A new coordination pattern classification to assess gait kinematics when utilising a modified vector coding technique
Abstract A modified vector coding (VC) technique was used to quantify lumbar–pelvic coordination during gait. The outcome measure from the modified VC technique is known as the coupling angle (CA) which can be classified into one of four coordination patterns. This study introduces a new classificat...
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Veröffentlicht in: | Journal of biomechanics 2015-09, Vol.48 (12), p.3506-3511 |
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description | Abstract A modified vector coding (VC) technique was used to quantify lumbar–pelvic coordination during gait. The outcome measure from the modified VC technique is known as the coupling angle (CA) which can be classified into one of four coordination patterns. This study introduces a new classification for this coordination pattern that expands on a current data analysis technique by introducing the terms in-phase with proximal dominancy, in-phase with distal dominancy, anti-phase with proximal dominancy and anti-phase with distal dominancy. This proposed coordination pattern classification can offer an interpretation of the CA that provides either in-phase or anti-phase coordination information, along with an understanding of the direction of segmental rotations and the segment that is the dominant mover at each point in time. Classifying the CA against the new defined coordination patterns and presenting this information in a traditional time-series format in this study has offered an insight into segmental range of motion. A new illustration is also presented which details the distribution of the CA within each of the coordination patterns and allows for the quantification of segmental dominancy. The proposed illustration technique can have important implications in demonstrating gait coordination data in an easily comprehensible fashion by clinicians and scientists alike. |
doi_str_mv | 10.1016/j.jbiomech.2015.07.023 |
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The outcome measure from the modified VC technique is known as the coupling angle (CA) which can be classified into one of four coordination patterns. This study introduces a new classification for this coordination pattern that expands on a current data analysis technique by introducing the terms in-phase with proximal dominancy, in-phase with distal dominancy, anti-phase with proximal dominancy and anti-phase with distal dominancy. This proposed coordination pattern classification can offer an interpretation of the CA that provides either in-phase or anti-phase coordination information, along with an understanding of the direction of segmental rotations and the segment that is the dominant mover at each point in time. Classifying the CA against the new defined coordination patterns and presenting this information in a traditional time-series format in this study has offered an insight into segmental range of motion. A new illustration is also presented which details the distribution of the CA within each of the coordination patterns and allows for the quantification of segmental dominancy. The proposed illustration technique can have important implications in demonstrating gait coordination data in an easily comprehensible fashion by clinicians and scientists alike.</description><identifier>ISSN: 0021-9290</identifier><identifier>EISSN: 1873-2380</identifier><identifier>DOI: 10.1016/j.jbiomech.2015.07.023</identifier><identifier>PMID: 26303167</identifier><language>eng</language><publisher>United States: Elsevier Ltd</publisher><subject>Biomechanical Phenomena ; Classification ; Coding ; Data analysis ; Data processing ; Dynamical systems approach ; Gait ; Gait - physiology ; Humans ; Illustrations ; Inter-segmental coordination pattern ; Lumbar–pelvic movement ; Lumbosacral Region ; Male ; Mathematical analysis ; Mechanical Phenomena ; Pattern Recognition, Automated - methods ; Pelvis - physiology ; Physical Medicine and Rehabilitation ; Range of Motion, Articular ; Segments ; Statistics as Topic - methods ; Studies ; Vector coding ; Vectors (mathematics) ; Walking ; Young Adult</subject><ispartof>Journal of biomechanics, 2015-09, Vol.48 (12), p.3506-3511</ispartof><rights>Elsevier Ltd</rights><rights>2015 Elsevier Ltd</rights><rights>Copyright © 2015 Elsevier Ltd. All rights reserved.