Development of a Haptic Elbow Spasticity Simulator (HESS) for improving accuracy and reliability of clinical assessment of spasticity.
Identifieur interne : 000C01 ( PubMed/Corpus ); précédent : 000C00; suivant : 000C02Development of a Haptic Elbow Spasticity Simulator (HESS) for improving accuracy and reliability of clinical assessment of spasticity.
Auteurs : Hyung-Soon Park ; Jonghyun Kim ; Diane L. DamianoSource :
- IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society [ 1558-0210 ] ; 2012.
English descriptors
- KwdEn :
- Adolescent, Algorithms, Cerebral Palsy (complications), Child, Computer Simulation, Computer Systems, Data Collection, Elbow (physiology), Equipment Design, Friction, Humans, Manikins, Models, Anatomic, Models, Statistical, Muscle Spasticity (diagnosis), Muscle Spasticity (physiopathology), Observer Variation, Reproducibility of Results, Safety.
- MESH :
- complications : Cerebral Palsy.
- diagnosis : Muscle Spasticity.
- physiology : Elbow.
- physiopathology : Muscle Spasticity.
- Adolescent, Algorithms, Child, Computer Simulation, Computer Systems, Data Collection, Equipment Design, Friction, Humans, Manikins, Models, Anatomic, Models, Statistical, Observer Variation, Reproducibility of Results, Safety.
Abstract
This paper presents the framework for developing a robotic system to improve accuracy and reliability of clinical assessment. Clinical assessment of spasticity tends to have poor reliability because of the nature of the in-person assessment. To improve accuracy and reliability of spasticity assessment, a haptic device, named the HESS (Haptic Elbow Spasticity Simulator) has been designed and constructed to recreate the clinical "feel" of elbow spasticity based on quantitative measurements. A mathematical model representing the spastic elbow joint was proposed based on clinical assessment using the Modified Ashworth Scale (MAS) and quantitative data (position, velocity, and torque) collected on subjects with elbow spasticity. Four haptic models (HMs) were created to represent the haptic feel of MAS 1, 1+, 2, and 3. The four HMs were assessed by experienced clinicians; three clinicians performed both in-person and haptic assessments, and had 100% agreement in MAS scores; and eight clinicians who were experienced with MAS assessed the four HMs without receiving any training prior to the test. Inter-rater reliability among the eight clinicians had substantial agreement (κ = 0.626). The eight clinicians also rated the level of realism ( 7.63 ± 0.92 out of 10) as compared to their experience with real patients.
DOI: 10.1109/TNSRE.2012.2195330
PubMed: 22562769
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pubmed:22562769Le document en format XML
<record><TEI><teiHeader><fileDesc><titleStmt><title xml:lang="en">Development of a Haptic Elbow Spasticity Simulator (HESS) for improving accuracy and reliability of clinical assessment of spasticity.</title><author><name sortKey="Park, Hyung Soon" sort="Park, Hyung Soon" uniqKey="Park H" first="Hyung-Soon" last="Park">Hyung-Soon Park</name><affiliation><nlm:affiliation>National Institutes of Health, Clinical Center, Rehabilitation Medicine Department, Bethesda, MD 20892, USA. parkhs@cc.nih.gov</nlm:affiliation></affiliation></author><author><name sortKey="Kim, Jonghyun" sort="Kim, Jonghyun" uniqKey="Kim J" first="Jonghyun" last="Kim">Jonghyun Kim</name></author><author><name sortKey="Damiano, Diane L" sort="Damiano, Diane L" uniqKey="Damiano D" first="Diane L" last="Damiano">Diane L. Damiano</name></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2012">2012</date><idno type="doi">10.1109/TNSRE.2012.2195330</idno><idno type="RBID">pubmed:22562769</idno><idno type="pmid">22562769</idno><idno type="wicri:Area/PubMed/Corpus">000C01</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Development of a Haptic Elbow Spasticity Simulator (HESS) for improving accuracy and reliability of clinical assessment of spasticity.