Modified electromyography-assisted optimization approach for predicting lumbar spine loading while walking with backpack loads
This study modified an electromyography-assisted optimization approach for predicting lumbar spine loading while walking with backpack loads. The modified-electromyography-assisted optimization approach eliminated the electromyography measurement at maximal voluntary contraction and adopted a linear...
Gespeichert in:
| Veröffentlicht in: | Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine Journal of engineering in medicine, 2020-05, Vol.234 (5), p.527-533 |
|---|---|
| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 533 |
|---|---|
| container_issue | 5 |
| container_start_page | 527 |
| container_title | Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine |
| container_volume | 234 |
| creator | Li, Simon SW Chow, Daniel HK |
| description | This study modified an electromyography-assisted optimization approach for predicting lumbar spine loading while walking with backpack loads. The modified-electromyography-assisted optimization approach eliminated the electromyography measurement at maximal voluntary contraction and adopted a linear electromyography–force relationship. Moreover, an optimal lower boundary condition for muscle gain was introduced to constrain the trunk muscle co-activation. Anthropometric information of 10 healthy young men as well as their kinematic, kinetic, and electromyography data obtained while walking with backpack loads were used as inputs in this study. A computational algorithm was used to find and analyse the sensitivity of the optimal lower boundary condition for achieving minimum deviation of the modified-electromyography-assisted optimization approach from the electromyography-assisted optimization approach for predicting lumbosacral joint compression force. Results validated that the modified-electromyography-assisted optimization approach (at optimal lower boundary condition of 0.92) predicted on average, a non-significant deviation in peak lumbosacral joint compression force of −18 N, a standard error of 9 N, and a root mean square difference in force profile of 73.8 N. The modified-electromyography-assisted optimization approach simplified the experimental process by eliminating the electromyography measurement at maximal voluntary contraction and provided comparable estimations for lumbosacral joint compression force that is also applicable to patients or individuals having difficulty in performing the maximal voluntary contraction activity. |
| doi_str_mv | 10.1177/0954411920906243 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2354737015</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sage_id>10.1177_0954411920906243</sage_id><sourcerecordid>2354737015</sourcerecordid><originalsourceid>FETCH-LOGICAL-c413t-7755b1dbb24d57b1b2feebd7fdab0c91a51e3f64c0961251f202461df868e7673</originalsourceid><addsrcrecordid>eNp1kctr3DAQxkVpSbZJ7j0VQS-9uJ3Rw4qPIeRRSOmlPRs9d5XYliPZhM2hf3u92aSFQA-DGH2_-WbgI-QDwhdEpb5CI4VAbBg0UDPB35AVA4EVB87fktVOrnb6IXlfyi0AIEJ9QA45A8lByBX5_T25GKJ31HfeTjn127TOetxsK11KLNOipHGKfXzUU0wD1eOYk7YbGlKmY_Yu2ikOa9rNvdGZljEOnnZJu93nwyZ2nj7o7u6pi9OGGm3vxqWemHJM3gXdFX_y_B6RX5cXP8-vq5sfV9_Oz24qK5BPlVJSGnTGMOGkMmhY8N44FZw2YBvUEj0PtbDQ1MgkBgZM1OjCaX3qVa34Efm8912Ov599mdo-Fuu7Tg8-zaVlXArFFaBc0E-v0Ns052G5rmUCUPEaBCwU7CmbUynZh3bMsdd52yK0u2za19ksIx-fjWfTe_d34CWMBaj2QNFr_2_rfw3_AHzvmDg</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2401736040</pqid></control><display><type>article</type><title>Modified electromyography-assisted optimization approach for predicting lumbar spine loading while walking with backpack loads</title><source>SAGE Complete A-Z List</source><source>MEDLINE</source><creator>Li, Simon SW ; Chow, Daniel HK</creator><creatorcontrib>Li, Simon SW ; Chow, Daniel HK</creatorcontrib><description>This study modified an electromyography-assisted optimization approach for predicting lumbar spine loading while walking with backpack loads. The modified-electromyography-assisted optimization approach eliminated the electromyography measurement at maximal voluntary contraction and adopted a linear electromyography–force