An Automated Recording Method in Clinical Consultation to Rate the Limp in Lower Limb Osteoarthritis
Identifieur interne : 000799 ( Pmc/Curation ); précédent : 000798; suivant : 000800An Automated Recording Method in Clinical Consultation to Rate the Limp in Lower Limb Osteoarthritis
Auteurs : R. Barrois [France] ; Th. Gregory [France] ; L. Oudre [France] ; Th. Moreau [France] ; Ch. Truong [France] ; A. Aram Pulini [France] ; A. Vienne [France] ; Ch. Labourdette [France] ; N. Vayatis [France] ; S. Buffat [France] ; A. Yelnik [France] ; C. De Waele [France] ; S. Laporte [France] ; P. P. Vidal [France] ; D. Ricard [France]Source :
- PLoS ONE [ 1932-6203 ] ; 2016.
Abstract
For diagnosis and follow up, it is important to be able to quantify limp in an objective, and precise way adapted to daily clinical consultation. The purpose of this exploratory study was to determine if an inertial sensor-based method could provide simple features that correlate with the severity of lower limb osteoarthritis evaluated by the WOMAC index without the use of step detection in the signal processing. Forty-eight patients with lower limb osteoarthritis formed two severity groups separated by the median of the WOMAC index (G1, G2). Twelve asymptomatic age-matched control subjects formed the control group (G0). Subjects were asked to walk straight 10 meters forward and 10 meters back at self-selected walking speeds with inertial measurement units (IMU) (3-D accelerometers, 3-D gyroscopes and 3-D magnetometers) attached on the head, the lower back (L3-L4) and both feet. Sixty parameters corresponding to the mean and the root mean square (RMS) of the recorded signals on the various sensors (head, lower back and feet), in the various axes, in the various frames were computed. Parameters were defined as discriminating when they showed statistical differences between the three groups. In total, four parameters were found discriminating: mean and RMS of the norm of the acceleration in the horizontal plane for contralateral and ipsilateral foot in the doctor’s office frame. No discriminating parameter was found on the head or the lower back. No discriminating parameter was found in the sensor linked frames. This study showed that two IMUs placed on both feet and a step detection free signal processing method could be an objective and quantitative complement to the clinical examination of the physician in everyday practice. Our method provides new automatically computed parameters that could be used for the comprehension of lower limb osteoarthritis. It may not only be used in medical consultation to score patients but also to monitor the evolution of their clinical syndrome during and after rehabilitation. Finally, it paves the way for the quantification of gait in other fields such as neurology and for monitoring the gait at a patient’s home.
Url:
DOI: 10.1371/journal.pone.0164975
PubMed: 27776168
PubMed Central: 5077168
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<sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">An Automated Recording Method in Clinical Consultation to Rate the Limp in Lower Limb Osteoarthritis</title>
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<author><name sortKey="Laporte, S" sort="Laporte, S" uniqKey="Laporte S" first="S." last="Laporte">S. Laporte</name>
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<author><name sortKey="Vidal, P P" sort="Vidal, P P" uniqKey="Vidal P" first="P. P." last="Vidal">P. P. Vidal</name>
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<series><title level="j">PLoS ONE</title>
<idno type="eISSN">1932-6203</idno>
<imprint><date when="2016">2016</date>
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<front><div type="abstract" xml:lang="en"><p>For diagnosis and follow up, it is important to be able to quantify limp in an objective, and precise way adapted to daily clinical consultation. The purpose of this exploratory study was to determine if an inertial sensor-based method could provide simple features that correlate with the severity of lower limb osteoarthritis evaluated by the WOMAC index without the use of step detection in the signal processing. Forty-eight patients with lower limb osteoarthritis formed two severity groups separated by the median of the WOMAC index (G1, G2). Twelve asymptomatic age-matched control subjects formed the control group (G0). Subjects were asked to walk straight 10 meters forward and 10 meters back at self-selected walking speeds with inertial measurement units (IMU) (3-D accelerometers, 3-D gyroscopes and 3-D magnetometers) attached on the head, the lower back (L3-L4) and both feet. Sixty parameters corresponding to the mean and the root mean square (RMS) of the recorded signals on the various sensors (head, lower back and feet), in the various axes, in the various frames were computed. Parameters were defined as discriminating when they showed statistical differences between the three groups. In total, four parameters