</title><author><name sortKey="Park, Hyung Soon" sort="Park, Hyung Soon" uniqKey="Park H" first="Hyung-Soon" last="Park">Hyung-Soon Park</name><affiliation><nlm:affiliation>National Institutes of Health, Clinical Center, Rehabilitation Medicine Department, Bethesda, MD 20892, USA. parkhs@cc.nih.gov</nlm:affiliation></affiliation></author><author><name sortKey="Kim, Jonghyun" sort="Kim, Jonghyun" uniqKey="Kim J" first="Jonghyun" last="Kim">Jonghyun Kim</name></author><author><name sortKey="Damiano, Diane L" sort="Damiano, Diane L" uniqKey="Damiano D" first="Diane L" last="Damiano">Diane L. Damiano</name></author></analytic><series><title level="j">IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society</title><idno type="eISSN">1558-0210</idno><imprint><date when="2012" type="published">2012</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Adolescent</term><term>Algorithms</term><term>Cerebral Palsy (complications)</term><term>Child</term><term>Computer Simulation</term><term>Computer Systems</term><term>Data Collection</term><term>Elbow (physiology)</term><term>Equipment Design</term><term>Friction</term><term>Humans</term><term>Manikins</term><term>Models, Anatomic</term><term>Models, Statistical</term><term>Muscle Spasticity (diagnosis)</term><term>Muscle Spasticity (physiopathology)</term><term>Observer Variation</term><term>Reproducibility of Results</term><term>Safety</term></keywords><keywords scheme="MESH" qualifier="complications" xml:lang="en"><term>Cerebral Palsy</term></keywords><keywords scheme="MESH" qualifier="diagnosis" xml:lang="en"><term>Muscle Spasticity</term></keywords><keywords scheme="MESH" qualifier="physiology" xml:lang="en"><term>Elbow</term></keywords><keywords scheme="MESH" qualifier="physiopathology" xml:lang="en"><term>Muscle Spasticity</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Adolescent</term><term>Algorithms</term><term>Child</term><term>Computer Simulation</term><term>Computer Systems</term><term>Data Collection</term><term>Equipment Design</term><term>Friction</term><term>Humans</term><term>Manikins</term><term>Models, Anatomic</term><term>Models, Statistical</term><term>Observer Variation</term><term>Reproducibility of Results</term><term>Safety</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">This paper presents the framework for developing a robotic system to improve accuracy and reliability of clinical assessment. Clinical assessment of spasticity tends to have poor reliability because of the nature of the in-person assessment. To improve accuracy and reliability of spasticity assessment, a haptic device, named the HESS (Haptic Elbow Spasticity Simulator) has been designed and constructed to recreate the clinical "feel" of elbow spasticity based on quantitative measurements. A mathematical model representing the spastic elbow joint was proposed based on clinical assessment using the Modified Ashworth Scale (MAS) and quantitative data (position, velocity, and torque) collected on subjects with elbow spasticity. Four haptic models (HMs) were created to represent the haptic feel of MAS 1, 1+, 2, and 3. The four HMs were assessed by experienced clinicians; three clinicians performed both in-person and haptic assessments, and had 100% agreement in MAS scores; and eight clinicians who were experienced with MAS assessed the four HMs without receiving any training prior to the test. Inter-rater reliability among the eight clinicians had substantial agreement (κ = 0.626). The eight clinicians also rated the level of realism ( 7.63 ± 0.92 out of 10) as compared to their experience with real patients.</div></front></TEI><pubmed><MedlineCitation Owner="NLM" Status="MEDLINE"><PMID Version="1">22562769</PMID><DateCreated><Year>2012</Year><Month>05</Month><Day>24</Day></DateCreated><DateCompleted><Year>2012</Year><Month>09</Month><Day>24</Day></DateCompleted><DateRevised><Year>2015</Year><Month>03</Month><Day>25</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1558-0210</ISSN><JournalIssue CitedMedium="Internet"><Volume>20</Volume><Issue>3</Issue><PubDate><Year>2012</Year><Month>May</Month></PubDate></JournalIssue><Title>IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society</Title><ISOAbbreviation>IEEE Trans Neural Syst Rehabil Eng</ISOAbbreviation></Journal><ArticleTitle>Development of a Haptic Elbow Spasticity Simulator (HESS) for improving accuracy and reliability of clinical assessment of spasticity.