On the use of approximate entropy and sample entropy with centre of pressure time-series.
Identifieur interne : 000382 ( Main/Exploration ); précédent : 000381; suivant : 000383On the use of approximate entropy and sample entropy with centre of pressure time-series.
Auteurs : Luis Montesinos [Royaume-Uni, Mexique] ; Rossana Castaldo [Royaume-Uni] ; Leandro Pecchia [Royaume-Uni]Source :
- Journal of neuroengineering and rehabilitation [ 1743-0003 ] ; 2018.
Descripteurs français
- KwdFr :
- MESH :
- physiologie : Équilibre postural.
- Adulte, Adulte d'âge moyen, Entropie, Femelle, Humains, Jeune adulte, Modèles biologiques, Mâle, Pression, Simulation numérique, Sujet âgé.
English descriptors
- KwdEn :
- MESH :
- physiology : Postural Balance.
- Adult, Aged, Computer Simulation, Entropy, Female, Humans, Male, Middle Aged, Models, Biological, Pressure, Young Adult.
Abstract
BACKGROUND
Approximate entropy (ApEn) and sample entropy (SampEn) have been previously used to quantify the regularity in centre of pressure (COP) time-series in different experimental groups and/or conditions. ApEn and SampEn are very sensitive to their input parameters: m (subseries length), r (tolerance) and N (data length). Yet, the effects of changing those parameters have been scarcely investigated in the analysis of COP time-series. This study aimed to investigate the effects of changing parameters m, r and N on ApEn and SampEn values in COP time-series, as well as the ability of these entropy measures to discriminate between groups.
METHODS
A public dataset of COP time-series was used. ApEn and SampEn were calculated for m = {2, 3, 4, 5}, r = {0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4, 0.45, 0.5} and N = {600, 1200} (30 and 60 s, respectively). Subjects were stratified in young adults (age < 60, n = 85), and older adults (age ≥ 60) with (n = 18) and without (n = 56) falls in the last year. The effects of changing parameters m, r and N on ApEn and SampEn were investigated with a three-way ANOVA. The ability of ApEn and SampEn to discriminate between groups was investigated with a mixed ANOVA (within-subject factors: m, r and N; between-subject factor: group). Specific combinations of m, r and N producing significant differences between groups were identified using the Tukey's honest significant difference procedure.
RESULTS
A significant three-way interaction between m, r and N confirmed the sensitivity of ApEn and SampEn to the input parameters. SampEn showed a higher consistency and ability to discriminate between groups than ApEn. Significant differences between groups were mostly observed in longer (N = 1200) COP time-series in the anterior-posterior direction. Those differences were observed for specific combinations of m and r, highlighting the importance of an adequate selection of input parameters.
CONCLUSIONS
Future studies should favour SampEn over ApEn and longer time-series (≥ 60 s) over shorter ones (e.g. 30 s). The use of parameter combinations such as SampEn (m = {4, 5}, r = {0.25, 0.3, 0.35}) is recommended.