were found discriminating: mean and RMS of the norm of the acceleration in the horizontal plane for contralateral and ipsilateral foot in the doctor’s office frame. No discriminating parameter was found on the head or the lower back. No discriminating parameter was found in the sensor linked frames. This study showed that two IMUs placed on both feet and a step detection free signal processing method could be an objective and quantitative complement to the clinical examination of the physician in everyday practice. Our method provides new automatically computed parameters that could be used for the comprehension of lower limb osteoarthritis. It may not only be used in medical consultation to score patients but also to monitor the evolution of their clinical syndrome during and after rehabilitation. Finally, it paves the way for the quantification of gait in other fields such as neurology and for monitoring the gait at a patient’s home.</p>
</div>
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<pmc article-type="research-article"><pmc-dir>properties open_access</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-ta">PLoS One</journal-id>
<journal-id journal-id-type="iso-abbrev">PLoS ONE</journal-id>
<journal-id journal-id-type="publisher-id">plos</journal-id>
<journal-id journal-id-type="pmc">plosone</journal-id>
<journal-title-group><journal-title>PLoS ONE</journal-title>
</journal-title-group>
<issn pub-type="epub">1932-6203</issn>
<publisher><publisher-name>Public Library of Science</publisher-name>
<publisher-loc>San Francisco, CA USA</publisher-loc>
</publisher>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">27776168</article-id>
<article-id pub-id-type="pmc">5077168</article-id>
<article-id pub-id-type="doi">10.1371/journal.pone.0164975</article-id>
<article-id pub-id-type="publisher-id">PONE-D-15-43758</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject>
<subj-group><subject>Biomechanics</subject>
<subj-group><subject>Biological Locomotion</subject>
<subj-group><subject>Gait Analysis</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject>
<subj-group><subject>Physiology</subject>
<subj-group><subject>Biological Locomotion</subject>
<subj-group><subject>Gait Analysis</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Medicine and Health Sciences</subject>
<subj-group><subject>Physiology</subject>
<subj-group><subject>Biological Locomotion</subject>
<subj-group><subject>Gait Analysis</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject>
<subj-group><subject>Biomechanics</subject>
<subj-group><subject>Biological Locomotion</subject>
<subj-group><subject>Walking</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject>
<subj-group><subject>Physiology</subject>
<subj-group><subject>Biological Locomotion</subject>
<subj-group><subject>Walking</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Medicine and Health Sciences</subject>
<subj-group><subject>Physiology</subject>
<subj-group><subject>Biological Locomotion</subject>
<subj-group><subject>Walking</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Medicine and Health Sciences</subject>
<subj-group><subject>Rheumatology</subject>
<subj-group><subject>Arthritis</subject>
<subj-group><subject>Osteoarthritis</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Physical Sciences</subject>
<subj-group><subject>Physics</subject>
<subj-group><subject>Classical Mechanics</subject>
<subj-group><subject>Acceleration</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Physical Sciences</subject>
<subj-group><subject>Physics</subject>
<subj-group><subject>Classical Mechanics</subject>
<subj-group><subject>Motion</subject>
<subj-group><subject>Velocity</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Physical Sciences</subject>
<subj-group><subject>Physics</subject>
<subj-group><subject>Classical Mechanics</subject>
<subj-group><subject>Motion</subject>
<subj-group><subject>Inertia</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Biology and Life Sciences</subject>
<subj-group><subject>Anatomy</subject>
<subj-group><subject>Musculoskeletal System</subject>
<subj-group><subject>Limbs (Anatomy)</subject>
<subj-group><subject>Legs</subject>
<subj-group><subject>Feet (Anatomy)</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Medicine and Health Sciences</subject>
<subj-group><subject>Anatomy</subject>
<subj-group><subject>Musculoskeletal System</subject>
<subj-group><subject>Limbs (Anatomy)</subject>
<subj-group><subject>Legs</subject>
<subj-group><subject>Feet (Anatomy)</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Research and Analysis Methods</subject>
<subj-group><subject>Mathematical and Statistical Techniques</subject>
<subj-group><subject>Statistical Methods</subject>
<subj-group><subject>Analysis of Variance</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
<subj-group subj-group-type="Discipline-v3"><subject>Physical Sciences</subject>
<subj-group><subject>Mathematics</subject>
