Objective detection of subtle freezing of gait episodes in Parkinson's disease
Identifieur interne : 000174 ( Istex/Corpus ); précédent : 000173; suivant : 000175Objective detection of subtle freezing of gait episodes in Parkinson's disease
Auteurs : Arnaud Delval ; Anke H. Snijders ; Vivian Weerdesteyn ; Jacques E. Duysens ; Luc Defebvre ; Nir Giladi ; Bastiaan R. BloemSource :
- Movement Disorders [ 0885-3185 ] ; 2010-08-15.
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- KwdEn :
Abstract
Freezing of gait (FOG) is a clinically defined phenomenon of Parkinson's disease (PD). Recent evidence suggests that subtle FOG episodes can be elicited in a gait laboratory using suddenly appearing obstacles during treadmill walking. We evaluated which quantitative gait parameters identify such subtle FOG episodes. We included 10 PD patients with FOG, 10 PD patients without FOG, and 10 controls. Subjects walked on a motorized treadmill while avoiding unexpectedly appearing obstacles. Treadmill walking was videotaped, and FOG episodes were identified by two independent experts. Gait was also analyzed using detailed kinematics. Knee joint signals were processed using time–frequency analysis with combinations of sliding fast Fourier transform and wavelets transform. Twenty FOG episodes occurred during treadmill walking in 5 patients (all with clinically certified FOG), predominantly in relation to obstacle avoidance. FOG was brief when it occurred just before or after obstacle crossing and was characterized by short, rapid steps. Frequency analysis showed a typical qualitative pattern: before the FOG episode an increase in dominant frequency in the 0 to 3 Hz band (festination), followed by decreased power in 0 to 3 Hz band and an increased power in the 3 to 8 Hz band during the FOG episode. This pattern led to an increased FOG index as a qualitative measure. These approaches detected even very brief FOG with acceptable sensitivity (75–83%) and specificity (>95%). We conclude that time–frequency analysis is an appropriate approach to detect brief and subtle FOG episodes. Future work will need to decide whether this approach can support or even replace expert clinical opinion. © 2010 Movement Disorder Society
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DOI: 10.1002/mds.23159
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Recent evidence suggests that subtle FOG episodes can be elicited in a gait laboratory using suddenly appearing obstacles during treadmill walking. We evaluated which quantitative gait parameters identify such subtle FOG episodes. We included 10 PD patients with FOG, 10 PD patients without FOG, and 10 controls. Subjects walked on a motorized treadmill while avoiding unexpectedly appearing obstacles. Treadmill walking was videotaped, and FOG episodes were identified by two independent experts. Gait was also analyzed using detailed kinematics. Knee joint signals were processed using time–frequency analysis with combinations of sliding fast Fourier transform and wavelets transform. Twenty FOG episodes occurred during treadmill walking in 5 patients (all with clinically certified FOG), predominantly in relation to obstacle avoidance. FOG was brief when it occurred just before or after obstacle crossing and was characterized by short, rapid steps. Frequency analysis showed a typical qualitative pattern: before the FOG episode an increase in dominant frequency in the 0 to 3 Hz band (festination), followed by decreased power in 0 to 3 Hz band and an increased power in the 3 to 8 Hz band during the FOG episode. This pattern led to an increased FOG index as a qualitative measure. These approaches detected even very brief FOG with acceptable sensitivity (75–83%) and specificity (>95%). We conclude that time–frequency analysis is an appropriate approach to detect brief and subtle FOG episodes. Future work will need to decide whether this approach can support or even replace expert clinical opinion. © 2010 Movement Disorder Society</div></front></TEI><istex><corpusName>wiley</corpusName><author><json:item><name>Arnaud Delval MD, PhD</name><affiliations><json:string>Department of Neurology and Movement Disorders, Regional University Hospital, Lille Cedex, France</json:string><json:string>Department of Clinical Neurophysiology, Regional University Hospital, Lille Cedex, France</json:string><json:string>Department of Neurology, Donders Center for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands</json:string></affiliations></json:item><json:item><name>Anke H. Snijders MD</name><affiliations><json:string>Department of Neurology, Donders Center for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands</json:string></affiliations></json:item><json:item><name>Vivian