relationship. Moreover, an optimal lower boundary condition for muscle gain was introduced to constrain the trunk muscle co-activation. Anthropometric information of 10 healthy young men as well as their kinematic, kinetic, and electromyography data obtained while walking with backpack loads were used as inputs in this study. A computational algorithm was used to find and analyse the sensitivity of the optimal lower boundary condition for achieving minimum deviation of the modified-electromyography-assisted optimization approach from the electromyography-assisted optimization approach for predicting lumbosacral joint compression force. Results validated that the modified-electromyography-assisted optimization approach (at optimal lower boundary condition of 0.92) predicted on average, a non-significant deviation in peak lumbosacral joint compression force of −18 N, a standard error of 9 N, and a root mean square difference in force profile of 73.8 N. The modified-electromyography-assisted optimization approach simplified the experimental process by eliminating the electromyography measurement at maximal voluntary contraction and provided comparable estimations for lumbosacral joint compression force that is also applicable to patients or individuals having difficulty in performing the maximal voluntary contraction activity.</description><identifier>ISSN: 0954-4119</identifier><identifier>EISSN: 2041-3033</identifier><identifier>DOI: 10.1177/0954411920906243</identifier><identifier>PMID: 32053045</identifier><language>eng</language><publisher>London, England: SAGE Publications</publisher><subject>Algorithms ; Anthropometry ; Biomechanical Phenomena ; Boundary conditions ; Compression ; Computer applications ; Contraction ; Deviation ; Electromyography ; Humans ; Joints (anatomy) ; Loads (forces) ; Lumbar Vertebrae - physiology ; Male ; Optimization ; Spine ; Spine (lumbar) ; Standard error ; Trunk muscles ; Walking - physiology ; Weight-Bearing ; Young Adult</subject><ispartof>Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine, 2020-05, Vol.234 (5), p.527-533</ispartof><rights>IMechE 2020</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c413t-7755b1dbb24d57b1b2feebd7fdab0c91a51e3f64c0961251f202461df868e7673</citedby><cites>FETCH-LOGICAL-c413t-7755b1dbb24d57b1b2feebd7fdab0c91a51e3f64c0961251f202461df868e7673</cites><orcidid>0000-0001-9333-4920</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://journals.sagepub.com/doi/pdf/10.1177/0954411920906243$$EPDF$$P50$$Gsage$$H</linktopdf><linktohtml>$$Uhttps://journals.sagepub.com/doi/10.1177/0954411920906243$$EHTML$$P50$$Gsage$$H</linktohtml><link.rule.ids>314,776,780,21798,27901,27902,43597,43598</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32053045$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Li, Simon SW</creatorcontrib><creatorcontrib>Chow, Daniel HK</creatorcontrib><title>Modified electromyography-assisted optimization approach for predicting lumbar spine loading while walking with backpack loads</title><title>Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine</title><addtitle>Proc Inst Mech Eng H</addtitle><description>This study modified an electromyography-assisted optimization approach for predicting lumbar spine loading while walking with backpack loads. The modified-electromyography-assisted optimization approach eliminated the electromyography measurement at maximal voluntary contraction and adopted a linear electromyography–force relationship. Moreover, an optimal lower boundary condition for muscle gain was introduced to constrain the trunk muscle co-activation. Anthropometric information of 10 healthy young men as well as their kinematic, kinetic, and electromyography data obtained while walking with backpack loads were used as inputs in this study. A computational algorithm was used to find and analyse the sensitivity of the optimal lower boundary condition for achieving minimum deviation of the modified-electromyography-assisted optimization approach from the electromyography-assisted optimization approach for predicting lumbosacral joint compression force. Results validated that the modified-electromyography-assisted