{"id":"https://openalex.org/W2898969864","doi":"https://doi.org/10.1109/embc.2018.8512914","title":"Dynamic Time-frequency Feature Extraction for Brain Activity Recognition","display_name":"Dynamic Time-frequency Feature Extraction for Brain Activity Recognition","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2898969864","doi":"https://doi.org/10.1109/embc.2018.8512914","mag":"2898969864","pmid":"https://pubmed.ncbi.nlm.nih.gov/30441051"},"language":"en","primary_location":{"id":"doi:10.1109/embc.2018.8512914","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2018.8512914","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref","pubmed"],"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/A5069526885","display_name":"Yang Shi","orcid":"https://orcid.org/0000-0001-6486-4340"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yang Shi","raw_affiliation_strings":["University of Georgia, Athens, GA, US"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Georgia, Athens, GA, US","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024397951","display_name":"Fangyu Li","orcid":"https://orcid.org/0000-0003-2340-3622"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fangyu Li","raw_affiliation_strings":["University of Georgia, Athens, GA, US"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Georgia, Athens, GA, US","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100647156","display_name":"Tianming Liu","orcid":"https://orcid.org/0000-0002-8132-9048"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tianming Liu","raw_affiliation_strings":["University of Georgia, Athens, GA, US"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Georgia, Athens, GA, US","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036344518","display_name":"Fred R. Beyette","orcid":"https://orcid.org/0000-0001-8704-7810"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fred R. Beyette","raw_affiliation_strings":["University of Georgia, Athens, GA, US"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Georgia, Athens, GA, US","institution_ids":["https://openalex.org/I165733156"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007530002","display_name":"Wen\u2010Zhan Song","orcid":"https://orcid.org/0000-0001-8174-1772"},"institutions":[{"id":"https://openalex.org/I165733156","display_name":"University of Georgia","ror":"https://ror.org/00te3t702","country_code":"US","type":"education","lineage":["https://openalex.org/I165733156"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"WenZhan Song","raw_affiliation_strings":["University of Georgia, Athens, GA, US"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Georgia, Athens, GA, US","institution_ids":["https://openalex.org/I165733156"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I165733156"],"apc_list":null,"apc_paid":null,"fwci":1.4794,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.81877374,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"2018","issue":null,"first_page":"3104","last_page":"3107"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9962000250816345,"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"}},{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9732999801635742,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"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/dynamic-time-warping","display_name":"Dynamic time warping","score":0.8407690525054932},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.8013808727264404},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.759513258934021},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7327438592910767},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7289508581161499},{"id":"https://openalex.org/keywords/motor-imagery","display_name":"Motor imagery","score":0.5653116106987},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5409767031669617},{"id":"https://openalex.org/keywords/time\u2013frequency-analysis","display_name":"Time\u2013frequency analysis","score":0.5044797658920288},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.4996187686920166},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.4664226174354553},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4643934369087219},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.4325190782546997},{"id":"https://openalex.org/keywords/wavelet-packet-decomposition","display_name":"Wavelet packet decomposition","score":0.42880699038505554},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3765396177768707},{"id":"https://openalex.org/keywords/electroencephalography","display_name":"Electroencephalography","score":0.33853572607040405},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.24822956323623657},{"id":"https://openalex.org/keywords/brain\u2013computer-interface","display_name":"Brain\u2013computer interface","score":0.11976489424705505},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.11292770504951477}],"concepts":[{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.8407690525054932},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.8013808727264404},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.759513258934021},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7327438592910767},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7289508581161499},{"id":"https://openalex.org/C54808283","wikidata":"https://www.wikidata.org/wiki/Q6918191","display_name":"Motor imagery","level":4,"score":0.5653116106987},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5409767031669617},{"id":"https://openalex.org/C142433447","wikidata":"https://www.wikidata.org/wiki/Q7806653","display_name":"Time\u2013frequency