Quantifying team cooperation through intrinsic multi-scale measures: respiratory and cardiac synchronization in choir singers and surgical teams.
Identifieur interne : 000092 ( Main/Exploration ); précédent : 000091; suivant : 000093Quantifying team cooperation through intrinsic multi-scale measures: respiratory and cardiac synchronization in choir singers and surgical teams.
Auteurs : Apit Hemakom [Royaume-Uni] ; Katarzyna Powezka [Royaume-Uni] ; Valentin Goverdovsky [Royaume-Uni] ; Usman Jaffer [Royaume-Uni] ; Danilo P. Mandic [Royaume-Uni]Source :
- Royal Society open science [ 2054-5703 ] ; 2017.
Abstract
A highly localized data-association measure, termed intrinsic synchrosqueezing transform (ISC), is proposed for the analysis of coupled nonlinear and non-stationary multivariate signals. This is achieved based on a combination of noise-assisted multivariate empirical mode decomposition and short-time Fourier transform-based univariate and multivariate synchrosqueezing transforms. It is shown that the ISC outperforms six other combinations of algorithms in estimating degrees of synchrony in synthetic linear and nonlinear bivariate signals. Its advantage is further illustrated in the precise identification of the synchronized respiratory and heart rate variability frequencies among a subset of bass singers of a professional choir, where it distinctly exhibits better performance than the continuous wavelet transform-based ISC. We also introduce an extension to the intrinsic phase synchrony (IPS) measure, referred to as nested intrinsic phase synchrony (N-IPS), for the empirical quantification of physically meaningful and straightforward-to-interpret trends in phase synchrony. The N-IPS is employed to reveal physically meaningful variations in the levels of cooperation in choir singing and performing a surgical procedure. Both the proposed techniques successfully reveal degrees of synchronization of the physiological signals in two different aspects: (i) precise localization of synchrony in time and frequency (ISC), and (ii) large-scale analysis for the empirical quantification of physically meaningful trends in synchrony (N-IPS).
DOI: 10.1098/rsos.170853
PubMed: 29308229
PubMed Central: PMC5748960
Affiliations:
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Mandic</name><affiliation wicri:level="1"><nlm:affiliation>Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UK.</nlm:affiliation><country xml:lang="fr">Royaume-Uni</country><wicri:regionArea>Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ</wicri:regionArea><wicri:noRegion>London SW7 2AZ</wicri:noRegion></affiliation></author></analytic><series><title level="j">Royal Society open science</title><idno type="ISSN">2054-5703</idno><imprint><date when="2017" type="published">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">A highly localized data-association measure, termed intrinsic synchrosqueezing transform (ISC), is proposed for the analysis of coupled nonlinear and non-stationary multivariate signals. This is achieved based on a combination of noise-assisted multivariate empirical mode decomposition and short-time Fourier transform-based univariate and multivariate synchrosqueezing transforms. It is shown that the ISC outperforms six other combinations of algorithms in estimating degrees of synchrony in synthetic linear and nonlinear bivariate signals. Its advantage is further illustrated in the precise identification of the synchronized respiratory and heart rate variability frequencies among a subset of bass singers of a professional choir, where it distinctly exhibits better performance than the continuous wavelet transform-based ISC. We also introduce an extension to the intrinsic phase synchrony (IPS) measure, referred to as nested intrinsic phase synchrony (N-IPS), for the empirical quantification of physically meaningful and straightforward-to-interpret trends in phase synchrony. The N-IPS is employed to reveal physically meaningful variations in the levels of cooperation in choir singing and performing a surgical procedure. Both the proposed techniques successfully reveal degrees of synchronization of the physiological signals in two different aspects: (i) precise localization of synchrony in time and frequency (ISC), and (ii) large-scale analysis for the empirical quantification of physically meaningful trends in synchrony (N-IPS).</div></front></TEI><pubmed><MedlineCitation Status="PubMed-not-MEDLINE" Owner="NLM"><PMID Version="1">29308229</PMID><DateRevised><Year>2020</Year><Month>09</Month><Day>28</Day></DateRevised><Article PubModel="Electronic-eCollection"><Journal><ISSN IssnType="Print">2054-5703</ISSN><JournalIssue CitedMedium="Print"><Volume>4</Volume><Issue>12</Issue><PubDate><Year>2017</Year><Month>Dec</Month></PubDate></JournalIssue><Title>Royal Society open science</Title></Journal><ArticleTitle>Quantifying team cooperation through intrinsic multi-scale measures: respiratory and cardiac synchronization in choir singers and surgical teams.