DOI: 10.1186/s12984-018-0465-9
PubMed: 30541587
PubMed Central: PMC6291990
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">On the use of approximate entropy and sample entropy with centre of pressure time-series.</title>
<author><name sortKey="Montesinos, Luis" sort="Montesinos, Luis" uniqKey="Montesinos L" first="Luis" last="Montesinos">Luis Montesinos</name>
<affiliation wicri:level="1"><nlm:affiliation>School of Engineering, University of Warwick, Coventry, CV4 7AL, UK.</nlm:affiliation>
<country xml:lang="fr">Royaume-Uni</country>
<wicri:regionArea>School of Engineering, University of Warwick, Coventry, CV4 7AL</wicri:regionArea>
<wicri:noRegion>CV4 7AL</wicri:noRegion>
</affiliation>
<affiliation wicri:level="1"><nlm:affiliation>Escuela de Ingenieria y Ciencias, Tecnologico de Monterrey, Mexico, 14380, Mexico.</nlm:affiliation>
<country xml:lang="fr">Mexique</country>
<wicri:regionArea>Escuela de Ingenieria y Ciencias, Tecnologico de Monterrey, Mexico, 14380</wicri:regionArea>
<wicri:noRegion>14380</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="Castaldo, Rossana" sort="Castaldo, Rossana" uniqKey="Castaldo R" first="Rossana" last="Castaldo">Rossana Castaldo</name>
<affiliation wicri:level="1"><nlm:affiliation>School of Engineering, University of Warwick, Coventry, CV4 7AL, UK.</nlm:affiliation>
<country xml:lang="fr">Royaume-Uni</country>
<wicri:regionArea>School of Engineering, University of Warwick, Coventry, CV4 7AL</wicri:regionArea>
<wicri:noRegion>CV4 7AL</wicri:noRegion>
</affiliation>
<affiliation wicri:level="1"><nlm:affiliation>Institute of Advanced Study, University of Warwick, Coventry, CV4 7HS, UK.</nlm:affiliation>
<country xml:lang="fr">Royaume-Uni</country>
<wicri:regionArea>Institute of Advanced Study, University of Warwick, Coventry, CV4 7HS</wicri:regionArea>
<wicri:noRegion>CV4 7HS</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="Pecchia, Leandro" sort="Pecchia, Leandro" uniqKey="Pecchia L" first="Leandro" last="Pecchia">Leandro Pecchia</name>
<affiliation wicri:level="1"><nlm:affiliation>School of Engineering, University of Warwick, Coventry, CV4 7AL, UK. L.Pecchia@warwick.ac.uk.</nlm:affiliation>
<country xml:lang="fr">Royaume-Uni</country>
<wicri:regionArea>School of Engineering, University of Warwick, Coventry, CV4 7AL</wicri:regionArea>
<wicri:noRegion>CV4 7AL</wicri:noRegion>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">PubMed</idno>
<date when="2018">2018</date>
<idno type="RBID">pubmed:30541587</idno>
<idno type="pmid">30541587</idno>
<idno type="doi">10.1186/s12984-018-0465-9</idno>
<idno type="pmc">PMC6291990</idno>
<idno type="wicri:Area/Main/Corpus">000300</idno>
<idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">000300</idno>
<idno type="wicri:Area/Main/Curation">000300</idno>
<idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Curation">000300</idno>
<idno type="wicri:Area/Main/Exploration">000300</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en">On the use of approximate entropy and sample entropy with centre of pressure time-series.</title>
<author><name sortKey="Montesinos, Luis" sort="Montesinos, Luis" uniqKey="Montesinos L" first="Luis" last="Montesinos">Luis Montesinos</name>
<affiliation wicri:level="1"><nlm:affiliation>School of Engineering, University of Warwick, Coventry, CV4 7AL, UK.</nlm:affiliation>
<country xml:lang="fr">Royaume-Uni</country>
<wicri:regionArea>School of Engineering, University of Warwick, Coventry, CV4 7AL</wicri:regionArea>
<wicri:noRegion>CV4 7AL</wicri:noRegion>
</affiliation>
<affiliation wicri:level="1"><nlm:affiliation>Escuela de Ingenieria y Ciencias, Tecnologico de Monterrey, Mexico, 14380, Mexico.</nlm:affiliation>
<country xml:lang="fr">Mexique</country>
<wicri:regionArea>Escuela de Ingenieria y Ciencias, Tecnologico de Monterrey, Mexico, 14380</wicri:regionArea>
