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<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Posture class prediction of pre-peak height velocity subjects according to gross body segment orientations using linear discriminant analysis</title>
<author><name sortKey="Dolphens, Mieke" sort="Dolphens, Mieke" uniqKey="Dolphens M" first="Mieke" last="Dolphens">Mieke Dolphens</name>
<affiliation><nlm:aff id="Aff1">Department of Rehabilitation Sciences and Physiotherapy, Faculty of Medicine and Health Sciences, Ghent University, Campus Heymans (UZ, 3B3), De Pintelaan 185, 9000 Ghent, Belgium</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Cagnie, Barbara" sort="Cagnie, Barbara" uniqKey="Cagnie B" first="Barbara" last="Cagnie">Barbara Cagnie</name>
<affiliation><nlm:aff id="Aff1">Department of Rehabilitation Sciences and Physiotherapy, Faculty of Medicine and Health Sciences, Ghent University, Campus Heymans (UZ, 3B3), De Pintelaan 185, 9000 Ghent, Belgium</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Coorevits, Pascal" sort="Coorevits, Pascal" uniqKey="Coorevits P" first="Pascal" last="Coorevits">Pascal Coorevits</name>
<affiliation><nlm:aff id="Aff2">Department of Public Health and Research in Advanced Medical Informatics and Telematics, Faculty of Medicine and Health Sciences, Ghent University, Business Complex Groeninghe (Building F), Zwijnaardsesteenweg 314, 9000 Ghent, Belgium</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Vleeming, Andry" sort="Vleeming, Andry" uniqKey="Vleeming A" first="Andry" last="Vleeming">Andry Vleeming</name>
<affiliation><nlm:aff id="Aff1">Department of Rehabilitation Sciences and Physiotherapy, Faculty of Medicine and Health Sciences, Ghent University, Campus Heymans (UZ, 3B3), De Pintelaan 185, 9000 Ghent, Belgium</nlm:aff>
</affiliation>
<affiliation><nlm:aff id="Aff3">Department of Anatomy, Medical Faculty, Center for Excellence in the Neurosciences, University of New England, 11 Hills Beach Road, Biddeford, ME 04005 USA</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Palmans, Tanneke" sort="Palmans, Tanneke" uniqKey="Palmans T" first="Tanneke" last="Palmans">Tanneke Palmans</name>
<affiliation><nlm:aff id="Aff1">Department of Rehabilitation Sciences and Physiotherapy, Faculty of Medicine and Health Sciences, Ghent University, Campus Heymans (UZ, 3B3), De Pintelaan 185, 9000 Ghent, Belgium</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Danneels, Lieven" sort="Danneels, Lieven" uniqKey="Danneels L" first="Lieven" last="Danneels">Lieven Danneels</name>
<affiliation><nlm:aff id="Aff1">Department of Rehabilitation Sciences and Physiotherapy, Faculty of Medicine and Health Sciences, Ghent University, Campus Heymans (UZ, 3B3), De Pintelaan 185, 9000 Ghent, Belgium</nlm:aff>
</affiliation>
</author>
</titleStmt>
<publicationStmt><idno type="wicri:source">PMC</idno>
<idno type="pmid">24097292</idno>
<idno type="pmc">3940786</idno>
<idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3940786</idno>
<idno type="RBID">PMC:3940786</idno>
<idno type="doi">10.1007/s00586-013-3058-0</idno>
<date when="2013">2013</date>
<idno type="wicri:Area/Pmc/Corpus">000104</idno>
<idno type="wicri:explorRef" wicri:stream="Pmc" wicri:step="Corpus" wicri:corpus="PMC">000104</idno>
</publicationStmt>
<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Posture class prediction of pre-peak height velocity subjects according to gross body segment orientations using linear discriminant analysis</title>
<author><name sortKey="Dolphens, Mieke" sort="Dolphens, Mieke" uniqKey="Dolphens M" first="Mieke" last="Dolphens">Mieke Dolphens</name>
<affiliation><nlm:aff id="Aff1">Department of Rehabilitation Sciences and Physiotherapy, Faculty of Medicine and Health Sciences, Ghent University, Campus Heymans (UZ, 3B3), De Pintelaan 185, 9000 Ghent, Belgium</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Cagnie, Barbara" sort="Cagnie, Barbara" uniqKey="Cagnie B" first="Barbara" last="Cagnie">Barbara Cagnie</name>
<affiliation><nlm:aff id="Aff1">Department of Rehabilitation Sciences and Physiotherapy, Faculty of Medicine and Health Sciences, Ghent University, Campus Heymans (UZ, 3B3), De Pintelaan 185, 9000 Ghent, Belgium</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Coorevits, Pascal" sort="Coorevits, Pascal" uniqKey="Coorevits P" first="Pascal" last="Coorevits">Pascal Coorevits</name>
<affiliation><nlm:aff id="Aff2">Department of Public Health and Research in Advanced Medical Informatics and Telematics, Faculty of Medicine and Health Sciences, Ghent University, Business Complex Groeninghe (Building F), Zwijnaardsesteenweg 314, 9000 Ghent, Belgium</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Vleeming, Andry" sort="Vleeming, Andry" uniqKey="Vleeming A" first="Andry" last="Vleeming">Andry Vleeming</name>
