Characterization and quantification of freezing of gait in Parkinson's disease: Can detection algorithms replace clinical expert opinion?
Identifieur interne : 000268 ( PubMed/Corpus ); précédent : 000267; suivant : 000269Characterization and quantification of freezing of gait in Parkinson's disease: Can detection algorithms replace clinical expert opinion?
Auteurs : A. Delval ; C. Tard ; M. Rambour ; L. Defebvre ; C. MoreauSource :
- Neurophysiologie clinique = Clinical neurophysiology [ 1769-7131 ] ; 2015.
English descriptors
- KwdEn :
- Algorithms, Biomechanical Phenomena, Brain Mapping, Gait Disorders, Neurologic (diagnosis), Gait Disorders, Neurologic (etiology), Humans, Magnetic Resonance Imaging, Parkinson Disease (complications), Physical Examination, Positron-Emission Tomography, Sensitivity and Specificity, Signal Processing, Computer-Assisted.
- MESH :
- complications : Parkinson Disease.
- diagnosis : Gait Disorders, Neurologic.
- etiology : Gait Disorders, Neurologic.
- Algorithms, Biomechanical Phenomena, Brain Mapping, Humans, Magnetic Resonance Imaging, Physical Examination, Positron-Emission Tomography, Sensitivity and Specificity, Signal Processing, Computer-Assisted.
Abstract
Freezing of gait is a paroxysmal phenomenon that is frequently reported by the parkinsonian patients or their entourage. The phenomenon significantly alters quality of life but is often difficult to characterize in the physician's office. In the present review, we focus on the clinical characterization and quantification of freezing of gait. Various biomechanical methods (based mainly on time-frequency analysis) can be used to determine time-domain characteristics of freezing of gait. Methods already used to study non-gait freezing of other effectors (the lower limbs, upper limbs and orofacial area) are also being developed for the analysis of freezing in functional magnetic resonance imaging protocols. Here, we review the reliability of these methods and compare them with reliability of information obtained from physical examination and detailed analysis of the patient's medical history.
DOI: 10.1016/j.neucli.2015.09.009
PubMed: 26547546
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pubmed:26547546Le document en format XML
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Tard</name><affiliation><nlm:affiliation>U1171, Université de Lille, Lille, France; Clinical Neurophysiology Department, Lille University Medical Center, Lille, France; Neurology and Movement Disorders Department, Lille University Medical Center, Lille, France.</nlm:affiliation></affiliation></author><author><name sortKey="Rambour, M" sort="Rambour, M" uniqKey="Rambour M" first="M" last="Rambour">M. Rambour</name><affiliation><nlm:affiliation>U1171, Université de Lille, Lille, France; Neurology and Movement Disorders Department, Lille University Medical Center, Lille, France.</nlm:affiliation></affiliation></author><author><name sortKey="Defebvre, L" sort="Defebvre, L" uniqKey="Defebvre L" first="L" last="Defebvre">L. Defebvre</name><affiliation><nlm:affiliation>U1171, Université de Lille, Lille, France; Neurology and Movement Disorders Department, Lille University Medical Center, Lille, France.</nlm:affiliation></affiliation></author><author><name sortKey="Moreau, C" sort="Moreau, C" uniqKey="Moreau C" first="C" last="Moreau">C. Moreau</name><affiliation><nlm:affiliation>U1171, Université de Lille, Lille, France; Neurology and Movement Disorders Department, Lille University Medical Center, Lille, France.</nlm:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2015">2015</date><idno type="RBID">pubmed:26547546</idno><idno type="pmid">26547546</idno><idno type="doi">10.1016/j.neucli.2015.09.009</idno><idno type="wicri:Area/PubMed/Corpus">000268</idno><idno type="wicri:explorRef" wicri:stream="PubMed" wicri:step="Corpus" wicri:corpus="PubMed">000268</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Characterization and quantification of freezing of gait in Parkinson's disease: Can detection algorithms replace clinical expert opinion?</title><author><name sortKey="Delval, A" sort="Delval, A" uniqKey="Delval A" first="A" last="Delval">A. Delval</name><affiliation><nlm:affiliation>U1171, Université de Lille, Lille, France; Clinical Neurophysiology Department, Lille University Medical Center, Lille, France. Electronic address: arnaud.delval@chru-lille.fr.</nlm:affiliation></affiliation></author><author><name sortKey="Tard, C" sort="Tard, C" uniqKey="Tard C" first="C" last="Tard">C. Tard</name><affiliation><nlm:affiliation>U1171, Université de Lille, Lille, France; Clinical Neurophysiology Department, Lille University Medical Center, Lille, France; Neurology and Movement Disorders Department, Lille University Medical Center, Lille, France.</nlm:affiliation></affiliation></author><author><name sortKey="Rambour, M" sort="Rambour, M" uniqKey="Rambour M" first="M" last="Rambour">M. Rambour</name><affiliation><nlm:affiliation>U1171, Université de Lille, Lille, France; Neurology and Movement Disorders Department, Lille University Medical Center, Lille, France.