<wicri:noRegion>14380</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="Castaldo, Rossana" sort="Castaldo, Rossana" uniqKey="Castaldo R" first="Rossana" last="Castaldo">Rossana Castaldo</name>
<affiliation wicri:level="1"><nlm:affiliation>School of Engineering, University of Warwick, Coventry, CV4 7AL, UK.</nlm:affiliation>
<country xml:lang="fr">Royaume-Uni</country>
<wicri:regionArea>School of Engineering, University of Warwick, Coventry, CV4 7AL</wicri:regionArea>
<wicri:noRegion>CV4 7AL</wicri:noRegion>
</affiliation>
<affiliation wicri:level="1"><nlm:affiliation>Institute of Advanced Study, University of Warwick, Coventry, CV4 7HS, UK.</nlm:affiliation>
<country xml:lang="fr">Royaume-Uni</country>
<wicri:regionArea>Institute of Advanced Study, University of Warwick, Coventry, CV4 7HS</wicri:regionArea>
<wicri:noRegion>CV4 7HS</wicri:noRegion>
</affiliation>
</author>
<author><name sortKey="Pecchia, Leandro" sort="Pecchia, Leandro" uniqKey="Pecchia L" first="Leandro" last="Pecchia">Leandro Pecchia</name>
<affiliation wicri:level="1"><nlm:affiliation>School of Engineering, University of Warwick, Coventry, CV4 7AL, UK. L.Pecchia@warwick.ac.uk.</nlm:affiliation>
<country xml:lang="fr">Royaume-Uni</country>
<wicri:regionArea>School of Engineering, University of Warwick, Coventry, CV4 7AL</wicri:regionArea>
<wicri:noRegion>CV4 7AL</wicri:noRegion>
</affiliation>
</author>
</analytic>
<series><title level="j">Journal of neuroengineering and rehabilitation</title>
<idno type="eISSN">1743-0003</idno>
<imprint><date when="2018" type="published">2018</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adult (MeSH)</term>
<term>Aged (MeSH)</term>
<term>Computer Simulation (MeSH)</term>
<term>Entropy (MeSH)</term>
<term>Female (MeSH)</term>
<term>Humans (MeSH)</term>
<term>Male (MeSH)</term>
<term>Middle Aged (MeSH)</term>
<term>Models, Biological (MeSH)</term>
<term>Postural Balance (physiology)</term>
<term>Pressure (MeSH)</term>
<term>Young Adult (MeSH)</term>
</keywords>
<keywords scheme="KwdFr" xml:lang="fr"><term>Adulte (MeSH)</term>
<term>Adulte d'âge moyen (MeSH)</term>
<term>Entropie (MeSH)</term>
<term>Femelle (MeSH)</term>
<term>Humains (MeSH)</term>
<term>Jeune adulte (MeSH)</term>
<term>Modèles biologiques (MeSH)</term>
<term>Mâle (MeSH)</term>
<term>Pression (MeSH)</term>
<term>Simulation numérique (MeSH)</term>
<term>Sujet âgé (MeSH)</term>
<term>Équilibre postural (physiologie)</term>
</keywords>
<keywords scheme="MESH" qualifier="physiologie" xml:lang="fr"><term>Équilibre postural</term>
</keywords>
<keywords scheme="MESH" qualifier="physiology" xml:lang="en"><term>Postural Balance</term>
</keywords>
<keywords scheme="MESH" xml:lang="en"><term>Adult</term>
<term>Aged</term>
<term>Computer Simulation</term>
<term>Entropy</term>
<term>Female</term>
<term>Humans</term>
<term>Male</term>
<term>Middle Aged</term>
<term>Models, Biological</term>
<term>Pressure</term>
<term>Young Adult</term>
</keywords>
<keywords scheme="MESH" xml:lang="fr"><term>Adulte</term>
<term>Adulte d'âge moyen</term>
<term>Entropie</term>
<term>Femelle</term>
<term>Humains</term>
<term>Jeune adulte</term>
<term>Modèles biologiques</term>
<term>Mâle</term>
<term>Pression</term>
<term>Simulation numérique</term>
<term>Sujet âgé</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en"><p><b>BACKGROUND</b>
</p>
<p>Approximate entropy (ApEn) and sample entropy (SampEn) have been previously used to quantify the regularity in centre of pressure (COP) time-series in different experimental groups and/or conditions. ApEn and SampEn are very sensitive to their input parameters: m (subseries length), r (tolerance) and N (data length). Yet, the effects of changing those parameters have been scarcely investigated in the analysis of COP time-series. This study aimed to investigate the effects of changing parameters m, r and N on ApEn and SampEn values in COP time-series, as well as the ability of these entropy measures to discriminate between groups.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>METHODS</b>
