Correlations between Statistical Models of Robotically Collected Kinematics and Clinical Measures of Upper Extremity Function*
Identifieur interne : 002529 ( Main/Merge ); précédent : 002528; suivant : 002530Correlations between Statistical Models of Robotically Collected Kinematics and Clinical Measures of Upper Extremity Function*
Auteurs : Maryam Rohafza ; Gerard G. Fluet ; Qinyin Qiu ; Sergei AdamovichSource :
- Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference [ 1557-170X ] ; 2012.
English descriptors
- KwdEn :
- Computer Simulation, Diagnosis, Computer-Assisted (methods), Female, Humans, Male, Middle Aged, Models, Biological, Models, Statistical, Movement, Paresis (diagnosis), Paresis (etiology), Paresis (physiopathology), Reproducibility of Results, Robotics (methods), Sensitivity and Specificity, Statistics as Topic, Stroke (complications), Stroke (diagnosis), Stroke (physiopathology), Upper Extremity (physiopathology).
- MESH :
- complications : Stroke.
- diagnosis : Paresis, Stroke.
- etiology : Paresis.
- methods : Diagnosis, Computer-Assisted, Robotics.
- physiopathology : Paresis, Stroke, Upper Extremity.
- Computer Simulation, Female, Humans, Male, Middle Aged, Models, Biological, Models, Statistical, Movement, Reproducibility of Results, Sensitivity and Specificity, Statistics as Topic.
Abstract
One of the obstacles in the development of rehabilitation robotics has been inadequacy in the measurement of treatment effects due to interventions. A measurement tool that will efficiently produce a large reliable sample of measurements collected during a single session that can also produce a rich set of data which reflects a subject’s ability to perform meaningful functional activities has not been developed. This paper presents three linear regression models generated from seven kinematic measures collected during the performance of virtually simulated rehabilitation activities that were integrated with haptic robots by 19 persons with upper extremity hemiparesis due to chronic stroke. One of these models demonstrated a statistically significant correlation with the subjects’ scores on the Jebsen Test of Hand Function (JTHF), a battery of six standardized upper extremity functional activities. The second and third models demonstrated a statistically significant correlation with the subjects’ change scores on the JTHF.
Url:
DOI: 10.1109/EMBC.2012.6346873
PubMed: 23366834
PubMed Central: 4552313
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PMC:4552313Le document en format XML
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Fluet</name></author><author><name sortKey="Qiu, Qinyin" sort="Qiu, Qinyin" uniqKey="Qiu Q" first="Qinyin" last="Qiu">Qinyin Qiu</name></author><author><name sortKey="Adamovich, Sergei" sort="Adamovich, Sergei" uniqKey="Adamovich S" first="Sergei" last="Adamovich">Sergei Adamovich</name></author></titleStmt><publicationStmt><idno type="wicri:source">PMC</idno><idno type="pmid">23366834</idno><idno type="pmc">4552313</idno><idno type="url">http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4552313</idno><idno type="RBID">PMC:4552313</idno><idno type="doi">10.1109/EMBC.2012.6346873</idno><date when="2012">2012</date><idno type="wicri:Area/Pmc/Corpus">001760</idno><idno type="wicri:Area/Pmc/Curation">001760</idno><idno type="wicri:Area/Pmc/Checkpoint">001802</idno><idno type="wicri:source">PubMed</idno><idno type="wicri:Area/PubMed/Corpus">000A38</idno><idno type="wicri:Area/PubMed/Curation">000A38</idno><idno type="wicri:Area/PubMed/Checkpoint">000B73</idno><idno type="wicri:Area/Ncbi/Merge">002476</idno><idno type="wicri:Area/Ncbi/Curation">002476</idno><idno type="wicri:Area/Ncbi/Checkpoint">002476</idno><idno type="wicri:doubleKey">1557-170X:2012:Rohafza M:correlations:between:statistical</idno><idno type="wicri:Area/Main/Merge">002529</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a" type="main">Correlations between Statistical Models of Robotically Collected Kinematics and Clinical Measures of Upper Extremity Function<xref ref-type="fn" rid="FN1">*</xref></title><author><name sortKey="Rohafza, Maryam" sort="Rohafza, Maryam" uniqKey="Rohafza M" first="Maryam" last="Rohafza">Maryam Rohafza</name></author><author><name sortKey="Fluet, Gerard G" sort="Fluet, Gerard G" uniqKey="Fluet G" first="Gerard G." last="Fluet">Gerard G. 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Annual Conference</title><idno type="ISSN">1557-170X</idno><imprint><date when="2012">2012</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Computer Simulation</term><term>Diagnosis, Computer-Assisted (methods)</term><term>Female</term><term>Humans</term><term>Male</term><term>Middle Aged</term><term>Models, Biological</term><term>Models, Statistical</term><term>Movement</term><term>Paresis (diagnosis)</term><term>Paresis (etiology)</term><term>Paresis (physiopathology)</term><term>Reproducibility of Results</term><term>Robotics (methods)</term><term>Sensitivity and Specificity</term><term>Statistics as Topic</term><term>Stroke (complications)</term><term>Stroke (diagnosis)</term><term>Stroke (physiopathology)</term><term>Upper Extremity (physiopathology)</term></keywords><keywords scheme="MESH" qualifier="complications" xml:lang="en"><term>Stroke</term></keywords><keywords scheme="MESH" qualifier="diagnosis" xml:lang="en"><term>Paresis</term><term>Stroke</term></keywords><keywords scheme="MESH" qualifier="etiology" xml:lang="en"><term>Paresis</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Diagnosis, Computer-Assisted</term><term>Robotics</term></keywords><keywords scheme="MESH" qualifier="physiopathology" xml:lang="en"><term>Paresis</term><term>Stroke</term><term>Upper Extremity</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Computer Simulation</term><term>Female</term><term>Humans</term><term>Male</term><term>Middle Aged</term><term>Models, Biological</term><term>Models, Statistical</term><term>Movement</term><term>Reproducibility of Results</term><term>Sensitivity and Specificity</term><term>Statistics as Topic</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en"><p id="P1">One of the obstacles in the development of rehabilitation robotics has been inadequacy in the measurement of treatment effects due to interventions. A measurement tool that will efficiently produce a large reliable sample of measurements collected during a single session that can also produce a rich set of data which reflects a subject’s ability to perform meaningful functional activities has not been developed. This paper presents three linear regression models generated from seven kinematic measures collected during the performance of virtually simulated rehabilitation activities that were integrated with haptic robots by 19 persons with upper extremity hemiparesis due to chronic stroke. One of these models demonstrated a statistically significant correlation with the subjects’ scores on the Jebsen Test of Hand Function (JTHF), a battery of six standardized upper extremity functional activities. The second and third models demonstrated a statistically significant correlation with the subjects’ change scores on the JTHF.</p></div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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