<affiliation><nlm:aff id="Aff1">Department of Rehabilitation Sciences and Physiotherapy, Faculty of Medicine and Health Sciences, Ghent University, Campus Heymans (UZ, 3B3), De Pintelaan 185, 9000 Ghent, Belgium</nlm:aff>
</affiliation>
<affiliation><nlm:aff id="Aff3">Department of Anatomy, Medical Faculty, Center for Excellence in the Neurosciences, University of New England, 11 Hills Beach Road, Biddeford, ME 04005 USA</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Palmans, Tanneke" sort="Palmans, Tanneke" uniqKey="Palmans T" first="Tanneke" last="Palmans">Tanneke Palmans</name>
<affiliation><nlm:aff id="Aff1">Department of Rehabilitation Sciences and Physiotherapy, Faculty of Medicine and Health Sciences, Ghent University, Campus Heymans (UZ, 3B3), De Pintelaan 185, 9000 Ghent, Belgium</nlm:aff>
</affiliation>
</author>
<author><name sortKey="Danneels, Lieven" sort="Danneels, Lieven" uniqKey="Danneels L" first="Lieven" last="Danneels">Lieven Danneels</name>
<affiliation><nlm:aff id="Aff1">Department of Rehabilitation Sciences and Physiotherapy, Faculty of Medicine and Health Sciences, Ghent University, Campus Heymans (UZ, 3B3), De Pintelaan 185, 9000 Ghent, Belgium</nlm:aff>
</affiliation>
</author>
</analytic>
<series><title level="j">European Spine Journal</title>
<idno type="ISSN">0940-6719</idno>
<idno type="eISSN">1432-0932</idno>
<imprint><date when="2013">2013</date>
</imprint>
</series>
</biblStruct>
</sourceDesc>
</fileDesc>
<profileDesc><textClass></textClass>
</profileDesc>
</teiHeader>
<front><div type="abstract" xml:lang="en"><sec><title>Background/purpose</title>
<p>Measurement and classification of standing posture in the sagittal plane has important clinical implications for adolescent spinal disorders. Previous work using cluster analysis on three gross body segment orientation parameters (lower limbs, trunk, and entire body inclination) has identified three distinct postural groups of healthy subjects before pubertal peak growth: “neutral”, “sway-back”, and “leaning-forward”. Although accurate postural subgrouping may be proposed to be crucial in understanding biomechanical challenges posed by usual standing, there is currently no objective method available for class assignment. Hence, this paper introduces a novel approach to subclassify new cases objectively according to their overall sagittal balance.</p>
</sec>
<sec><title>Methods</title>
<p>Postural data previously acquired from 1,196 pre-peak height velocity (pre-PHV) subjects were used in this study. To derive a classification rule for assigning a class label (“neutral”, “sway-back”, or “leaning-forward”) to any new pre-PHV subjects, linear discriminant analysis was applied. Predictor variables were pelvic displacement, trunk lean and body lean angle. The performance of the newly developed classification algorithm was verified by adopting a cross-validation procedure.</p>
</sec>
<sec><title>Results</title>
<p>The statistical model correctly classified over 96.2 % of original grouped subjects. In the cross-validation procedure used, over 95.9 % of subjects were correctly assigned.</p>
</sec>
<sec><title>Conclusions</title>
<p>Based on three angular measures describing gross body segment orientation, our triage method is capable of reliably classifying pre-PHV subjects as either “neutral”, “sway-back”, or “leaning-forward”. The discriminant prediction equations presented here enable a highly accurate posture class allocation of new cases with a prediction capability higher than 95.9 %, thereby removing subjectivity from sagittal plane posture classification.</p>
</sec>
</div>
</front>
</TEI>
<pmc article-type="research-article"><pmc-comment>The publisher of this article does not allow downloading of the full text in XML form.</pmc-comment>
<front><journal-meta><journal-id journal-id-type="nlm-ta">Eur Spine J</journal-id>
<journal-id journal-id-type="iso-abbrev">Eur Spine J</journal-id>
<journal-title-group><journal-title>European Spine Journal</journal-title>
</journal-title-group>
<issn pub-type="ppub">0940-6719</issn>
<issn pub-type="epub">1432-0932</issn>
<publisher><publisher-name>Springer Berlin Heidelberg</publisher-name>
<publisher-loc>Berlin/Heidelberg</publisher-loc>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">24097292</article-id>
<article-id pub-id-type="pmc">3940786</article-id>
<article-id pub-id-type="publisher-id">3058</article-id>
<article-id pub-id-type="doi">10.1007/s00586-013-3058-0</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Original Article</subject>
</subj-group>
</article-categories>
<title-group><article-title>Posture class prediction of pre-peak height velocity subjects according to gross body segment orientations using linear discriminant analysis</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" corresp="yes"><name><surname>Dolphens</surname>
<given-names>Mieke</given-names>