<subj-group><subject>Statistics (Mathematics)</subject>
<subj-group><subject>Statistical Methods</subject>
<subj-group><subject>Analysis of Variance</subject>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
</subj-group>
</article-categories>
<title-group><article-title>An Automated Recording Method in Clinical Consultation to Rate the Limp in Lower Limb Osteoarthritis</article-title>
<alt-title alt-title-type="running-head">An Automated Recording Method in Clinical Consultation to Rate the Limp in Lower Limb Osteoarthritis</alt-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Barrois</surname>
<given-names>R.</given-names>
</name>
<xref ref-type="aff" rid="aff001"><sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Gregory</surname>
<given-names>Th.</given-names>
</name>
<xref ref-type="aff" rid="aff002"><sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Oudre</surname>
<given-names>L.</given-names>
</name>
<xref ref-type="aff" rid="aff001"><sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff003"><sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Moreau</surname>
<given-names>Th.</given-names>
</name>
<xref ref-type="aff" rid="aff001"><sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Truong</surname>
<given-names>Ch.</given-names>
</name>
<xref ref-type="aff" rid="aff001"><sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Aram Pulini</surname>
<given-names>A.</given-names>
</name>
<xref ref-type="aff" rid="aff001"><sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Vienne</surname>
<given-names>A.</given-names>
</name>
<xref ref-type="aff" rid="aff001"><sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Labourdette</surname>
<given-names>Ch.</given-names>
</name>
<xref ref-type="aff" rid="aff001"><sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff004"><sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Vayatis</surname>
<given-names>N.</given-names>
</name>
<xref ref-type="aff" rid="aff001"><sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff004"><sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Buffat</surname>
<given-names>S.</given-names>
</name>
<xref ref-type="aff" rid="aff001"><sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff005"><sup>5</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Yelnik</surname>
<given-names>A.</given-names>
</name>
<xref ref-type="aff" rid="aff001"><sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff006"><sup>6</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>de Waele</surname>
<given-names>C.</given-names>
</name>
<xref ref-type="aff" rid="aff001"><sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Laporte</surname>
<given-names>S.</given-names>
</name>
<xref ref-type="aff" rid="aff007"><sup>7</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Vidal</surname>
<given-names>P. P.</given-names>
</name>
<xref ref-type="aff" rid="aff001"><sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Ricard</surname>
<given-names>D.</given-names>
</name>
<xref ref-type="aff" rid="aff001"><sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff008"><sup>8</sup>
</xref>
<xref ref-type="corresp" rid="cor001">*</xref>
</contrib>
</contrib-group>
<aff id="aff001"><label>1</label>
<addr-line>Cognition and Action Group, Cognac-G, CNRS, Université Paris Descartes, SSA, Paris, France</addr-line>
</aff>
<aff id="aff002"><label>2</label>
<addr-line>Service de chirurgie orthopédique et traumatologie, HEGP, université Paris Descartes, Paris, France</addr-line>
</aff>
<aff id="aff003"><label>3</label>
<addr-line>Institut Galilée, Université Paris 13, Villetaneuse, France</addr-line>
</aff>
<aff id="aff004"><label>4</label>
<addr-line>Centre des Mathématiques et de Leurs Applications, Ecole Normale Supérieure de Cachan, Cachan, France</addr-line>
</aff>
<aff id="aff005"><label>5</label>
<addr-line>Institut de Recherche Biomédicale des Armées, Brétigny-sur-Orge, France</addr-line>
</aff>
<aff id="aff006"><label>6</label>
<addr-line>PRM Department, GH St Louis Lariboisière F. Widal, AP-HP, Diderot University, Paris, France</addr-line>
</aff>
<aff id="aff007"><label>7</label>
<addr-line>LBM/Institut de Biomécanique Humaine Georges Charpak, Arts et Métiers Paris Tech, 151 Boulevard de l’Hôpital, 75003, Paris, France</addr-line>
</aff>
<aff id="aff008"><label>8</label>
<addr-line>Service de Neurologie, Hôpital d’Instruction des Armées de Percy, Service de Santé des Armées, Clamart, France</addr-line>
</aff>
<contrib-group><contrib contrib-type="editor"><name><surname>Gard</surname>
<given-names>Steven Allen</given-names>
</name>
<role>Editor</role>
<xref ref-type="aff" rid="edit1"></xref>
</contrib>
</contrib-group>
<aff id="edit1"><addr-line>Northwestern University, UNITED STATES</addr-line>
</aff>
<author-notes><fn fn-type="COI-statement" id="coi001"><p><bold>Competing Interests: </bold>
The authors have declared that no competing interests exist.</p>
</fn>
<fn fn-type="con"><p><list list-type="simple"><list-item><p><bold>Conceptualization:</bold>
