{"id":"https://openalex.org/W2059139568","doi":"https://doi.org/10.1109/memea.2014.6860096","title":"A compressive sensing framework for electromyogram and electroencephalogram","display_name":"A compressive sensing framework for electromyogram and electroencephalogram","publication_year":2014,"publication_date":"2014-06-01","ids":{"openalex":"https://openalex.org/W2059139568","doi":"https://doi.org/10.1109/memea.2014.6860096","mag":"2059139568"},"language":"en","primary_location":{"id":"doi:10.1109/memea.2014.6860096","is_oa":false,"landing_page_url":"https://doi.org/10.1109/memea.2014.6860096","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","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/A5057561656","display_name":"Yong-Siang Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Yong-Siang Chen","raw_affiliation_strings":["National Tsing Hua University, Hsinchu, TW","Dept. of Electr. Eng., Nat. Tsing Hua Univ., Hsinchu, Taiwan#TAB#"],"affiliations":[{"raw_affiliation_string":"National Tsing Hua University, Hsinchu, TW","institution_ids":["https://openalex.org/I25846049"]},{"raw_affiliation_string":"Dept. of Electr. Eng., Nat. Tsing Hua Univ., Hsinchu, Taiwan#TAB#","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100652782","display_name":"Hsin-Yi Lin","orcid":"https://orcid.org/0000-0001-5731-2353"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hsin-Yi Lin","raw_affiliation_strings":["National Tsing Hua University, Hsinchu, TW","Dept. of Electr. Eng., Nat. Tsing Hua Univ., Hsinchu, Taiwan#TAB#"],"affiliations":[{"raw_affiliation_string":"National Tsing Hua University, Hsinchu, TW","institution_ids":["https://openalex.org/I25846049"]},{"raw_affiliation_string":"Dept. of Electr. Eng., Nat. Tsing Hua Univ., Hsinchu, Taiwan#TAB#","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027315505","display_name":"Hung\u2010Chih Chiu","orcid":"https://orcid.org/0000-0001-9538-7188"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hung-Chih Chiu","raw_affiliation_strings":["National Tsing Hua University, Hsinchu, TW","Dept. of Electr. Eng., Nat. Tsing Hua Univ., Hsinchu, Taiwan#TAB#"],"affiliations":[{"raw_affiliation_string":"National Tsing Hua University, Hsinchu, TW","institution_ids":["https://openalex.org/I25846049"]},{"raw_affiliation_string":"Dept. of Electr. Eng., Nat. Tsing Hua Univ., Hsinchu, Taiwan#TAB#","institution_ids":["https://openalex.org/I25846049"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101673453","display_name":"Hsi\u2010Pin Ma","orcid":"https://orcid.org/0000-0002-0837-4387"},"institutions":[{"id":"https://openalex.org/I25846049","display_name":"National Tsing Hua University","ror":"https://ror.org/00zdnkx70","country_code":"TW","type":"education","lineage":["https://openalex.org/I25846049"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Hsi-Pin Ma","raw_affiliation_strings":["National Tsing Hua University, Hsinchu, TW","Dept. of Electr. Eng., Nat. Tsing Hua Univ., Hsinchu, Taiwan#TAB#"],"affiliations":[{"raw_affiliation_string":"National Tsing Hua University, Hsinchu, TW","institution_ids":["https://openalex.org/I25846049"]},{"raw_affiliation_string":"Dept. of Electr. Eng., Nat. Tsing Hua Univ., Hsinchu, Taiwan#TAB#","institution_ids":["https://openalex.org/I25846049"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5057561656"],"corresponding_institution_ids":["https://openalex.org/I25846049"],"apc_list":null,"apc_paid":null,"fwci":2.5778,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.88547864,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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":0.9983000159263611,"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/T10323","display_name":"Analog and Mixed-Signal Circuit Design","score":0.9973999857902527,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.8573213815689087},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.7007096409797668},{"id":"https://openalex.org/keywords/matching-pursuit","display_name":"Matching pursuit","score":0.6786352396011353},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6535124778747559},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4667663276195526},{"id":"https://openalex.org/keywords/compression-ratio","display_name":"Compression ratio","score":0.44439664483070374},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.44209355115890503},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.4393923580646515},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.43273138999938965},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3919444680213928},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3591915965080261},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3501173257827759},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11953684687614441}],"concepts":[{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.8573213815689087},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.7007096409797668},{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.6786352396011353},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6535124778747559},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4667663276195526},{"id":"https://openalex.org/C25797200","wikidata":"https://www.wikidata.org/wiki/Q828137","display_name":"Compression