analysis","level":3,"score":0.5044797658920288},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.4996187686920166},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.4664226174354553},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4643934369087219},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.4325190782546997},{"id":"https://openalex.org/C155777637","wikidata":"https://www.wikidata.org/wiki/Q2736187","display_name":"Wavelet packet decomposition","level":4,"score":0.42880699038505554},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3765396177768707},{"id":"https://openalex.org/C522805319","wikidata":"https://www.wikidata.org/wiki/Q179965","display_name":"Electroencephalography","level":2,"score":0.33853572607040405},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.24822956323623657},{"id":"https://openalex.org/C173201364","wikidata":"https://www.wikidata.org/wiki/Q897410","display_name":"Brain\u2013computer interface","level":3,"score":0.11976489424705505},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.11292770504951477},{"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/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","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/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}],"mesh":[{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D000465","descriptor_name":"Algorithms","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D001921","descriptor_name":"Brain","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D004569","descriptor_name":"Electroencephalography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004569","descriptor_name":"Electroencephalography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D004569","descriptor_name":"Electroencephalography","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D012815","descriptor_name":"Signal Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012815","descriptor_name":"Signal Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D012815","descriptor_name":"Signal Processing, Computer-Assisted","qualifier_ui":null,"qualifier_name":null,"is_major_topic":true},{"descriptor_ui":"D019018","descriptor_name":"Imagery, Psychotherapy","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019018","descriptor_name":"Imagery, Psychotherapy","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false},{"descriptor_ui":"D019018","descriptor_name":"Imagery, Psychotherapy","qualifier_ui":null,"qualifier_name":null,"is_major_topic":false}],"locations_count":2,"locations":[{"id":"doi:10.1109/embc.2018.8512914","is_oa":false,"landing_page_url":"https://doi.org/10.1109/embc.2018.8512914","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)","raw_type":"proceedings-article"},{"id":"pmid:30441051","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/30441051","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1966701961","https://openalex.org/W1989801867","https://openalex.org/W2036007897","https://openalex.org/W2051663518","https://openalex.org/W2053080368","https://openalex.org/W2064493351","https://openalex.org/W2091921805","https://openalex.org/W2141885969","https://openalex.org/W2401713956","https://openalex.org/W2423195739","https://openalex.org/W2508797499","https://openalex.org/W2519140045","https://openalex.org/W2566849112","https://openalex.org/W2593745311","https://openalex.org/W2598278819","https://openalex.org/W2625591639","https://openalex.org/W2727976497","https://openalex.org/W2735900866"],"related_works":["https://openalex.org/W2054017055","https://openalex.org/W2085792030","https://openalex.org/W2034318424","https://openalex.org/W1588899229","https://openalex.org/W4321517526","https://openalex.org/W1976022598","https://openalex.org/W1967182499","https://openalex.org/W2111896212","https://openalex.org/W2097034666","https://openalex.org/W2152748622"],"abstract_inverted_index":{"The":[0],"biomedical":[1,131],"signal":[2,52],"classification":[3,96,108],"accuracy":[4,109],"on":[5,33],"motor":[6,87],"imagery":[7,88],"is":[8,105],"not":[9,14],"always":[10],"satisfactory,":[11],"partially":[12],"because":[13],"all":[15],"the":[16,44,56,64,76,90,118,121],"important":[17,68],"features":[18,69,78],"have":[19],"been":[20],"effectively":[21],"extracted.":[22],"This":[23],"paper":[24],"proposes":[25],"an":[26,38],"improved":[27],"dynamic":[28,57],"feature":[29,101,123],"extraction":[30,102,124],"approach":[31],"based":[32,86],"a":[34,106],"time-frequency":[35],"representation":[36],"and":[37,55,93],"optimal":[39],"sequence":[40,65],"similarity":[41],"measurement.":[42],"Since":[43],"wavelet":[45],"packet":[46],"decomposition":[47],"(WPD)":[48],"generates":[49],"more":[50,67],"detailed":[51],"variation":[53],"information":[54],"time":[58,126],"warping":[59],"(DTW)":[60],"helps":[61],"optimally":[62],"measure":[63],"similarity,":[66],"are":[70],"kept":[71],"for":[72],"classification.":[73],"We":[74],"apply":[75],"extracted":[77],"from":[79,111],"our":[80],"proposed":[81],"method":[82],"to":[83,113],"Electroencephalogram":[84],"(EEG)":[85],"through":[89],"OpenBCI":[91],"device":[92],"obtain":[94],"higher":[95],"accuracy.":[97],"Compared":[98],"with":[99],"traditional":[100],"methods,":[103],"there":[104],"significant":[107],"improvement":[110],"83.53%":[112],"90.89%.":[114],"Our":[115],"work":[116],"demonstrates":[117],"importance":[119],"of":[120],"advanced":[122],"in":[125],"series":[127],"data":[128],"analysis,":[129],"e.g.":[130],"signal.":[132]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