</p>
<p>A public dataset of COP time-series was used. ApEn and SampEn were calculated for m = {2, 3, 4, 5}, r = {0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4, 0.45, 0.5} and N = {600, 1200} (30 and 60 s, respectively). Subjects were stratified in young adults (age < 60, n = 85), and older adults (age ≥ 60) with (n = 18) and without (n = 56) falls in the last year. The effects of changing parameters m, r and N on ApEn and SampEn were investigated with a three-way ANOVA. The ability of ApEn and SampEn to discriminate between groups was investigated with a mixed ANOVA (within-subject factors: m, r and N; between-subject factor: group). Specific combinations of m, r and N producing significant differences between groups were identified using the Tukey's honest significant difference procedure.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>RESULTS</b>
</p>
<p>A significant three-way interaction between m, r and N confirmed the sensitivity of ApEn and SampEn to the input parameters. SampEn showed a higher consistency and ability to discriminate between groups than ApEn. Significant differences between groups were mostly observed in longer (N = 1200) COP time-series in the anterior-posterior direction. Those differences were observed for specific combinations of m and r, highlighting the importance of an adequate selection of input parameters.</p>
</div>
<div type="abstract" xml:lang="en"><p><b>CONCLUSIONS</b>
</p>
<p>Future studies should favour SampEn over ApEn and longer time-series (≥ 60 s) over shorter ones (e.g. 30 s). The use of parameter combinations such as SampEn (m = {4, 5}, r = {0.25, 0.3, 0.35}) is recommended.</p>
</div>
</front>
</TEI>
<pubmed><MedlineCitation Status="MEDLINE" IndexingMethod="Curated" Owner="NLM"><PMID Version="1">30541587</PMID>
<DateCompleted><Year>2019</Year>
<Month>11</Month>
<Day>11</Day>
</DateCompleted>
<DateRevised><Year>2020</Year>
<Month>03</Month>
<Day>09</Day>
</DateRevised>
<Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">1743-0003</ISSN>
<JournalIssue CitedMedium="Internet"><Volume>15</Volume>
<Issue>1</Issue>
<PubDate><Year>2018</Year>
<Month>12</Month>
<Day>12</Day>
</PubDate>
</JournalIssue>
<Title>Journal of neuroengineering and rehabilitation</Title>
<ISOAbbreviation>J Neuroeng Rehabil</ISOAbbreviation>
</Journal>
<ArticleTitle>On the use of approximate entropy and sample entropy with centre of pressure time-series.</ArticleTitle>
<Pagination><MedlinePgn>116</MedlinePgn>
</Pagination>
<ELocationID EIdType="doi" ValidYN="Y">10.1186/s12984-018-0465-9</ELocationID>
<Abstract><AbstractText Label="BACKGROUND">Approximate entropy (ApEn) and sample entropy (SampEn) have been previously used to quantify the regularity in centre of pressure (COP) time-series in different experimental groups and/or conditions. ApEn and SampEn are very sensitive to their input parameters: m (subseries length), r (tolerance) and N (data length). Yet, the effects of changing those parameters have been scarcely investigated in the analysis of COP time-series. This study aimed to investigate the effects of changing parameters m, r and N on ApEn and SampEn values in COP time-series, as well as the ability of these entropy measures to discriminate between groups.</AbstractText>
<AbstractText Label="METHODS">A public dataset of COP time-series was used. ApEn and SampEn were calculated for m = {2, 3, 4, 5}, r = {0.1, 0.15, 0.2, 0.25, 0.3, 0.35, 0.4, 0.45, 0.5} and N = {600, 1200} (30 and 60 s, respectively). Subjects were stratified in young adults (age < 60, n = 85), and older adults (age ≥ 60) with (n = 18) and without (n = 56) falls in the last year. The effects of changing parameters m, r and N on ApEn and SampEn were investigated with a three-way ANOVA. The ability of ApEn and SampEn to discriminate between groups was investigated with a mixed ANOVA (within-subject factors: m, r and N; between-subject factor: group). Specific combinations of m, r and N producing significant differences between groups were identified using the Tukey's honest significant difference procedure.</AbstractText>