</rights><rights>Copyright Elsevier Limited 2015</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c565t-ade2788e4dc6744fd2abed0228d361888cef337aa75617a132318241935d7efa3</citedby><cites>FETCH-LOGICAL-c565t-ade2788e4dc6744fd2abed0228d361888cef337aa75617a132318241935d7efa3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/1718120212?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995,64385,64387,64389,72469</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26303167$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Needham, Robert A</creatorcontrib><creatorcontrib>Naemi, Roozbeh</creatorcontrib><creatorcontrib>Chockalingam, Nachiappan</creatorcontrib><title>A new coordination pattern classification to assess gait kinematics when utilising a modified vector coding technique</title><title>Journal of biomechanics</title><addtitle>J Biomech</addtitle><description>Abstract A modified vector coding (VC) technique was used to quantify lumbar–pelvic coordination during gait. The outcome measure from the modified VC technique is known as the coupling angle (CA) which can be classified into one of four coordination patterns. This study introduces a new classification for this coordination pattern that expands on a current data analysis technique by introducing the terms in-phase with proximal dominancy, in-phase with distal dominancy, anti-phase with proximal dominancy and anti-phase with distal dominancy. This proposed coordination pattern classification can offer an interpretation of the CA that provides either in-phase or anti-phase coordination information, along with an understanding of the direction of segmental rotations and the segment that is the dominant mover at each point in time. Classifying the CA against the new defined coordination patterns and presenting this information in a traditional time-series format in this study has offered an insight into segmental range of motion. A new illustration is also presented which details the distribution of the CA within each of the coordination patterns and allows for the quantification of segmental dominancy. The proposed illustration technique can have important implications in demonstrating gait coordination data in an easily comprehensible fashion by clinicians and scientists alike.</description><subject>Biomechanical Phenomena</subject><subject>Classification</subject><subject>Coding</subject><subject>Data analysis</subject><subject>Data processing</subject><subject>Dynamical systems approach</subject><subject>Gait</subject><subject>Gait - physiology</subject><subject>Humans</subject><subject>Illustrations</subject><subject>Inter-segmental coordination pattern</subject><subject>Lumbar–pelvic movement</subject><subject>Lumbosacral Region</subject><subject>Male</subject><subject>Mathematical analysis</subject><subject>Mechanical Phenomena</subject><subject>Pattern Recognition, Automated - methods</subject><subject>Pelvis - physiology</subject><subject>Physical Medicine and Rehabilitation</subject><subject>Range of Motion, Articular</subject><subject>Segments</subject><subject>Statistics as Topic - methods</subject><subject>Studies</subject><subject>Vector coding</subject><subject>Vectors (mathematics)</subject><subject>Walking</subject><subject>Young Adult</subject><issn>0021-9290</issn><issn>1873-2380</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNqNkk1v1DAQhi0EokvhL1SWuHBJGNtJ7FwQVVU-pEocgLPltSett4m92Emr_nsctgWpl3Ky7HnmHc-8Q8gJg5oB697v6t3WxwntVc2BtTXIGrh4RjZMSVFxoeA52QBwVvW8hyPyKucdAMhG9i_JEe8ECNbJDVlOacBbamNMzgcz-xjo3swzpkDtaHL2g7eH5znScsec6aXxM732AacSsZneXmGgy-xHn324pIZO0ZU8dPQG7RxTkXdrYC7fDf7Xgq_Ji8GMGd_cn8fk56fzH2dfqotvn7-enV5Utu3auTIOuVQKG2c72TSD42aLDjhXTnRMKWVxEEIaI9uOScMEF0zxhvWidRIHI47Ju4PuPsVSNs968tniOJqAccmaKSFFA33XP41KqUC0omH_gTLVMwClCvr2EbqLSwql5z8U48UhXqjuQNkUc0446H3yk0l3moFe7dY7_WC3Xu3WIHWxuySe3Msv2wnd37QHfwvw8QBgmfKNx6Sz9RgsOp-KNdpF_3SND48k7OhDWYrxGu8w_-tHZ65Bf1-Xbt051gI0rEz2N4a907U</recordid><startdate>20150918</startdate><enddate>20150918</enddate><creator>Needham, Robert A</creator><creator>Naemi, Roozbeh</creator><creator>Chockalingam, Nachiappan</creator><general>Elsevier Ltd</general><general>Elsevier Limited</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QP</scope><scope>7TB</scope><scope>7TS</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2O</scope><scope>M7P</scope><scope>MBDVC</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope><scope>7QO</scope><scope>P64</scope></search><sort><creationdate>20150918</creationdate><title>A new coordination pattern classification to assess gait kinematics when utilising a modified vector coding