Power‐law temporal autocorrelation of activity reflects severity of parkinsonism
Identifieur interne : 001A33 ( Istex/Corpus ); précédent : 001A32; suivant : 001A34Power‐law temporal autocorrelation of activity reflects severity of parkinsonism
Auteurs : Weidong Pan ; Kyoko Ohashi ; Yoshiharu Yamamoto ; Shin KwakSource :
- Movement Disorders [ 0885-3185 ] ; 2007-07-15.
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Abstract
We aimed to obtain a reliable, objective scale representing disease severity for appropriate management of patients with Parkinson's disease (PD). Nineteen patients with PD at the Department of Neurology, Tokyo University Hospital, were classified into mild (n = 10) or severe groups (n = 9) depending on their Hoehn‐Yahr scores, and wore accelerometers on their wrists for more than 6 consecutive days. During this time we monitored their subjective assessments of symptom severity and analyzed the power‐law exponents (α) for local maxima and minima of fluctuations in the activity time series. Statistical comparisons were made between the severe and mild groups and of individual patients on “good condition” and “bad condition” days, as well as between days before and after antiparkinsonism medication. In all patients, the α for local maxima was always lower when parkinsonism was mild than when severe. Presence of tremor did not influence the α for local maxima. As the lower α value for local maxima of fluctuations in activity records reflects more frequent switching behavior from low to high physical activities or the severity of akinesia, actigraph monitoring of parkinsonism, and analysis of its power‐law correlation may provide useful objective information for controlling parkinsonism in outpatient clinics and for evaluating new antiparkinsonism drugs. © 2007 Movement Disorder Society
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DOI: 10.1002/mds.21527
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Nineteen patients with PD at the Department of Neurology, Tokyo University Hospital, were classified into mild (n = 10) or severe groups (n = 9) depending on their Hoehn‐Yahr scores, and wore accelerometers on their wrists for more than 6 consecutive days. During this time we monitored their subjective assessments of symptom severity and analyzed the power‐law exponents (α) for local maxima and minima of fluctuations in the activity time series. Statistical comparisons were made between the severe and mild groups and of individual patients on “good condition” and “bad condition” days, as well as between days before and after antiparkinsonism medication. In all patients, the α for local maxima was always lower when parkinsonism was mild than when severe. Presence of tremor did not influence the α for local maxima. As the lower α value for local maxima of fluctuations in activity records reflects more frequent switching behavior from low to high physical activities or the severity of akinesia, actigraph monitoring of parkinsonism, and analysis of its power‐law correlation may provide useful objective information for controlling parkinsonism in outpatient clinics and for evaluating new antiparkinsonism drugs. © 2007 Movement Disorder Society</div></front></TEI><istex><corpusName>wiley</corpusName><author><json:item><name>Weidong Pan MD, PhD</name><affiliations><json:string>Department of Neurology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan</json:string></affiliations></json:item><json:item><name>Kyoko Ohashi PhD</name><affiliations><json:string>Educational Physiology Laboratory, Graduate School of Education, The University of Tokyo, Tokyo, Japan</json:string><json:string>Developmental Biopsychiatry Research Program, McLean Hospital/Harvard Medical School, Belmont, Massachusetts, USA</json:string></affiliations></json:item><json:item><name>Yoshiharu Yamamoto PhD</name><affiliations><json:string>Educational Physiology Laboratory, Graduate School of Education, The University of Tokyo, Tokyo, Japan</json:string></affiliations></json:item><json:item><name>Shin Kwak MD, PhD</name><affiliations><json:string>Department of Neurology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan</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>actigraph</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>akinesia</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>fractal analysis</value></json:item><json:item><lang><json:string>eng</json:string></lang><value>power‐law temporal autocorrelation</value></json:item></subject><language><json:string>eng</json:string></language><abstract>We aimed to obtain a reliable, objective scale representing disease severity for appropriate management of patients with Parkinson's disease (PD). 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As the lower α value for local maxima of fluctuations in activity records reflects more frequent switching behavior from low to high physical activities or the severity of akinesia, actigraph monitoring of parkinsonism, and analysis of its power‐law correlation may provide useful objective information for controlling parkinsonism in outpatient clinics and for evaluating new antiparkinsonism drugs. © 2007 Movement Disorder Society</p></abstract><textClass xml:lang="en"><keywords scheme="keyword"><list><head>Keywords</head><item><term>Parkinson's disease</term></item><item><term>actigraph</term></item><item><term>akinesia</term></item><item><term>fractal analysis</term></item><item><term>power‐law temporal autocorrelation</term></item></list></keywords></textClass><textClass><keywords scheme="Journal Subject"><list><head>Article category</head><item><term>Research Article</term></item></list></keywords></textClass></profileDesc><revisionDesc><change when="2006-12-27">Received</change><change when="2007-03-19">Registration</change><change when="2007-07-15">Published</change></revisionDesc></teiHeader></istex:fulltextTEI><json:item><original>false</original><mimetype>text/plain</mimetype><extension>txt</extension><uri>https://api.istex.fr/document/CD9CDC7C52E2C692EFE7BE513FB2550CE6DD53C9/fulltext/txt</uri></json:item></fulltext><metadata><istex:metadataXml wicri:clean="Wiley, elements deleted: body"><istex:xmlDeclaration>version="1.0" encoding="UTF-8" standalone="yes"</istex:xmlDeclaration><istex:document><component version="2.0" type="serialArticle" xml:lang="en"><header><publicationMeta level="product"><publisherInfo><publisherName>Wiley Subscription Services, Inc., A Wiley Company</publisherName><publisherLoc>Hoboken</publisherLoc></publisherInfo><doi registered="yes">10.1002/(ISSN)1531-8257</doi><issn type="print">0885-3185</issn><issn type="electronic">1531-8257</issn><idGroup><id type="product" value="MDS"></id></idGroup><titleGroup><title type="main" xml:lang="en" sort="MOVEMENT DISORDERS">Movement Disorders</title><title type="subtitle">Official Journal of the Movement Disorder Society</title><title type="short">Mov. 