<AbstractText Label="RESULTS">A significant three-way interaction between m, r and N confirmed the sensitivity of ApEn and SampEn to the input parameters. SampEn showed a higher consistency and ability to discriminate between groups than ApEn. Significant differences between groups were mostly observed in longer (N = 1200) COP time-series in the anterior-posterior direction. Those differences were observed for specific combinations of m and r, highlighting the importance of an adequate selection of input parameters.</AbstractText>
<AbstractText Label="CONCLUSIONS">Future studies should favour SampEn over ApEn and longer time-series (≥ 60 s) over shorter ones (e.g. 30 s). The use of parameter combinations such as SampEn (m = {4, 5}, r = {0.25, 0.3, 0.35}) is recommended.</AbstractText>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Montesinos</LastName>
<ForeName>Luis</ForeName>
<Initials>L</Initials>
<AffiliationInfo><Affiliation>School of Engineering, University of Warwick, Coventry, CV4 7AL, UK.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Escuela de Ingenieria y Ciencias, Tecnologico de Monterrey, Mexico, 14380, Mexico.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Castaldo</LastName>
<ForeName>Rossana</ForeName>
<Initials>R</Initials>
<AffiliationInfo><Affiliation>School of Engineering, University of Warwick, Coventry, CV4 7AL, UK.</Affiliation>
</AffiliationInfo>
<AffiliationInfo><Affiliation>Institute of Advanced Study, University of Warwick, Coventry, CV4 7HS, UK.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Pecchia</LastName>
<ForeName>Leandro</ForeName>
<Initials>L</Initials>
<Identifier Source="ORCID">0000-0002-7900-5415</Identifier>
<AffiliationInfo><Affiliation>School of Engineering, University of Warwick, Coventry, CV4 7AL, UK. L.Pecchia@warwick.ac.uk.</Affiliation>
</AffiliationInfo>
</Author>
</AuthorList>
<Language>eng</Language>
<PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType>
<PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType>
</PublicationTypeList>
<ArticleDate DateType="Electronic"><Year>2018</Year>
<Month>12</Month>
<Day>12</Day>
</ArticleDate>
</Article>
<MedlineJournalInfo><Country>England</Country>
<MedlineTA>J Neuroeng Rehabil</MedlineTA>
<NlmUniqueID>101232233</NlmUniqueID>
<ISSNLinking>1743-0003</ISSNLinking>
</MedlineJournalInfo>
<CitationSubset>IM</CitationSubset>
<MeshHeadingList><MeshHeading><DescriptorName UI="D000328" MajorTopicYN="N">Adult</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D000368" MajorTopicYN="N">Aged</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D003198" MajorTopicYN="N">Computer Simulation</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D019277" MajorTopicYN="Y">Entropy</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D005260" MajorTopicYN="N">Female</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D006801" MajorTopicYN="N">Humans</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D008297" MajorTopicYN="N">Male</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D008875" MajorTopicYN="N">Middle Aged</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D008954" MajorTopicYN="Y">Models, Biological</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D004856" MajorTopicYN="N">Postural Balance</DescriptorName>
<QualifierName UI="Q000502" MajorTopicYN="Y">physiology</QualifierName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D011312" MajorTopicYN="N">Pressure</DescriptorName>
</MeshHeading>
<MeshHeading><DescriptorName UI="D055815" MajorTopicYN="N">Young Adult</DescriptorName>
</MeshHeading>
</MeshHeadingList>
<KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="Y">Approximate entropy</Keyword>
<Keyword MajorTopicYN="Y">Centre of pressure</Keyword>