Weerdesteyn PT, PhD</name><affiliations><json:string>Department of Rehabilitation, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands</json:string></affiliations></json:item><json:item><name>Jacques E. Duysens MD, PhD</name><affiliations><json:string>Department of Rehabilitation, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands</json:string></affiliations></json:item><json:item><name>Luc Defebvre MD, PhD</name><affiliations><json:string>Department of Neurology and Movement Disorders, Regional University Hospital, Lille Cedex, France</json:string></affiliations></json:item><json:item><name>Nir Giladi MD, PhD</name><affiliations><json:string>Movement Disorders Unit, Department of Neurology, Tel‐Aviv Sourasky Medical Center, Sackler School of Medicine, Tel‐Aviv University, Tel‐Aviv, Israel</json:string></affiliations></json:item><json:item><name>Bastiaan R. Bloem MD, PhD</name><affiliations><json:string>Department of Neurology, Donders Center for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands</json:string></affiliations></json:item></author><subject><json:item><lang><json:string>eng</json:string></lang><value>Parkinson's disease</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>freezing of gait</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>festination</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>fast Fourier transform</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>wavelets</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>frequency analysis</value></json:item></subject><language><json:string>eng</json:string></language><abstract>Freezing of gait (FOG) is a clinically defined phenomenon of Parkinson's disease (PD). Recent evidence suggests that subtle FOG episodes can be elicited in a gait laboratory using suddenly appearing obstacles during treadmill walking. We evaluated which quantitative gait parameters identify such subtle FOG episodes. We included 10 PD patients with FOG, 10 PD patients without FOG, and 10 controls. Subjects walked on a motorized treadmill while avoiding unexpectedly appearing obstacles. Treadmill walking was videotaped, and FOG episodes were identified by two independent experts. Gait was also analyzed using detailed kinematics. Knee joint signals were processed using time–frequency analysis with combinations of sliding fast Fourier transform and wavelets transform. Twenty FOG episodes occurred during treadmill walking in 5 patients (all with clinically certified FOG), predominantly in relation to obstacle avoidance. FOG was brief when it occurred just before or after obstacle crossing and was characterized by short, rapid steps. Frequency analysis showed a typical qualitative pattern: before the FOG episode an increase in dominant frequency in the 0 to 3 Hz band (festination), followed by decreased power in 0 to 3 Hz band and an increased power in the 3 to 8 Hz band during the FOG episode. This pattern led to an increased FOG index as a qualitative measure. These approaches detected even very brief FOG with acceptable sensitivity (75–83%) and specificity (>95%). We conclude that time–frequency analysis is an appropriate approach to detect brief and subtle FOG episodes. 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University Hospital, Lille Cedex, France</affiliation><affiliation>Department of Clinical Neurophysiology, Regional University Hospital, Lille Cedex, France</affiliation><affiliation>Department of Neurology, Donders Center for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands</affiliation></author><author><persName><forename type="first">Anke H.</forename><surname>Snijders</surname><roleName type="degree">MD</roleName></persName><affiliation>Department of Neurology, Donders Center for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands</affiliation></author><author><persName><forename type="first">Vivian</forename><surname>Weerdesteyn</surname><roleName type="degree">PT, PhD</roleName></persName><affiliation>Department of Rehabilitation, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands</affiliation></author><author><persName><forename type="first">Jacques E.</forename><surname>Duysens</surname><roleName type="degree">MD, PhD</roleName></persName><affiliation>Department of Rehabilitation, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands</affiliation></author><author><persName><forename type="first">Luc</forename><surname>Defebvre</surname><roleName type="degree">MD, PhD</roleName></persName><affiliation>Department of Neurology and Movement Disorders, Regional University Hospital, Lille Cedex, France</affiliation></author><author><persName><forename type="first">Nir</forename><surname>Giladi</surname><roleName type="degree">MD, PhD</roleName></persName><affiliation>Movement Disorders Unit, Department of Neurology, Tel‐Aviv Sourasky Medical Center, Sackler School of Medicine, Tel‐Aviv University, Tel‐Aviv, Israel</affiliation></author><author><persName><forename type="first">Bastiaan R.