technique</title><author>Needham, Robert A ; Naemi, Roozbeh ; Chockalingam, Nachiappan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c565t-ade2788e4dc6744fd2abed0228d361888cef337aa75617a132318241935d7efa3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Biomechanical Phenomena</topic><topic>Classification</topic><topic>Coding</topic><topic>Data analysis</topic><topic>Data processing</topic><topic>Dynamical systems approach</topic><topic>Gait</topic><topic>Gait - physiology</topic><topic>Humans</topic><topic>Illustrations</topic><topic>Inter-segmental coordination pattern</topic><topic>Lumbar–pelvic movement</topic><topic>Lumbosacral Region</topic><topic>Male</topic><topic>Mathematical analysis</topic><topic>Mechanical Phenomena</topic><topic>Pattern Recognition, Automated - methods</topic><topic>Pelvis - physiology</topic><topic>Physical Medicine and Rehabilitation</topic><topic>Range of Motion, Articular</topic><topic>Segments</topic><topic>Statistics as Topic - methods</topic><topic>Studies</topic><topic>Vector coding</topic><topic>Vectors (mathematics)</topic><topic>Walking</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Needham, Robert A</creatorcontrib><creatorcontrib>Naemi, Roozbeh</creatorcontrib><creatorcontrib>Chockalingam, Nachiappan</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Physical Education Index</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Research Library</collection><collection>Biological Science Database</collection><collection>Research Library (Corporate)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>Biotechnology Research Abstracts</collection><collection>Biotechnology and BioEngineering Abstracts</collection><jtitle>Journal of biomechanics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Needham, Robert A</au><au>Naemi, Roozbeh</au><au>Chockalingam, Nachiappan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A new coordination pattern classification to assess gait kinematics when utilising a modified vector coding technique</atitle><jtitle>Journal of biomechanics</jtitle><addtitle>J Biomech</addtitle><date>2015-09-18</date><risdate>2015</risdate><volume>48</volume><issue>12</issue><spage>3506</spage><epage>3511</epage><pages>3506-3511</pages><issn>0021-9290</issn><eissn>1873-2380</eissn><abstract>Abstract A modified vector coding (VC) technique was used to quantify lumbar–pelvic coordination during gait. The outcome measure from the modified VC technique is known as the coupling angle (CA) which can be classified into one of four coordination patterns. This study introduces a new classification for this coordination pattern that expands on a current data analysis technique by introducing the terms in-phase with proximal dominancy, in-phase with distal dominancy, anti-phase with proximal dominancy and anti-phase with distal dominancy. This proposed coordination pattern classification can offer an interpretation of the CA that provides either in-phase or anti-phase coordination information, along with an understanding of the direction of segmental rotations and the segment that is the dominant mover at each point in time. Classifying the CA against the new defined coordination patterns and presenting this information in a traditional time-series format in this study has offered an insight into segmental range of motion. A new illustration is also presented which details the distribution of the CA within each of the coordination patterns and allows for the quantification of segmental dominancy. The proposed illustration technique can have important implications in demonstrating gait coordination data in an easily comprehensible fashion by clinicians and scientists alike.</abstract><cop>United States</cop><pub>Elsevier Ltd</pub><pmid>26303167</pmid><doi>10.1016/j.jbiomech.2015.07.023</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Biomechanical Phenomena Classification Coding Data analysis Data processing Dynamical systems approach Gait Gait - physiology Humans Illustrations Inter-segmental coordination pattern Lumbar–pelvic movement Lumbosacral Region Male Mathematical analysis Mechanical Phenomena Pattern Recognition, Automated - methods Pelvis - physiology Physical Medicine and Rehabilitation Range of Motion, Articular Segments Statistics as Topic - methods Studies Vector coding Vectors (mathematics) Walking Young Adult |
title | A new coordination pattern classification to assess gait kinematics when utilising a modified vector coding technique |
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