<Keyword MajorTopicYN="Y">Human balance</Keyword>
<Keyword MajorTopicYN="Y">Postural control</Keyword>
<Keyword MajorTopicYN="Y">Posturography</Keyword>
<Keyword MajorTopicYN="Y">Sample entropy</Keyword>
</KeywordList>
</MedlineCitation>
<PubmedData><History><PubMedPubDate PubStatus="received"><Year>2018</Year>
<Month>08</Month>
<Day>02</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="accepted"><Year>2018</Year>
<Month>11</Month>
<Day>20</Day>
</PubMedPubDate>
<PubMedPubDate PubStatus="entrez"><Year>2018</Year>
<Month>12</Month>
<Day>14</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="pubmed"><Year>2018</Year>
<Month>12</Month>
<Day>14</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
<PubMedPubDate PubStatus="medline"><Year>2019</Year>
<Month>11</Month>
<Day>12</Day>
<Hour>6</Hour>
<Minute>0</Minute>
</PubMedPubDate>
</History>
<PublicationStatus>epublish</PublicationStatus>
<ArticleIdList><ArticleId IdType="pubmed">30541587</ArticleId>
<ArticleId IdType="doi">10.1186/s12984-018-0465-9</ArticleId>
<ArticleId IdType="pii">10.1186/s12984-018-0465-9</ArticleId>
<ArticleId IdType="pmc">PMC6291990</ArticleId>
</ArticleIdList>
<ReferenceList><Reference><Citation>Braz J Phys Ther. 2017 May - Jun;21(3):184-191</Citation>
<ArticleIdList><ArticleId IdType="pubmed">28473281</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Front Hum Neurosci. 2017 Apr 26;11:206</Citation>
<ArticleIdList><ArticleId IdType="pubmed">28491029</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>J Neuroeng Rehabil. 2007 Oct 30;4:42</Citation>
<ArticleIdList><ArticleId IdType="pubmed">17971209</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Exp Brain Res. 2007 Jul;181(1):1-11</Citation>
<ArticleIdList><ArticleId IdType="pubmed">17401553</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>J Neurol Phys Ther. 2008 Dec;32(4):186-91</Citation>
<ArticleIdList><ArticleId IdType="pubmed">19265760</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>PeerJ. 2016 Nov 2;4:e2648</Citation>
<ArticleIdList><ArticleId IdType="pubmed">27833813</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Rev Bras Fisioter. 2010 May-Jun;14(3):183-92</Citation>
<ArticleIdList><ArticleId IdType="pubmed">20730361</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Med Biol Eng Comput. 2000 Nov;38(6):617-24</Citation>
<ArticleIdList><ArticleId IdType="pubmed">11217878</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Gait Posture. 2015 Feb;41(2):731-5</Citation>
<ArticleIdList><ArticleId IdType="pubmed">25737236</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>J Sport Health Sci. 2016 Mar;5(1):44-51</Citation>
<ArticleIdList><ArticleId IdType="pubmed">30356502</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>IEEE Trans Neural Syst Rehabil Eng. 2016 Aug;24(8):859-71</Citation>
<ArticleIdList><ArticleId IdType="pubmed">26372426</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Phys Rev Lett. 2002 Aug 5;89(6):068102</Citation>
<ArticleIdList><ArticleId IdType="pubmed">12190613</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Gait Posture. 2009 Jul;30(1):106-9</Citation>
<ArticleIdList><ArticleId IdType="pubmed">19411174</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Ann Biomed Eng. 2013 Feb;41(2):349-65</Citation>
<ArticleIdList><ArticleId IdType="pubmed">23064819</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>J Clin Monit. 1991 Oct;7(4):335-45</Citation>
<ArticleIdList><ArticleId IdType="pubmed">1744678</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Exp Brain Res. 2008 Nov;191(3):265-76</Citation>
<ArticleIdList><ArticleId IdType="pubmed">18696056</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Am J Physiol Heart Circ Physiol. 2000 Jun;278(6):H2039-49</Citation>
<ArticleIdList><ArticleId IdType="pubmed">10843903</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Feb;71(2 Pt 1):021906</Citation>
