{"id":"https://openalex.org/W1590452687","doi":"https://doi.org/10.1109/memea.2015.7145207","title":"A compressive sensing spectral model for fNIRS haemodynamic response de-noising","display_name":"A compressive sensing spectral model for fNIRS haemodynamic response de-noising","publication_year":2015,"publication_date":"2015-05-01","ids":{"openalex":"https://openalex.org/W1590452687","doi":"https://doi.org/10.1109/memea.2015.7145207","mag":"1590452687"},"language":"en","primary_location":{"id":"doi:10.1109/memea.2015.7145207","is_oa":false,"landing_page_url":"https://doi.org/10.1109/memea.2015.7145207","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Proceedings","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/A5008004705","display_name":"Guglielmo Frigo","orcid":"https://orcid.org/0000-0002-5762-4354"},"institutions":[{"id":"https://openalex.org/I138689650","display_name":"University of Padua","ror":"https://ror.org/00240q980","country_code":"IT","type":"education","lineage":["https://openalex.org/I138689650"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Guglielmo Frigo","raw_affiliation_strings":["Department of Information Engineering, University of Padova","Department of Information Engineering University of Padova  Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, University of Padova","institution_ids":["https://openalex.org/I138689650"]},{"raw_affiliation_string":"Department of Information Engineering University of Padova  Italy","institution_ids":["https://openalex.org/I138689650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081523515","display_name":"Sabrina Brigadoi","orcid":"https://orcid.org/0000-0003-3032-7381"},"institutions":[{"id":"https://openalex.org/I45129253","display_name":"University College London","ror":"https://ror.org/02jx3x895","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I45129253"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Sabrina Brigadoi","raw_affiliation_strings":["Department of Medical Physics and Biomedical Engineering, University College, London","Dept. of Medical Physics and Biomedical Engineering, University College London, UK"],"affiliations":[{"raw_affiliation_string":"Department of Medical Physics and Biomedical Engineering, University College, London","institution_ids":["https://openalex.org/I45129253"]},{"raw_affiliation_string":"Dept. of Medical Physics and Biomedical Engineering, University College London, UK","institution_ids":["https://openalex.org/I45129253"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103131953","display_name":"Giada Giorgi","orcid":"https://orcid.org/0000-0001-9498-4722"},"institutions":[{"id":"https://openalex.org/I138689650","display_name":"University of Padua","ror":"https://ror.org/00240q980","country_code":"IT","type":"education","lineage":["https://openalex.org/I138689650"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Giada Giorgi","raw_affiliation_strings":["Department of Information Engineering, University of Padova","Department of Information Engineering University of Padova  Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, University of Padova","institution_ids":["https://openalex.org/I138689650"]},{"raw_affiliation_string":"Department of Information Engineering University of Padova  Italy","institution_ids":["https://openalex.org/I138689650"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071251680","display_name":"Giovanni Sparacino","orcid":"https://orcid.org/0000-0002-3248-1393"},"institutions":[{"id":"https://openalex.org/I138689650","display_name":"University of Padua","ror":"https://ror.org/00240q980","country_code":"IT","type":"education","lineage":["https://openalex.org/I138689650"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Giovanni Sparacino","raw_affiliation_strings":["Department of Information Engineering, University of Padova","Department of Information Engineering University of Padova  Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, University of Padova","institution_ids":["https://openalex.org/I138689650"]},{"raw_affiliation_string":"Department of Information Engineering University of Padova  Italy","institution_ids":["https://openalex.org/I138689650"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066241074","display_name":"Claudio Narduzzi","orcid":"https://orcid.org/0000-0002-9021-2693"},"institutions":[{"id":"https://openalex.org/I138689650","display_name":"University of Padua","ror":"https://ror.org/00240q980","country_code":"IT","type":"education","lineage":["https://openalex.org/I138689650"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Claudio Narduzzi","raw_affiliation_strings":["Department of Information Engineering, University of Padova","Department of Information Engineering University of Padova  Italy"],"affiliations":[{"raw_affiliation_string":"Department of Information Engineering, University of Padova","institution_ids":["https://openalex.org/I138689650"]},{"raw_affiliation_string":"Department of Information Engineering University of Padova  Italy","institution_ids":["https://openalex.org/I138689650"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5008004705"],"corresponding_institution_ids":["https://openalex.org/I138689650"],"apc_list":null,"apc_paid":null,"fwci":0.8117,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.73591448,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":97},"biblio":{"volume":"198","issue":null,"first_page":"244","last_page":"249"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10977","display_name":"Optical Imaging and Spectroscopy Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T10977","display_name":"Optical Imaging and Spectroscopy Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9998000264167786,"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/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9997000098228455,"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/spurious-relationship","display_name":"Spurious relationship","score":0.6752183437347412},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6406402587890625},{"id":"https://openalex.org/keywords/functional-near-infrared-spectroscopy","display_name":"Functional near-infrared