</name>
<address><phone>+32-9-3325503</phone>
<fax>+32-9-3323811</fax>
<email>Mieke.Dolphens@UGent.be</email>
</address>
<xref ref-type="aff" rid="Aff1"></xref>
</contrib>
<contrib contrib-type="author"><name><surname>Cagnie</surname>
<given-names>Barbara</given-names>
</name>
<xref ref-type="aff" rid="Aff1"></xref>
</contrib>
<contrib contrib-type="author"><name><surname>Coorevits</surname>
<given-names>Pascal</given-names>
</name>
<xref ref-type="aff" rid="Aff2"></xref>
</contrib>
<contrib contrib-type="author"><name><surname>Vleeming</surname>
<given-names>Andry</given-names>
</name>
<xref ref-type="aff" rid="Aff1"></xref>
<xref ref-type="aff" rid="Aff3"></xref>
</contrib>
<contrib contrib-type="author"><name><surname>Palmans</surname>
<given-names>Tanneke</given-names>
</name>
<xref ref-type="aff" rid="Aff1"></xref>
</contrib>
<contrib contrib-type="author"><name><surname>Danneels</surname>
<given-names>Lieven</given-names>
</name>
<xref ref-type="aff" rid="Aff1"></xref>
</contrib>
<aff id="Aff1"><label></label>
Department of Rehabilitation Sciences and Physiotherapy, Faculty of Medicine and Health Sciences, Ghent University, Campus Heymans (UZ, 3B3), De Pintelaan 185, 9000 Ghent, Belgium</aff>
<aff id="Aff2"><label></label>
Department of Public Health and Research in Advanced Medical Informatics and Telematics, Faculty of Medicine and Health Sciences, Ghent University, Business Complex Groeninghe (Building F), Zwijnaardsesteenweg 314, 9000 Ghent, Belgium</aff>
<aff id="Aff3"><label></label>
Department of Anatomy, Medical Faculty, Center for Excellence in the Neurosciences, University of New England, 11 Hills Beach Road, Biddeford, ME 04005 USA</aff>
</contrib-group>
<pub-date pub-type="epub"><day>7</day>
<month>10</month>
<year>2013</year>
</pub-date>
<pub-date pub-type="ppub"><month>3</month>
<year>2014</year>
</pub-date>
<volume>23</volume>
<issue>3</issue>
<fpage>530</fpage>
<lpage>535</lpage>
<history><date date-type="received"><day>26</day>
<month>4</month>
<year>2013</year>
</date>
<date date-type="rev-recd"><day>9</day>
<month>8</month>
<year>2013</year>
</date>
<date date-type="accepted"><day>27</day>
<month>9</month>
<year>2013</year>
</date>
</history>
<permissions><copyright-statement>© Springer-Verlag Berlin Heidelberg 2013</copyright-statement>
</permissions>
<abstract id="Abs1"><sec><title>Background/purpose</title>
<p>Measurement and classification of standing posture in the sagittal plane has important clinical implications for adolescent spinal disorders. Previous work using cluster analysis on three gross body segment orientation parameters (lower limbs, trunk, and entire body inclination) has identified three distinct postural groups of healthy subjects before pubertal peak growth: “neutral”, “sway-back”, and “leaning-forward”. Although accurate postural subgrouping may be proposed to be crucial in understanding biomechanical challenges posed by usual standing, there is currently no objective method available for class assignment. Hence, this paper introduces a novel approach to subclassify new cases objectively according to their overall sagittal balance.</p>
</sec>
<sec><title>Methods</title>
<p>Postural data previously acquired from 1,196 pre-peak height velocity (pre-PHV) subjects were used in this study. To derive a classification rule for assigning a class label (“neutral”, “sway-back”, or “leaning-forward”) to any new pre-PHV subjects, linear discriminant analysis was applied. Predictor variables were pelvic displacement, trunk lean and body lean angle. The performance of the newly developed classification algorithm was verified by adopting a cross-validation procedure.</p>
</sec>
<sec><title>Results</title>
<p>The statistical model correctly classified over 96.2 % of original grouped subjects. In the cross-validation procedure used, over 95.9 % of subjects were correctly assigned.</p>
</sec>
<sec><title>Conclusions</title>
<p>Based on three angular measures describing gross body segment orientation, our triage method is capable of reliably classifying pre-PHV subjects as either “neutral”, “sway-back”, or “leaning-forward”. The discriminant prediction equations presented here enable a highly accurate posture class allocation of new cases with a prediction capability higher than 95.9 %, thereby removing subjectivity from sagittal plane posture classification.</p>
</sec>
</abstract>
<kwd-group xml:lang="en"><title>Keywords</title>
<kwd>Classification</kwd>
<kwd>Sagittal balance</kwd>
<kwd>Posture type prediction</kwd>
<kwd>Linear discriminant analysis</kwd>
<kwd>Young adolescence</kwd>
</kwd-group>
<custom-meta-group><custom-meta><meta-name>issue-copyright-statement</meta-name>
<meta-value>© Springer-Verlag Berlin Heidelberg 2014</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
</pmc>
</record>
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