</ArticleTitle><Pagination><MedlinePgn>361-70</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1109/TNSRE.2012.2195330</ELocationID><Abstract><AbstractText>This paper presents the framework for developing a robotic system to improve accuracy and reliability of clinical assessment. Clinical assessment of spasticity tends to have poor reliability because of the nature of the in-person assessment. To improve accuracy and reliability of spasticity assessment, a haptic device, named the HESS (Haptic Elbow Spasticity Simulator) has been designed and constructed to recreate the clinical "feel" of elbow spasticity based on quantitative measurements. A mathematical model representing the spastic elbow joint was proposed based on clinical assessment using the Modified Ashworth Scale (MAS) and quantitative data (position, velocity, and torque) collected on subjects with elbow spasticity. Four haptic models (HMs) were created to represent the haptic feel of MAS 1, 1+, 2, and 3. The four HMs were assessed by experienced clinicians; three clinicians performed both in-person and haptic assessments, and had 100% agreement in MAS scores; and eight clinicians who were experienced with MAS assessed the four HMs without receiving any training prior to the test. Inter-rater reliability among the eight clinicians had substantial agreement (κ = 0.626). The eight clinicians also rated the level of realism ( 7.63 ± 0.92 out of 10) as compared to their experience with real patients.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Park</LastName><ForeName>Hyung-Soon</ForeName><Initials>HS</Initials><AffiliationInfo><Affiliation>National Institutes of Health, Clinical Center, Rehabilitation Medicine Department, Bethesda, MD 20892, USA. parkhs@cc.nih.gov</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Kim</LastName><ForeName>Jonghyun</ForeName><Initials>J</Initials></Author><Author ValidYN="Y"><LastName>Damiano</LastName><ForeName>Diane L</ForeName><Initials>DL</Initials></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>Z99 CL999999</GrantID><Agency>Intramural NIH HHS</Agency><Country>United States</Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D052060">Research Support, N.I.H., Intramural</PublicationType><PublicationType UI="D013486">Research Support, U.S. Gov't, Non-P.H.S.</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2012</Year><Month>05</Month><Day>02</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>IEEE Trans Neural Syst Rehabil Eng</MedlineTA><NlmUniqueID>101097023</NlmUniqueID><ISSNLinking>1534-4320</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><CommentsCorrectionsList><CommentsCorrections RefType="Cites"><RefSource>Spinal Cord. 2010 Mar;48(3):207-13</RefSource><PMID Version="1">19786977</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>IEEE Int Conf Rehabil Robot. 2011;2011:5975510</RefSource><PMID Version="1">22275706</PMID></CommentsCorrections><CommentsCorrections RefType="Cites"><RefSource>Ann Biomed Eng. 2001 Apr;29(4):330-9</RefSource><PMID 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Variation</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D015203">Reproducibility of Results</DescriptorName></MeshHeading><MeshHeading><DescriptorName MajorTopicYN="N" UI="D012449">Safety</DescriptorName></MeshHeading></MeshHeadingList><OtherID Source="NLM">NIHMS442699</OtherID><OtherID Source="NLM">PMC3579668</OtherID></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="aheadofprint"><Year>2012</Year><Month>5</Month><Day>02</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2012</Year><Month>5</Month><Day>8</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2012</Year><Month>5</Month><Day>9</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2012</Year><Month>9</Month><Day>25</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId 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