Relationship between pain and intersegmental spinal motion characteristics in low-back pain subjects
This study was undertaken to determine the relationship between low-back pain and spinal motion. Percutaneous intra-pedicle screws were placed into the right and left L4 (or L5) and S1 segments of nine chronic low-back pain patients. Each of the subjects performed a standard battery of spinal motion...
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| creator | Dickey, J.P. Pierrynowski, M.R. Galea, V. Bednar, D.A. Yang, S.X. |
| description | This study was undertaken to determine the relationship between low-back pain and spinal motion. Percutaneous intra-pedicle screws were placed into the right and left L4 (or L5) and S1 segments of nine chronic low-back pain patients. Each of the subjects performed a standard battery of spinal motions including bending in all planes. At the completion of each desired motion, each subject was asked to self-report the pain they experienced on a 10 point scale. The 3D location of markers attached to the pedicle screws was recorded for each motion. Intra- and inter-vertebral motions were calculated. The time series data was reduced to the ranges of motion for each of the tests. A three-layer neural network with fast back-propagation learning algorithm was designed to investigate the relationship between the pain and the motion parameters. This model provided an accurate model for prediction of low-back pain from segmental spinal motion and also offered insights into the mechanisms causing mechanical low-back pain. |
| doi_str_mv | 10.1109/ICSMC.2000.884999 |
| format | Conference Proceeding |
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Percutaneous intra-pedicle screws were placed into the right and left L4 (or L5) and S1 segments of nine chronic low-back pain patients. Each of the subjects performed a standard battery of spinal motions including bending in all planes. At the completion of each desired motion, each subject was asked to self-report the pain they experienced on a 10 point scale. The 3D location of markers attached to the pedicle screws was recorded for each motion. Intra- and inter-vertebral motions were calculated. The time series data was reduced to the ranges of motion for each of the tests. A three-layer neural network with fast back-propagation learning algorithm was designed to investigate the relationship between the pain and the motion parameters. 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This model provided an accurate model for prediction of low-back pain from segmental spinal motion and also offered insights into the mechanisms causing mechanical low-back pain.</description><subject>Algorithm design and analysis</subject><subject>Battery charge measurement</subject><subject>Biology</subject><subject>Fasteners</subject><subject>Humans</subject><subject>Motion measurement</subject><subject>Neural networks</subject><subject>Pain</subject><subject>Predictive models</subject><subject>Testing</subject><issn>1062-922X</issn><issn>2577-1655</issn><isbn>9780780365834</isbn><isbn>0780365836</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2000</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNotkNtKAzEYhIMHsNY-gF7lBbb-SZpNcimLh4IieADvSg7_2tRtumwixbd3pcLAMPDNXAwhlwzmjIG5XjavT82cA8Bc64Ux5ohMuFSqYrWUx2RmlIZRopZaLE7IhEHNK8P5xxk5z3kDwGHB9ISEF-xsibuU17GnDsseMdHexkRtCjSmgkPGzy2mYjua-5hG2-7-GtSv7WD9CMRcos8jTLvdvnLWfx0W8rfboC_5gpy2tss4-_cpeb-7fWseqsfn-2Vz81hFDqJUXAdsZXC1F9opLq2xEEB7rYPmRhnpmJaq5Vo6bwE9Gt3aMSn0IsjgxZRcHXYjIq76IW7t8LM6_CN-ATHTWoM</recordid><startdate>2000</startdate><enddate>2000</enddate><creator>Dickey, J.P.</creator><creator>Pierrynowski, M.R.</creator><creator>Galea, V.</creator><creator>Bednar, D.A.</creator><creator>Yang, S.X.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>2000</creationdate><title>Relationship between pain and intersegmental spinal motion characteristics in low-back pain subjects</title><author>Dickey, J.P. ; Pierrynowski, M.R. ; Galea, V. ; Bednar, D.A. ; Yang, S.X.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i203t-28def5db6c38b725a9a0d08c88d829795b1857f285bca0ece98fa2857ec3d5dc3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2000</creationdate><topic>Algorithm design and analysis</topic><topic>Battery charge measurement</topic><topic>Biology</topic><topic>Fasteners</topic><topic>Humans</topic><topic>Motion measurement</topic><topic>Neural networks</topic><topic>Pain</topic><topic>Predictive models</topic><topic>Testing</topic><toplevel>online_resources</toplevel><creatorcontrib>Dickey, J.P.</creatorcontrib><creatorcontrib>Pierrynowski, M.R.</creatorcontrib><creatorcontrib>Galea, V.</creatorcontrib><creatorcontrib>Bednar, D.A.</creatorcontrib><creatorcontrib>Yang, S.X.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Dickey, J.P.</au><au>Pierrynowski, M.R.</au><au>Galea, V.</au><au>Bednar, D.A.</au><au>Yang, S.X.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Relationship between pain and intersegmental spinal motion characteristics in low-back pain subjects</atitle><btitle>Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0</btitle><stitle>ICSMC</stitle><date>2000</date><risdate>2000</risdate><volume>1</volume><spage>260</spage><epage>264 vol.1</epage><pages>260-264 vol.1</pages><issn>1062-922X</issn><eissn>2577-1655</eissn><isbn>9780780365834</isbn><isbn>0780365836</isbn><abstract>This study was undertaken to determine the relationship between low-back pain and spinal motion. Percutaneous intra-pedicle screws were placed into the right and left L4 (or L5) and S1 segments of nine chronic low-back pain patients. Each of the subjects performed a standard battery of spinal motions including bending in all planes. At the completion of each desired motion, each subject was asked to self-report the pain they experienced on a 10 point scale. The 3D location of markers attached to the pedicle screws was recorded for each motion. Intra- and inter-vertebral motions were calculated. The time series data was reduced to the ranges of motion for each of the tests. A three-layer neural network with fast back-propagation learning algorithm was designed to investigate the relationship between the pain and the motion parameters. This model provided an accurate model for prediction of low-back pain from segmental spinal motion and also offered insights into the mechanisms causing mechanical low-back pain.</abstract><pub>IEEE</pub><doi>10.1109/ICSMC.2000.884999</doi></addata></record> |
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| ispartof | Smc 2000 conference proceedings. 2000 ieee international conference on systems, man and cybernetics. 'cybernetics evolving to systems, humans, organizations, and their complex interactions' (cat. no.0, 2000, Vol.1, p.260-264 vol.1 |
| issn | 1062-922X 2577-1655 |
| language | eng |
| recordid | cdi_ieee_primary_884999 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Algorithm design and analysis Battery charge measurement Biology Fasteners Humans Motion measurement Neural networks Pain Predictive models Testing |
| title | Relationship between pain and intersegmental spinal motion characteristics in low-back pain subjects |
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