</forename><surname>Bloem</surname><roleName type="degree">MD, PhD</roleName></persName><affiliation>Department of Neurology, Donders 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Recent evidence suggests that subtle FOG episodes can be elicited in a gait laboratory using suddenly appearing obstacles during treadmill walking. We evaluated which quantitative gait parameters identify such subtle FOG episodes. We included 10 PD patients with FOG, 10 PD patients without FOG, and 10 controls. Subjects walked on a motorized treadmill while avoiding unexpectedly appearing obstacles. Treadmill walking was videotaped, and FOG episodes were identified by two independent experts. Gait was also analyzed using detailed kinematics. Knee joint signals were processed using time–frequency analysis with combinations of sliding fast Fourier transform and wavelets transform. Twenty FOG episodes occurred during treadmill walking in 5 patients (all with clinically certified FOG), predominantly in relation to obstacle avoidance. FOG was brief when it occurred just before or after obstacle crossing and was characterized by short, rapid steps. Frequency analysis showed a typical qualitative pattern: before the FOG episode an increase in dominant frequency in the 0 to 3 Hz band (festination), followed by decreased power in 0 to 3 Hz band and an increased power in the 3 to 8 Hz band during the FOG episode. This pattern led to an increased FOG index as a qualitative measure. These approaches detected even very brief FOG with acceptable sensitivity (75–83%) and specificity (>95%). We conclude that time–frequency analysis is an appropriate approach to detect brief and subtle FOG episodes. 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href="file:MDS.MDS23159.pdf"></link></linkGroup></publicationMeta><contentMeta><countGroup><count type="figureTotal" number="5"></count><count type="tableTotal" number="1"></count><count type="referenceTotal" number="30"></count><count type="wordTotal" number="7263"></count></countGroup><titleGroup><title type="main" xml:lang="en">Objective detection of subtle freezing of gait episodes in Parkinson's disease<link href="#fn4"></link> <link href="#fn5"></link></title><title type="short" xml:lang="en">Detection of Subtle FOG</title></titleGroup><creators><creator xml:id="au1" creatorRole="author" affiliationRef="#af1 #af2 #af3" corresponding="yes"><personName><givenNames>Arnaud</givenNames><familyName>Delval</familyName><degrees>MD, PhD</degrees></personName><contactDetails><email normalForm="arnaud.delval@chru-lille.fr">arnaud.delval@chru‐lille.fr</email></contactDetails></creator><creator xml:id="au2" creatorRole="author" affiliationRef="#af3"><personName><givenNames>Anke H.</givenNames><familyName>Snijders</familyName><degrees>MD</degrees></personName></creator><creator xml:id="au3" creatorRole="author" affiliationRef="#af4"><personName><givenNames>Vivian</givenNames><familyName>Weerdesteyn</familyName><degrees>PT, PhD</degrees></personName></creator><creator xml:id="au4" creatorRole="author" affiliationRef="#af4"><personName><givenNames>Jacques E.</givenNames><familyName>Duysens</familyName><degrees>MD, PhD</degrees></personName></creator><creator xml:id="au5" creatorRole="author" affiliationRef="#af1"><personName><givenNames>Luc</givenNames><familyName>Defebvre</familyName><degrees>MD, PhD</degrees></personName></creator><creator xml:id="au6" creatorRole="author" affiliationRef="#af5"><personName><givenNames>Nir</givenNames><familyName>Giladi</familyName><degrees>MD, PhD</degrees></personName></creator><creator xml:id="au7" creatorRole="author" affiliationRef="#af3"><personName><givenNames>Bastiaan R.</givenNames><familyName>Bloem</familyName><degrees>MD, PhD</degrees></personName></creator></creators><affiliationGroup><affiliation xml:id="af1" countryCode="FR" type="organization"><unparsedAffiliation>Department of Neurology and Movement Disorders, Regional University Hospital, Lille Cedex, France</unparsedAffiliation></affiliation><affiliation xml:id="af2" countryCode="FR" type="organization"><unparsedAffiliation>Department of Clinical Neurophysiology, Regional University Hospital, Lille Cedex, France</unparsedAffiliation></affiliation><affiliation xml:id="af3" countryCode="NL" type="organization"><unparsedAffiliation>Department of Neurology, Donders Center for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands</unparsedAffiliation></affiliation><affiliation xml:id="af4" countryCode="NL" type="organization"><unparsedAffiliation>Department