ThG ChL NV SB AY CdW PPV DR.</p>
</list-item>
<list-item><p><bold>Data curation:</bold>
RB AAP.</p>
</list-item>
<list-item><p><bold>Formal analysis:</bold>
RB LO ThM ChT AAP AV ChL.</p>
</list-item>
<list-item><p><bold>Funding acquisition:</bold>
PPV.</p>
</list-item>
<list-item><p><bold>Investigation:</bold>
RB ThG DR.</p>
</list-item>
<list-item><p><bold>Methodology:</bold>
ThG ChL NV SB AY CdW PPV DR.</p>
</list-item>
<list-item><p><bold>Project administration:</bold>
RB ThG PPV DR.</p>
</list-item>
<list-item><p><bold>Resources:</bold>
ThG.</p>
</list-item>
<list-item><p><bold>Software:</bold>
RB LO ThM ChT AAP AV ChL.</p>
</list-item>
<list-item><p><bold>Supervision:</bold>
ThG PPV DR.</p>
</list-item>
<list-item><p><bold>Validation:</bold>
RB ThG LO AAP AV ChL PPV DR.</p>
</list-item>
<list-item><p><bold>Visualization:</bold>
RB ThM DR.</p>
</list-item>
<list-item><p><bold>Writing – original draft:</bold>
RB LO PPV DR.</p>
</list-item>
<list-item><p><bold>Writing – review & editing:</bold>
RB LO SL PPV DR.</p>
</list-item>
</list>
</p>
</fn>
<corresp id="cor001">* E-mail: <email>damien.ricard@m4x.org</email>
</corresp>
</author-notes>
<pub-date pub-type="epub"><day>24</day>
<month>10</month>
<year>2016</year>
</pub-date>
<pub-date pub-type="collection"><year>2016</year>
</pub-date>
<volume>11</volume>
<issue>10</issue>
<elocation-id>e0164975</elocation-id>
<history><date date-type="received"><day>7</day>
<month>10</month>
<year>2015</year>
</date>
<date date-type="accepted"><day>4</day>
<month>10</month>
<year>2016</year>
</date>
</history>
<permissions><copyright-statement>© 2016 Barrois et al</copyright-statement>
<copyright-year>2016</copyright-year>
<copyright-holder>Barrois et al</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/"><license-p>This is an open access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License</ext-link>
, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p>
</license>
</permissions>
<self-uri content-type="pdf" xlink:href="pone.0164975.pdf"></self-uri>
<abstract><p>For diagnosis and follow up, it is important to be able to quantify limp in an objective, and precise way adapted to daily clinical consultation. The purpose of this exploratory study was to determine if an inertial sensor-based method could provide simple features that correlate with the severity of lower limb osteoarthritis evaluated by the WOMAC index without the use of step detection in the signal processing. Forty-eight patients with lower limb osteoarthritis formed two severity groups separated by the median of the WOMAC index (G1, G2). Twelve asymptomatic age-matched control subjects formed the control group (G0). Subjects were asked to walk straight 10 meters forward and 10 meters back at self-selected walking speeds with inertial measurement units (IMU) (3-D accelerometers, 3-D gyroscopes and 3-D magnetometers) attached on the head, the lower back (L3-L4) and both feet. Sixty parameters corresponding to the mean and the root mean square (RMS) of the recorded signals on the various sensors (head, lower back and feet), in the various axes, in the various frames were computed. Parameters were defined as discriminating when they showed statistical differences between the three groups. In total, four parameters were found discriminating: mean and RMS of the norm of the acceleration in the horizontal plane for contralateral and ipsilateral foot in the doctor’s office frame. No discriminating parameter was found on the head or the lower back. No discriminating parameter was found in the sensor linked frames. This study showed that two IMUs placed on both feet and a step detection free signal processing method could be an objective and quantitative complement to the clinical examination of the physician in everyday practice. Our method provides new automatically computed parameters that could be used for the comprehension of lower limb osteoarthritis. It may not only be used in medical consultation to score patients but also to monitor the evolution of their clinical syndrome during and after rehabilitation. Finally, it paves the way for the quantification of gait in other fields such as neurology and for monitoring the gait at a patient’s home.</p>
</abstract>
<funding-group><funding-statement>SATT Innov Ile de France. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.</funding-statement>
</funding-group>
<counts><fig-count count="3"></fig-count>
<table-count count="3"></table-count>
<page-count count="15"></page-count>
</counts>
<custom-meta-group><custom-meta id="data-availability"><meta-name>Data Availability</meta-name>
<meta-value>All relevant data are within the paper and its Supporting Information files.</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
<notes><title>Data Availability</title>
<p>All relevant data are within the paper and its Supporting Information files.</p>
</notes>
</front>
</pmc>
</record>
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