed.":[135],"Then":[136],"spectrum":[139,153,161],"each":[141],"channel's":[142],"signal":[143],"calculated":[145],"by":[146,167,199],"continuous":[147],"transform.":[149],"After":[150],"that":[151,193],"optimized,":[155],"(Wtspc)":[164],"extracted":[166,198],"PCA.":[168],"At":[169],"last,":[170],"Wtspc,":[172],"highest":[176],"corresponding":[180,233],"flexion,":[182],"chosen":[184],"final":[187],"The":[189],"experiment":[190],"results":[191],"indicate":[192],"Wtspc":[195,225],"our":[200],"than":[206],"original":[207],"typical":[210],"time-domain":[211],"studies.":[216],"Particularly,":[217],"local":[220],"period,":[223],"highly":[227],"demonstrates":[228],"flexion.":[235]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}