of Rehabilitation, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands</unparsedAffiliation></affiliation><affiliation xml:id="af5" countryCode="IL" type="organization"><unparsedAffiliation>Movement Disorders Unit, Department of Neurology, Tel‐Aviv Sourasky Medical Center, Sackler School of Medicine, Tel‐Aviv University, Tel‐Aviv, Israel</unparsedAffiliation></affiliation></affiliationGroup><keywordGroup xml:lang="en" type="author"><keyword xml:id="kwd1">Parkinson's disease</keyword><keyword xml:id="kwd2">freezing of gait</keyword><keyword xml:id="kwd3">festination</keyword><keyword xml:id="kwd4">fast Fourier transform</keyword><keyword xml:id="kwd5">wavelets</keyword><keyword xml:id="kwd6">frequency analysis</keyword></keywordGroup><abstractGroup><abstract type="main" xml:lang="en"><title type="main">Abstract</title><p>Freezing of gait (FOG) is a clinically defined phenomenon of Parkinson's disease (PD). Recent evidence suggests that subtle FOG episodes can be elicited in a gait laboratory using suddenly appearing obstacles during treadmill walking. We evaluated which quantitative gait parameters identify such subtle FOG episodes. We included 10 PD patients with FOG, 10 PD patients without FOG, and 10 controls. Subjects walked on a motorized treadmill while avoiding unexpectedly appearing obstacles. Treadmill walking was videotaped, and FOG episodes were identified by two independent experts. Gait was also analyzed using detailed kinematics. Knee joint signals were processed using time–frequency analysis with combinations of sliding fast Fourier transform and wavelets transform. Twenty FOG episodes occurred during treadmill walking in 5 patients (all with clinically certified FOG), predominantly in relation to obstacle avoidance. FOG was brief when it occurred just before or after obstacle crossing and was characterized by short, rapid steps. Frequency analysis showed a typical qualitative pattern: before the FOG episode an increase in dominant frequency in the 0 to 3 Hz band (festination), followed by decreased power in 0 to 3 Hz band and an increased power in the 3 to 8 Hz band during the FOG episode. This pattern led to an increased FOG index as a qualitative measure. These approaches detected even very brief FOG with acceptable sensitivity (75–83%) and specificity (>95%). We conclude that time–frequency analysis is an appropriate approach to detect brief and subtle FOG episodes. Future work will need to decide whether this approach can support or even replace expert clinical opinion. © 2010 Movement Disorder Society</p></abstract></abstractGroup></contentMeta><noteGroup><note xml:id="fn4"><p>Potential conflict of interest: Nothing to report.</p></note><note xml:id="fn5"><p>The protocol has been approved by the local committee of ethics.</p></note></noteGroup></header></component></istex:document></istex:metadataXml><!--Version 0.6 générée le 3-12-2015--><mods version="3.6"><titleInfo lang="en"><title>Objective detection of subtle freezing of gait episodes in Parkinson's disease</title></titleInfo><titleInfo type="abbreviated" lang="en"><title>Detection of Subtle FOG</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Objective detection of subtle freezing of gait episodes in Parkinson's disease</title></titleInfo><name type="personal"><namePart type="given">Arnaud</namePart><namePart type="family">Delval</namePart><namePart type="termsOfAddress">MD, PhD</namePart><affiliation>Department of Neurology and Movement Disorders, Regional University Hospital, Lille Cedex, France</affiliation><affiliation>Department of Clinical Neurophysiology, Regional University Hospital, Lille Cedex, France</affiliation><affiliation>Department of Neurology, Donders Center for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands</affiliation><description>Correspondence: Neurology Department, Hôpital Salengro, F‐59037 Lille Cedex, France</description><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Anke H.</namePart><namePart type="family">Snijders</namePart><namePart type="termsOfAddress">MD</namePart><affiliation>Department of Neurology, Donders Center for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Vivian</namePart><namePart type="family">Weerdesteyn</namePart><namePart type="termsOfAddress">PT, PhD</namePart><affiliation>Department of Rehabilitation, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Jacques E.