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Nineteen patients with PD at the Department of Neurology, Tokyo University Hospital, were classified into mild (n = 10) or severe groups (n = 9) depending on their Hoehn‐Yahr scores, and wore accelerometers on their wrists for more than 6 consecutive days. During this time we monitored their subjective assessments of symptom severity and analyzed the power‐law exponents (α) for local maxima and minima of fluctuations in the activity time series. Statistical comparisons were made between the severe and mild groups and of individual patients on “good condition” and “bad condition” days, as well as between days before and after antiparkinsonism medication. In all patients, the α for local maxima was always lower when parkinsonism was mild than when severe. Presence of tremor did not influence the α for local maxima. As the lower α value for local maxima of fluctuations in activity records reflects more frequent switching behavior from low to high physical activities or the severity of akinesia, actigraph monitoring of parkinsonism, and analysis of its power‐law correlation may provide useful objective information for controlling parkinsonism in outpatient clinics and for evaluating new antiparkinsonism drugs. © 2007 Movement Disorder Society</p></abstract></abstractGroup></contentMeta></header></component></istex:document></istex:metadataXml><!--Version 0.6 générée le 4-12-2015--><mods version="3.6"><titleInfo lang="en"><title>Power‐law temporal autocorrelation of activity reflects severity of parkinsonism</title></titleInfo><titleInfo type="abbreviated" lang="en"><title>Quantitative Analysis of Parkinsonism</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Power‐law temporal autocorrelation of activity reflects severity of parkinsonism</title></titleInfo><name type="personal"><namePart type="given">Weidong</namePart><namePart type="family">Pan</namePart><namePart type="termsOfAddress">MD, PhD</namePart><affiliation>Department of Neurology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Kyoko</namePart><namePart type="family">Ohashi</namePart><namePart type="termsOfAddress">PhD</namePart><affiliation>Educational Physiology Laboratory, Graduate School of Education, The University of Tokyo, Tokyo, Japan</affiliation><affiliation>Developmental Biopsychiatry Research Program, McLean Hospital/Harvard Medical School, Belmont, Massachusetts, USA</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Yoshiharu</namePart><namePart type="family">Yamamoto</namePart><namePart type="termsOfAddress">PhD</namePart><affiliation>Educational Physiology Laboratory, Graduate School of Education, The University of Tokyo, Tokyo, Japan</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Shin</namePart><namePart type="family">Kwak</namePart><namePart type="termsOfAddress">MD, PhD</namePart><affiliation>Department of Neurology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan</affiliation><description>Correspondence: Department of Neurology, Graduate School of Medicine, The University of Tokyo, 7‐3‐1 Hongo, Bunkyo‐ku, Tokyo 113‐8655, Japan</description><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">2007-07-15</dateIssued><dateCaptured encoding="w3cdtf">2006-12-27</dateCaptured><dateValid encoding="w3cdtf">2007-03-19</dateValid><copyrightDate encoding="w3cdtf">2007</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">4</extent><extent unit="tables">1</extent><extent unit="references">21</extent><extent unit="words">3809</extent></physicalDescription><abstract lang="en">We aimed to obtain a reliable, objective scale representing disease severity for appropriate management of patients with Parkinson's disease (PD). Nineteen patients with PD at the Department of Neurology, Tokyo University Hospital, were classified into mild (n = 10) or severe groups (n = 9) depending on their Hoehn‐Yahr scores, and wore accelerometers on their wrists for more than 6 consecutive days. During this time we monitored their subjective assessments of symptom severity and analyzed the power‐law exponents (α) for local maxima and minima of fluctuations in the activity time series. Statistical comparisons were made between the severe and mild groups and of individual patients on “good condition” and “bad condition” days, as well as between days before and after antiparkinsonism medication. In all patients, the α for local maxima was always lower when parkinsonism was mild than when severe. Presence of tremor did not influence the α for local maxima. As the lower α value for local maxima of fluctuations in activity records reflects more frequent switching behavior from low to high physical activities or the severity of akinesia, actigraph monitoring of parkinsonism, and analysis of its power‐law correlation may provide useful objective information for controlling parkinsonism in outpatient clinics and for evaluating new antiparkinsonism drugs. © 2007 Movement Disorder Society</abstract><subject lang="en"><genre>Keywords</genre><topic>Parkinson's disease</topic><topic>actigraph</topic><topic>akinesia</topic><topic>fractal analysis</topic><topic>power‐law temporal autocorrelation</topic></subject><relatedItem type="host"><titleInfo><title>Movement Disorders</title><subTitle>Official Journal of the Movement Disorder Society</subTitle></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>2007</date><detail type="volume"><caption>vol.</caption><number>22</number></detail><detail type="issue"><caption>no.</caption><number>9</number></detail><extent unit="pages"><start>1308</start><end>1313</end><total>6</total></extent></part></relatedItem><identifier type="istex">CD9CDC7C52E2C692EFE7BE513FB2550CE6DD53C9</identifier><identifier type="DOI">10.1002/mds.21527</identifier><identifier type="ArticleID">MDS21527</identifier><accessCondition type="use and reproduction" contentType="copyright">Copyright © 2007 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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