<ArticleIdList><ArticleId IdType="pubmed">15783351</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>J Neuroeng Rehabil. 2010 Jul 30;7:38</Citation>
<ArticleIdList><ArticleId IdType="pubmed">20670457</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Clin Interv Aging. 2017 Mar 08;12:499-503</Citation>
<ArticleIdList><ArticleId IdType="pubmed">28331301</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Prog Neuropsychopharmacol Biol Psychiatry. 2013 Aug 1;45:287-93</Citation>
<ArticleIdList><ArticleId IdType="pubmed">22985940</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Biomed Res Int. 2015;2015:891390</Citation>
<ArticleIdList><ArticleId IdType="pubmed">26640800</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Lancet. 2005 Nov 26;366(9500):1885-93</Citation>
<ArticleIdList><ArticleId IdType="pubmed">16310556</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Clin Neurophysiol. 2008 Nov;119(11):2424-36</Citation>
<ArticleIdList><ArticleId IdType="pubmed">18789756</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Gait Posture. 2013 Feb;37(2):290-2</Citation>
<ArticleIdList><ArticleId IdType="pubmed">22889928</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>J Geriatr Med Gerontol. 2015;1(1):</Citation>
<ArticleIdList><ArticleId IdType="pubmed">26942231</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Br J Sports Med. 2005 Nov;39(11):805-11</Citation>
<ArticleIdList><ArticleId IdType="pubmed">16244188</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Exp Brain Res. 2009 Apr;194(2):323-8</Citation>
<ArticleIdList><ArticleId IdType="pubmed">19252902</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Phys Rev E Stat Nonlin Soft Matter Phys. 2011 Dec;84(6 Pt 1):061918</Citation>
<ArticleIdList><ArticleId IdType="pubmed">22304127</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>J Athl Train. 2011 Jan-Feb;46(1):85-91</Citation>
<ArticleIdList><ArticleId IdType="pubmed">21214355</ArticleId>
</ArticleIdList>
</Reference>
<Reference><Citation>Maturitas. 2013 May;75(1):51-61</Citation>
<ArticleIdList><ArticleId IdType="pubmed">23523272</ArticleId>
</ArticleIdList>
</Reference>
</ReferenceList>
</PubmedData>
</pubmed>
<affiliations><list><country><li>Mexique</li>
<li>Royaume-Uni</li>
</country>
</list>
<tree><country name="Royaume-Uni"><noRegion><name sortKey="Montesinos, Luis" sort="Montesinos, Luis" uniqKey="Montesinos L" first="Luis" last="Montesinos">Luis Montesinos</name>
</noRegion>
<name sortKey="Castaldo, Rossana" sort="Castaldo, Rossana" uniqKey="Castaldo R" first="Rossana" last="Castaldo">Rossana Castaldo</name>
<name sortKey="Castaldo, Rossana" sort="Castaldo, Rossana" uniqKey="Castaldo R" first="Rossana" last="Castaldo">Rossana Castaldo</name>
<name sortKey="Pecchia, Leandro" sort="Pecchia, Leandro" uniqKey="Pecchia L" first="Leandro" last="Pecchia">Leandro Pecchia</name>
</country>
<country name="Mexique"><noRegion><name sortKey="Montesinos, Luis" sort="Montesinos, Luis" uniqKey="Montesinos L" first="Luis" last="Montesinos">Luis Montesinos</name>
</noRegion>
</country>
</tree>
</affiliations>
</record>
Pour manipuler ce document sous Unix (Dilib)
EXPLOR_STEP=$WICRI_ROOT/Sante/explor/PosturoV1/Data/Main/Exploration
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 000382 | SxmlIndent | more
Ou
HfdSelect -h $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd -nk 000382 | SxmlIndent | more
Pour mettre un lien sur cette page dans le réseau Wicri
{{Explor lien |wiki= Sante |area= PosturoV1 |flux= Main |étape= Exploration |type= RBID |clé= pubmed:30541587 |texte= On the use of approximate entropy and sample entropy with centre of pressure time-series. }}
Pour générer des pages wiki
HfdIndexSelect -h $EXPLOR_AREA/Data/Main/Exploration/RBID.i -Sk "pubmed:30541587" \ | HfdSelect -Kh $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd \ | NlmPubMed2Wicri -a PosturoV1
![]() | This area was generated with Dilib version V0.6.37. | ![]() |