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:
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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 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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)
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| HfdSelect -Kh $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd \
| NlmPubMed2Wicri -a PosturoV1
| This area was generated with Dilib version V0.6.37. |  |