optimization approach (at optimal lower boundary condition of 0.92) predicted on average, a non-significant deviation in peak lumbosacral joint compression force of −18 N, a standard error of 9 N, and a root mean square difference in force profile of 73.8 N. The modified-electromyography-assisted optimization approach simplified the experimental process by eliminating the electromyography measurement at maximal voluntary contraction and provided comparable estimations for lumbosacral joint compression force that is also applicable to patients or individuals having difficulty in performing the maximal voluntary contraction activity.</description><subject>Algorithms</subject><subject>Anthropometry</subject><subject>Biomechanical Phenomena</subject><subject>Boundary conditions</subject><subject>Compression</subject><subject>Computer applications</subject><subject>Contraction</subject><subject>Deviation</subject><subject>Electromyography</subject><subject>Humans</subject><subject>Joints (anatomy)</subject><subject>Loads (forces)</subject><subject>Lumbar Vertebrae - physiology</subject><subject>Male</subject><subject>Optimization</subject><subject>Spine</subject><subject>Spine (lumbar)</subject><subject>Standard error</subject><subject>Trunk muscles</subject><subject>Walking - physiology</subject><subject>Weight-Bearing</subject><subject>Young Adult</subject><issn>0954-4119</issn><issn>2041-3033</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp1kctr3DAQxkVpSbZJ7j0VQS-9uJ3Rw4qPIeRRSOmlPRs9d5XYliPZhM2hf3u92aSFQA-DGH2_-WbgI-QDwhdEpb5CI4VAbBg0UDPB35AVA4EVB87fktVOrnb6IXlfyi0AIEJ9QA45A8lByBX5_T25GKJ31HfeTjn127TOetxsK11KLNOipHGKfXzUU0wD1eOYk7YbGlKmY_Yu2ikOa9rNvdGZljEOnnZJu93nwyZ2nj7o7u6pi9OGGm3vxqWemHJM3gXdFX_y_B6RX5cXP8-vq5sfV9_Oz24qK5BPlVJSGnTGMOGkMmhY8N44FZw2YBvUEj0PtbDQ1MgkBgZM1OjCaX3qVa34Efm8912Ov599mdo-Fuu7Tg8-zaVlXArFFaBc0E-v0Ns052G5rmUCUPEaBCwU7CmbUynZh3bMsdd52yK0u2za19ksIx-fjWfTe_d34CWMBaj2QNFr_2_rfw3_AHzvmDg</recordid><startdate>20200501</startdate><enddate>20200501</enddate><creator>Li, Simon SW</creator><creator>Chow, Daniel HK</creator><general>SAGE Publications</general><general>SAGE PUBLICATIONS, INC</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>7QF</scope><scope>7QO</scope><scope>7QQ</scope><scope>7SC</scope><scope>7SE</scope><scope>7SP</scope><scope>7SR</scope><scope>7TA</scope><scope>7TB</scope><scope>7U5</scope><scope>8BQ</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>H8D</scope><scope>H8G</scope><scope>JG9</scope><scope>JQ2</scope><scope>K9.</scope><scope>KR7</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>P64</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-9333-4920</orcidid></search><sort><creationdate>20200501</creationdate><title>Modified electromyography-assisted optimization approach for predicting lumbar spine loading while walking with backpack loads</title><author>Li, Simon SW ; Chow, Daniel HK</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c413t-7755b1dbb24d57b1b2feebd7fdab0c91a51e3f64c0961251f202461df868e7673</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Algorithms</topic><topic>Anthropometry</topic><topic>Biomechanical Phenomena</topic><topic>Boundary conditions</topic><topic>Compression</topic><topic>Computer applications</topic><topic>Contraction</topic><topic>Deviation</topic><topic>Electromyography</topic><topic>Humans</topic><topic>Joints (anatomy)</topic><topic>Loads (forces)</topic><topic>Lumbar Vertebrae - physiology</topic><topic>Male</topic><topic>Optimization</topic><topic>Spine</topic><topic>Spine (lumbar)</topic><topic>Standard error</topic><topic>Trunk muscles</topic><topic>Walking - physiology</topic><topic>Weight-Bearing</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Simon SW</creatorcontrib><creatorcontrib>Chow, Daniel HK</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Aluminium Industry Abstracts</collection><collection>Biotechnology Research Abstracts</collection><collection>Ceramic Abstracts</collection><collection>Computer and Information Systems Abstracts</collection><collection>Corrosion Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Engineered Materials Abstracts</collection><collection>Materials