</namePart><namePart type="family">Duysens</namePart><namePart type="termsOfAddress">MD, PhD</namePart><affiliation>Department of Rehabilitation, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Luc</namePart><namePart type="family">Defebvre</namePart><namePart type="termsOfAddress">MD, PhD</namePart><affiliation>Department of Neurology and Movement Disorders, Regional University Hospital, Lille Cedex, France</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Nir</namePart><namePart type="family">Giladi</namePart><namePart type="termsOfAddress">MD, PhD</namePart><affiliation>Movement Disorders Unit, Department of Neurology, Tel‐Aviv Sourasky Medical Center, Sackler School of Medicine, Tel‐Aviv University, Tel‐Aviv, Israel</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Bastiaan R.</namePart><namePart type="family">Bloem</namePart><namePart type="termsOfAddress">MD, PhD</namePart><affiliation>Department of Neurology, Donders Center for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre authority="originalCategForm">article</genre><originInfo><publisher>Wiley Subscription Services, Inc., A Wiley Company</publisher><place><placeTerm type="text">Hoboken</placeTerm></place><dateIssued encoding="w3cdtf">2010-08-15</dateIssued><dateCaptured encoding="w3cdtf">2009-07-06</dateCaptured><dateValid encoding="w3cdtf">2010-03-17</dateValid><copyrightDate encoding="w3cdtf">2010</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType><extent unit="figures">5</extent><extent unit="tables">1</extent><extent unit="references">30</extent><extent unit="words">7263</extent></physicalDescription><abstract lang="en">Freezing of gait (FOG) is a clinically defined phenomenon of Parkinson's disease (PD). Recent evidence suggests that subtle FOG episodes can be elicited in a gait laboratory using suddenly appearing obstacles during treadmill walking. We evaluated which quantitative gait parameters identify such subtle FOG episodes. We included 10 PD patients with FOG, 10 PD patients without FOG, and 10 controls. Subjects walked on a motorized treadmill while avoiding unexpectedly appearing obstacles. Treadmill walking was videotaped, and FOG episodes were identified by two independent experts. Gait was also analyzed using detailed kinematics. Knee joint signals were processed using time–frequency analysis with combinations of sliding fast Fourier transform and wavelets transform. Twenty FOG episodes occurred during treadmill walking in 5 patients (all with clinically certified FOG), predominantly in relation to obstacle avoidance. FOG was brief when it occurred just before or after obstacle crossing and was characterized by short, rapid steps. Frequency analysis showed a typical qualitative pattern: before the FOG episode an increase in dominant frequency in the 0 to 3 Hz band (festination), followed by decreased power in 0 to 3 Hz band and an increased power in the 3 to 8 Hz band during the FOG episode. This pattern led to an increased FOG index as a qualitative measure. These approaches detected even very brief FOG with acceptable sensitivity (75–83%) and specificity (>95%). We conclude that time–frequency analysis is an appropriate approach to detect brief and subtle FOG episodes. Future work will need to decide whether this approach can support or even replace expert clinical opinion. © 2010 Movement Disorder Society</abstract><note type="content">*Potential conflict of interest: Nothing to report.</note><note type="content">*The protocol has been approved by the local committee of ethics.</note><subject lang="en"><genre>Keywords</genre><topic>Parkinson's disease</topic><topic>freezing of gait</topic><topic>festination</topic><topic>fast Fourier transform</topic><topic>wavelets</topic><topic>frequency analysis</topic></subject><relatedItem type="host"><titleInfo><title>Movement Disorders</title></titleInfo><titleInfo type="abbreviated"><title>Mov. Disord.</title></titleInfo><subject><genre>article category</genre><topic>Research Article</topic></subject><identifier type="ISSN">0885-3185</identifier><identifier type="eISSN">1531-8257</identifier><identifier type="DOI">10.1002/(ISSN)1531-8257</identifier><identifier type="PublisherID">MDS</identifier><part><date>2010</date><detail type="volume"><caption>vol.</caption><number>25</number></detail><detail type="issue"><caption>no.</caption><number>11</number></detail><extent unit="pages"><start>1684</start><end>1693</end><total>10</total></extent></part></relatedItem><identifier type="istex">2FC6DAA12D9EA0F0A18480B6C09F29309059D962</identifier><identifier type="DOI">10.1002/mds.23159</identifier><identifier type="ArticleID">MDS23159</identifier><accessCondition type="use and reproduction" contentType="copyright">Copyright © 2010 Movement Disorder Society</accessCondition><recordInfo><recordOrigin>Wiley Subscription Services, Inc., A Wiley Company</recordOrigin><recordContentSource>WILEY</recordContentSource></recordInfo></mods></metadata><serie></serie></istex></record>Pour manipuler ce document sous Unix (Dilib)
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