</nlm:affiliation></affiliation></author><author><name sortKey="Defebvre, L" sort="Defebvre, L" uniqKey="Defebvre L" first="L" last="Defebvre">L. Defebvre</name><affiliation><nlm:affiliation>U1171, Université de Lille, Lille, France; Neurology and Movement Disorders Department, Lille University Medical Center, Lille, France.</nlm:affiliation></affiliation></author><author><name sortKey="Moreau, C" sort="Moreau, C" uniqKey="Moreau C" first="C" last="Moreau">C. Moreau</name><affiliation><nlm:affiliation>U1171, Université de Lille, Lille, France; Neurology and Movement Disorders Department, Lille University Medical Center, Lille, France.</nlm:affiliation></affiliation></author></analytic><series><title level="j">Neurophysiologie clinique = Clinical neurophysiology</title><idno type="eISSN">1769-7131</idno><imprint><date when="2015" type="published">2015</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Algorithms</term><term>Biomechanical Phenomena</term><term>Brain Mapping</term><term>Gait Disorders, Neurologic (diagnosis)</term><term>Gait Disorders, Neurologic (etiology)</term><term>Humans</term><term>Magnetic Resonance Imaging</term><term>Parkinson Disease (complications)</term><term>Physical Examination</term><term>Positron-Emission Tomography</term><term>Sensitivity and Specificity</term><term>Signal Processing, Computer-Assisted</term></keywords><keywords scheme="MESH" qualifier="complications" xml:lang="en"><term>Parkinson Disease</term></keywords><keywords scheme="MESH" qualifier="diagnosis" xml:lang="en"><term>Gait Disorders, Neurologic</term></keywords><keywords scheme="MESH" qualifier="etiology" xml:lang="en"><term>Gait Disorders, Neurologic</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Algorithms</term><term>Biomechanical Phenomena</term><term>Brain Mapping</term><term>Humans</term><term>Magnetic Resonance Imaging</term><term>Physical Examination</term><term>Positron-Emission Tomography</term><term>Sensitivity and Specificity</term><term>Signal Processing, Computer-Assisted</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Freezing of gait is a paroxysmal phenomenon that is frequently reported by the parkinsonian patients or their entourage. The phenomenon significantly alters quality of life but is often difficult to characterize in the physician's office. In the present review, we focus on the clinical characterization and quantification of freezing of gait. Various biomechanical methods (based mainly on time-frequency analysis) can be used to determine time-domain characteristics of freezing of gait. Methods already used to study non-gait freezing of other effectors (the lower limbs, upper limbs and orofacial area) are also being developed for the analysis of freezing in functional magnetic resonance imaging protocols. Here, we review the reliability of these methods and compare them with reliability of information obtained from physical examination and detailed analysis of the patient's medical history.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">26547546</PMID><DateCreated><Year>2015</Year><Month>11</Month><Day>30</Day></DateCreated><DateCompleted><Year>2016</Year><Month>09</Month><Day>14</Day></DateCompleted><DateRevised><Year>2015</Year><Month>11</Month><Day>30</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1769-7131</ISSN><JournalIssue CitedMedium="Internet"><Volume>45</Volume><Issue>4-5</Issue><PubDate><Year>2015</Year><Month>Nov</Month></PubDate></JournalIssue><Title>Neurophysiologie clinique = Clinical neurophysiology</Title><ISOAbbreviation>Neurophysiol Clin</ISOAbbreviation></Journal><ArticleTitle>Characterization and quantification of freezing of gait in Parkinson's disease: Can detection algorithms replace clinical expert opinion?</ArticleTitle><Pagination><MedlinePgn>305-13</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.neucli.2015.09.009</ELocationID><ELocationID EIdType="pii" ValidYN="Y">S0987-7053(15)00149-5</ELocationID><Abstract><AbstractText>Freezing of gait is a paroxysmal phenomenon that is frequently reported by the parkinsonian patients or their entourage. The phenomenon significantly alters quality of life but is often difficult to characterize in the physician's office. In the present review, we focus on the clinical characterization and quantification of freezing of gait. Various biomechanical methods (based mainly on time-frequency analysis) can be used to determine time-domain characteristics of freezing of gait. Methods already used to study non-gait freezing of other effectors (the lower limbs, upper limbs and orofacial area) are also being developed for the analysis of freezing in functional magnetic resonance imaging protocols. Here, we review the reliability of these methods and compare them with reliability of information obtained from physical examination and detailed analysis of the patient's medical history.</AbstractText><CopyrightInformation>Copyright © 2015 Elsevier Masson SAS. All rights reserved.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Delval</LastName><ForeName>A</ForeName><Initials>A</Initials><AffiliationInfo><Affiliation>U1171, Université de Lille, Lille, France; Clinical Neurophysiology Department, Lille University Medical Center, Lille, France. 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