Business File</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Copper Technical Reference Library</collection><collection>Materials Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Simon SW</au><au>Chow, Daniel HK</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Modified electromyography-assisted optimization approach for predicting lumbar spine loading while walking with backpack loads</atitle><jtitle>Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine</jtitle><addtitle>Proc Inst Mech Eng H</addtitle><date>2020-05-01</date><risdate>2020</risdate><volume>234</volume><issue>5</issue><spage>527</spage><epage>533</epage><pages>527-533</pages><issn>0954-4119</issn><eissn>2041-3033</eissn><abstract>This study modified an electromyography-assisted optimization approach for predicting lumbar spine loading while walking with backpack loads. The modified-electromyography-assisted optimization approach eliminated the electromyography measurement at maximal voluntary contraction and adopted a linear electromyography–force relationship. Moreover, an optimal lower boundary condition for muscle gain was introduced to constrain the trunk muscle co-activation. Anthropometric information of 10 healthy young men as well as their kinematic, kinetic, and electromyography data obtained while walking with backpack loads were used as inputs in this study. A computational algorithm was used to find and analyse the sensitivity of the optimal lower boundary condition for achieving minimum deviation of the modified-electromyography-assisted optimization approach from the electromyography-assisted optimization approach for predicting lumbosacral joint compression force. Results validated that the modified-electromyography-assisted optimization approach (at optimal lower boundary condition of 0.92) predicted on average, a non-significant deviation in peak lumbosacral joint compression force of −18 N, a standard error of 9 N, and a root mean square difference in force profile of 73.8 N. The modified-electromyography-assisted optimization approach simplified the experimental process by eliminating the electromyography measurement at maximal voluntary contraction and provided comparable estimations for lumbosacral joint compression force that is also applicable to patients or individuals having difficulty in performing the maximal voluntary contraction activity.</abstract><cop>London, England</cop><pub>SAGE Publications</pub><pmid>32053045</pmid><doi>10.1177/0954411920906243</doi><tpages>7</tpages><orcidid>https://orcid.org/0000-0001-9333-4920</orcidid></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0954-4119 |
| ispartof | Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine, 2020-05, Vol.234 (5), p.527-533 |
| issn | 0954-4119 2041-3033 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_2354737015 |
| source | SAGE Complete A-Z List; MEDLINE |
| subjects | Algorithms Anthropometry Biomechanical Phenomena Boundary conditions Compression Computer applications Contraction Deviation Electromyography Humans Joints (anatomy) Loads (forces) Lumbar Vertebrae - physiology Male Optimization Spine Spine (lumbar) Standard error Trunk muscles Walking - physiology Weight-Bearing Young Adult |
| title | Modified electromyography-assisted optimization approach for predicting lumbar spine loading while walking with backpack loads |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-09T04%3A20%3A23IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Modified%20electromyography-assisted%20optimization%20approach%20for%20predicting%20lumbar%20spine%20loading%20while%20walking%20with%20backpack%20loads&rft.jtitle=Proceedings%20of%20the%20Institution%20of%20Mechanical%20Engineers.%20Part%20H,%20Journal%20of%20engineering%20in%20medicine&rft.au=Li,%20Simon%20SW&rft.date=2020-05-01&rft.volume=234&rft.issue=5&rft.spage=527&rft.epage=533&rft.pages=527-533&rft.issn=0954-4119&rft.eissn=2041-3033&rft_id=info:doi/10.1177/0954411920906243&rft_dat=%3Cproquest_cross%3E2354737015%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2401736040&rft_id=info:pmid/32053045&rft_sage_id=10.1177_0954411920906243&rfr_iscdi=true |