</ArticleTitle><Pagination><MedlinePgn>170853</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1098/rsos.170853</ELocationID><Abstract><AbstractText>A highly localized data-association measure, termed intrinsic synchrosqueezing transform (ISC), is proposed for the analysis of coupled nonlinear and non-stationary multivariate signals. This is achieved based on a combination of noise-assisted multivariate empirical mode decomposition and short-time Fourier transform-based univariate and multivariate synchrosqueezing transforms. It is shown that the ISC outperforms six other combinations of algorithms in estimating degrees of synchrony in synthetic linear and nonlinear bivariate signals. Its advantage is further illustrated in the precise identification of the synchronized respiratory and heart rate variability frequencies among a subset of bass singers of a professional choir, where it distinctly exhibits better performance than the continuous wavelet transform-based ISC. We also introduce an extension to the intrinsic phase synchrony (IPS) measure, referred to as nested intrinsic phase synchrony (N-IPS), for the empirical quantification of physically meaningful and straightforward-to-interpret trends in phase synchrony. The N-IPS is employed to reveal physically meaningful variations in the levels of cooperation in choir singing and performing a surgical procedure. Both the proposed techniques successfully reveal degrees of synchronization of the physiological signals in two different aspects: (i) precise localization of synchrony in time and frequency (ISC), and (ii) large-scale analysis for the empirical quantification of physically meaningful trends in synchrony (N-IPS).</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Hemakom</LastName><ForeName>Apit</ForeName><Initials>A</Initials><Identifier Source="ORCID">0000-0003-0621-5240</Identifier><AffiliationInfo><Affiliation>Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Powezka</LastName><ForeName>Katarzyna</ForeName><Initials>K</Initials><AffiliationInfo><Affiliation>Department of Vascular Surgery, Imperial College London, London SW7 2AZ, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Goverdovsky</LastName><ForeName>Valentin</ForeName><Initials>V</Initials><AffiliationInfo><Affiliation>Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Jaffer</LastName><ForeName>Usman</ForeName><Initials>U</Initials><AffiliationInfo><Affiliation>Department of Vascular Surgery, Imperial College London, London SW7 2AZ, UK.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Mandic</LastName><ForeName>Danilo P</ForeName><Initials>DP</Initials><AffiliationInfo><Affiliation>Department of Electrical and Electronic Engineering, Imperial College London, London SW7 2AZ, UK.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><DataBankList CompleteYN="Y"><DataBank><DataBankName>Dryad</DataBankName><AccessionNumberList><AccessionNumber>10.5061/dryad.80cv0</AccessionNumber></AccessionNumberList></DataBank></DataBankList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2017</Year><Month>11</Month><Day>06</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>R Soc Open Sci</MedlineTA><NlmUniqueID>101647528</NlmUniqueID><ISSNLinking>2054-5703</ISSNLinking></MedlineJournalInfo><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">coherence</Keyword><Keyword MajorTopicYN="N">heart rate variability</Keyword><Keyword MajorTopicYN="N">intrinsic multi-scale analysis</Keyword><Keyword MajorTopicYN="N">multivariate empirical mode decomposition</Keyword><Keyword MajorTopicYN="N">multivariate synchrosqueezing transform</Keyword><Keyword MajorTopicYN="N">respiration</Keyword></KeywordList><CoiStatement>We declare we have no competing interests.</CoiStatement></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2017</Year><Month>07</Month><Day>06</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2017</Year><Month>07</Month><Day>07</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2018</Year><Month>1</Month><Day>9</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2018</Year><Month>1</Month><Day>9</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2018</Year><Month>1</Month><Day>9</Day><Hour>6</Hour><Minute>1</Minute></PubMedPubDate></History><PublicationStatus>epublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">29308229</ArticleId><ArticleId IdType="doi">10.1098/rsos.170853</ArticleId><ArticleId IdType="pii">rsos170853</ArticleId><ArticleId IdType="pmc">PMC5748960</ArticleId></ArticleIdList><ReferenceList><Reference><Citation>Phys Rev 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1995 Feb;51(2):980-994</Citation><ArticleIdList><ArticleId IdType="pubmed">9962737</ArticleId></ArticleIdList></Reference></ReferenceList></PubmedData></pubmed><affiliations><list><country><li>Royaume-Uni</li></country></list><tree><country name="Royaume-Uni"><noRegion><name sortKey="Hemakom, Apit" sort="Hemakom, Apit" uniqKey="Hemakom A" first="Apit" last="Hemakom">Apit Hemakom</name></noRegion><name sortKey="Goverdovsky, Valentin" sort="Goverdovsky, Valentin" uniqKey="Goverdovsky V" first="Valentin" last="Goverdovsky">Valentin Goverdovsky</name><name sortKey="Jaffer, Usman" sort="Jaffer, Usman" uniqKey="Jaffer U" first="Usman" last="Jaffer">Usman Jaffer</name><name sortKey="Mandic, Danilo P" sort="Mandic, Danilo P" uniqKey="Mandic D" first="Danilo P" last="Mandic">Danilo P. Mandic</name><name sortKey="Powezka, Katarzyna" sort="Powezka, Katarzyna" uniqKey="Powezka K" first="Katarzyna" last="Powezka">Katarzyna Powezka</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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