ratio","level":3,"score":0.44439664483070374},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.44209355115890503},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.4393923580646515},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.43273138999938965},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3919444680213928},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3591915965080261},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3501173257827759},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11953684687614441},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.0},{"id":"https://openalex.org/C511840579","wikidata":"https://www.wikidata.org/wiki/Q12757","display_name":"Internal combustion engine","level":2,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/memea.2014.6860096","is_oa":false,"landing_page_url":"https://doi.org/10.1109/memea.2014.6860096","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","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":13,"referenced_works":["https://openalex.org/W1909934645","https://openalex.org/W1976237476","https://openalex.org/W2074619921","https://openalex.org/W2095893482","https://openalex.org/W2096892334","https://openalex.org/W2119667497","https://openalex.org/W2126301071","https://openalex.org/W2127271355","https://openalex.org/W2135920679","https://openalex.org/W2147115663","https://openalex.org/W2147129803","https://openalex.org/W2289917018","https://openalex.org/W6696163806"],"related_works":["https://openalex.org/W2098521117","https://openalex.org/W4319793311","https://openalex.org/W2465351041","https://openalex.org/W4385694579","https://openalex.org/W2340242818","https://openalex.org/W4300881421","https://openalex.org/W2103001330","https://openalex.org/W2262109992","https://openalex.org/W2241396314","https://openalex.org/W2436826437"],"abstract_inverted_index":{"Compressive":[0],"sensing":[1,24,49,83],"is":[2,58,100,247,262],"an":[3,20],"emerging":[4],"technique":[5],"for":[6,10,25,109,113,129,154,166,194,244],"reducing":[7],"data":[8],"sampling":[9],"further":[11],"processing":[12],"or":[13],"transmission.":[14],"In":[15,39],"this":[16],"paper,":[17],"we":[18,78],"propose":[19,79],"architecture":[21,99,128,243],"of":[22,75,102,231,235,241,257,269],"compressive":[23,82],"electroencephalogram":[26],"(EEG)":[27],"and":[28,72,87,116,226,233],"electr":[29],"omy":[30],"ogram":[31],"(EMG)":[32],"signals":[33,111,131,156,168,246],"in":[34,46,105,124,260,272],"the":[35,43,48,55,61,66,69,73,88,95,134,150,163,188,198,229,239,255,267],"telemedicine":[36,275],"sensor":[37,276],"network.":[38,277],"order":[40],"to":[41,93,144,213],"save":[42],"hardware":[44],"cost":[45],"encoding-end,":[47,106],"matrix":[50,104],"must":[51],"be":[52,170,201],"simple.":[53],"Moreover,":[54,162],"decoding":[56,91,122,183],"algorithm":[57,118],"required":[59],"with":[60,119,159,174,180,191],"medium":[62],"computational":[63],"complexity":[64,199,256,271],"under":[65],"trade-off":[67],"between":[68],"reconstructed":[70],"error":[71],"speed":[74],"convergence.":[76],"Accordingly,":[77],"a":[80],"modified":[81],"matching":[84],"pursuit":[85],"(MCoSaMP)":[86],"multiple":[89,120,181],"domains":[90,121,182],"method":[92,123,184,259],"enhance":[94],"performance.":[96],"The":[97,126,177],"proposed":[98,127,178,242,258],"composed":[101],"Bernoulli":[103],"Daubechies-4":[107],"(DB-4)":[108],"EMG":[110,167,195,245,252],"(DCT":[112],"EEG":[114,130,155],"signals),":[115],"MCoSaMP":[117,179],"decoding-end.":[125],"can":[132,148,169,185,200],"reduce":[133],"percentage":[135],"root":[136],"mean":[137],"square":[138],"difference":[139],"(PRD)":[140],"by":[141],"17%":[142],"compared":[143],"other":[145],"papers.":[146],"We":[147],"achieve":[149,186],"compression":[151,253],"ratio":[152,165],"(CR)":[153],"at":[157,172,274],"0.4":[158,173],"PRD":[160,175,190,240],"9.1%.":[161],"comperssion":[164],"achieved":[171],"21.3%.":[176],"almost":[187],"same":[189],"convex":[192],"optimization":[193],"signals.":[196],"And":[197],"reduced":[202],"from":[203],"O(N":[204],"<sup":[205,209,215,220],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[206,210,216,221],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">3</sup>":[207,217],".":[208],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">5</sup>":[211],")":[212],"O(m":[214],"/(log":[218],"N)":[219],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">2</sup>":[222],"),":[223],"where":[224],"m":[225],"N":[227],"are":[228],"number":[230],"measurement":[232],"length":[234],"signal,":[236],"respectively.":[237],"Although":[238],"6%":[248],"larger":[249],"than":[250],"traditional":[251],"method,":[254],"encoding-end":[261,273],"much":[263],"lower.":[264],"That":[265],"achieves":[266],"goal":[268],"low":[270]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}