spectroscopy","score":0.5533872246742249},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5167381167411804},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.46901243925094604},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.4559635818004608},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4514434039592743},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.45004093647003174},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.44942450523376465},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4345184862613678},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.42467713356018066},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.41898012161254883},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.4150213301181793},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.18330293893814087},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.12426716089248657},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1061500608921051}],"concepts":[{"id":"https://openalex.org/C97256817","wikidata":"https://www.wikidata.org/wiki/Q1462316","display_name":"Spurious relationship","level":2,"score":0.6752183437347412},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6406402587890625},{"id":"https://openalex.org/C130796691","wikidata":"https://www.wikidata.org/wiki/Q750537","display_name":"Functional near-infrared spectroscopy","level":4,"score":0.5533872246742249},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5167381167411804},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.46901243925094604},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.4559635818004608},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4514434039592743},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.45004093647003174},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.44942450523376465},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4345184862613678},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.42467713356018066},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41898012161254883},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.4150213301181793},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.18330293893814087},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.12426716089248657},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1061500608921051},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C169760540","wikidata":"https://www.wikidata.org/wiki/Q207011","display_name":"Neuroscience","level":1,"score":0.0},{"id":"https://openalex.org/C169900460","wikidata":"https://www.wikidata.org/wiki/Q2200417","display_name":"Cognition","level":2,"score":0.0},{"id":"https://openalex.org/C2781195155","wikidata":"https://www.wikidata.org/wiki/Q18680","display_name":"Prefrontal cortex","level":3,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/memea.2015.7145207","is_oa":false,"landing_page_url":"https://doi.org/10.1109/memea.2015.7145207","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Proceedings","raw_type":"proceedings-article"},{"id":"pmh:oai:www.research.unipd.it:11577/3143728","is_oa":false,"landing_page_url":"http://hdl.handle.net/11577/3143728","pdf_url":null,"source":{"id":"https://openalex.org/S4306402547","display_name":"Padua Research Archive (University of Padova)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I138689650","host_organization_name":"University of Padua","host_organization_lineage":["https://openalex.org/I138689650"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W96336251","https://openalex.org/W1770488939","https://openalex.org/W1979421079","https://openalex.org/W1992529560","https://openalex.org/W2002994039","https://openalex.org/W2007884967","https://openalex.org/W2008600715","https://openalex.org/W2016015580","https://openalex.org/W2026337283","https://openalex.org/W2053356496","https://openalex.org/W2054996700","https://openalex.org/W2072273812","https://openalex.org/W2092890379","https://openalex.org/W2098378641","https://openalex.org/W2102771656","https://openalex.org/W2118066778","https://openalex.org/W2123179036","https://openalex.org/W2128659236","https://openalex.org/W2136890587","https://openalex.org/W2138418088","https://openalex.org/W2400273390","https://openalex.org/W4231404861","https://openalex.org/W6638158097","https://openalex.org/W6712433158","https://openalex.org/W6844970432"],"related_works":["https://openalex.org/W3113091479","https://openalex.org/W2162899405","https://openalex.org/W941090075","https://openalex.org/W2044987316","https://openalex.org/W3134374554","https://openalex.org/W2237480245","https://openalex.org/W2075065631","https://openalex.org/W2519167559","https://openalex.org/W4311248832","https://openalex.org/W4225274307"],"abstract_inverted_index":{"In":[0,15,56],"the":[1,22,44,99,138,147,155],"biomedical":[2],"scenario,":[3],"near-infrared":[4,18],"spectroscopy":[5,19],"(NIRS)":[6],"is":[7,64,80,94],"employed":[8],"as":[9,27],"a":[10,39,48,59,90,108,111,130],"non-invasive":[11],"brain":[12,23],"imaging":[13],"technique.":[14],"particular,":[16],"functional":[17],"(fNIRS)":[20],"measures":[21],"response,":[24],"also":[25],"known":[26],"haemodynamic":[28],"response":[29],"(HR),":[30],"to":[31,42],"pre-defined":[32],"stimuli.":[33],"Processing":[34],"of":[35,51,88,110,133,154],"fNIRS":[36,61],"data":[37],"requires":[38],"great":[40],"effort":[41],"extrapolate":[43],"informative":[45],"component":[46],"from":[47,98],"noisy":[49],"mixture":[50],"physiological":[52],"and":[53,66,72,96,119],"spurious":[54,134],"contributions.":[55],"this":[57],"paper":[58],"novel":[60],"de-noising":[62],"algorithm":[63,105],"presented":[65],"validated":[67],"over":[68],"both":[69],"synthetic":[70,73],"ideal":[71],"realistic":[74],"data.":[75,103],"The":[76,104],"short-separation":[77],"channel":[78,102],"signal":[79],"divided":[81],"into":[82],"nonoverlapping":[83],"short":[84],"sequences.":[85],"For":[86],"each":[87],"them,":[89],"specific":[91],"noise":[92],"model":[93],"identified":[95],"subtracted":[97],"corresponding":[100],"standard":[101],"relies":[106],"on":[107,115],"combination":[109],"super-resolution":[112],"technique":[113],"based":[114],"Compressive":[116],"Sensing":[117],"theory":[118],"spectral":[120],"analysis":[121],"performed":[122],"via":[123],"Taylor-Fourier":[124],"transform.":[125],"Preliminary":[126],"experimental":[127],"results":[128],"show":[129],"significant":[131,142],"reduction":[132],"components":[135],"in":[136,146],"all":[137],"considered":[139],"conditions.":[140],"No":[141],"distortions":[143],"are":[144],"introduced":[145],"recovered":[148],"HR,":[149],"ensuring":[150],"reliable":[151],"clinical":[152],"interpretation":[153],"acquired":[156],"trace.":[157]},"counts_by_year":[{"year":2016,"cited_by_count":3}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}