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Differentiating temporal electromyographic waveforms between those with chronic low back pain and healthy controls
Objectives. Temporal activation patterns from abdominal and lumbar muscles were compared between healthy control subjects and those with chronic low back pain. Study design. A cross-sectional comparative study. Background. Synergist and antagonist coactivity has been considered an important neuromus...
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| Published in: | Clinical biomechanics (Bristol) 2002-11, Vol.17 (9), p.621-629 |
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| creator | Hubley-Kozey, C.L. Vezina, M.J. |
| description | Objectives. Temporal activation patterns from abdominal and lumbar muscles were compared between healthy control subjects and those with chronic low back pain.
Study design. A cross-sectional comparative study.
Background. Synergist and antagonist coactivity has been considered an important neuromuscular control strategy to maintain spinal stability. Differences in onset times and amplitudes have been reported from trunk muscle EMG recordings between healthy subjects and those with low back pain;however, evaluating temporal EMG waveforms should demonstrate whether differences exist in the ability of those with and those without low back pain to respond to changing perturbations.
Methods. The Karhunen–Loève expansion was applied to the ensemble-average EMG profiles recorded from four abdominal and three trunk extensor muscle sites while subjects performed a leg-lifting task aimed at challenging lumbar spine stability. The principal patterns were derived and the weighting coefficients for each pattern were the main dependent variables in a series of two-factor (group and muscle) mixed
anova models.
Results. Three principal patterns explained 96% of the variance in the temporal EMG profiles. The
anovas revealed statistically significant group and muscle main effects (
P |
| doi_str_mv | 10.1016/S0268-0033(02)00103-1 |
| format | article |
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Study design. A cross-sectional comparative study.
Background. Synergist and antagonist coactivity has been considered an important neuromuscular control strategy to maintain spinal stability. Differences in onset times and amplitudes have been reported from trunk muscle EMG recordings between healthy subjects and those with low back pain;however, evaluating temporal EMG waveforms should demonstrate whether differences exist in the ability of those with and those without low back pain to respond to changing perturbations.
Methods. The Karhunen–Loève expansion was applied to the ensemble-average EMG profiles recorded from four abdominal and three trunk extensor muscle sites while subjects performed a leg-lifting task aimed at challenging lumbar spine stability. The principal patterns were derived and the weighting coefficients for each pattern were the main dependent variables in a series of two-factor (group and muscle) mixed
anova models.
Results. Three principal patterns explained 96% of the variance in the temporal EMG profiles. The
anovas revealed statistically significant group and muscle main effects (
P<0.05) for the principal pattern and significant group by muscle interactions (
P<0.05) for patterns two and three. Post hoc analysis showed that patterns were not different among all muscle sites for the healthy controls, but differences were significant for the low back pain group.
Conclusions. The healthy group coactivated all seven sites with the same temporal pattern of activation. The low back pain group used different activation patterns indicative of a lack of synergistic coactivitation among the muscle sites examined.
Relevance
These results provide a foundation for developing a diagnostic classifier of neuromuscular impairment associated with low back pain, that could be used to evaluate the effectiveness of therapeutic interventions to improve muscle coactivation.</description><identifier>ISSN: 0268-0033</identifier><identifier>EISSN: 1879-1271</identifier><identifier>DOI: 10.1016/S0268-0033(02)00103-1</identifier><identifier>PMID: 12446158</identifier><language>eng</language><publisher>England: Elsevier Ltd</publisher><subject>Abdominal Muscles - physiology ; Abdominal Muscles - physiopathology ; Adult ; Algorithms ; Back - physiology ; Back - physiopathology ; Chronic Disease ; Coactivation ; Electromyography ; Electromyography - methods ; Electromyography - statistics & numerical data ; Exercise Test ; Humans ; Low Back Pain - diagnosis ; Low Back Pain - physiopathology ; Lumbosacral Region - physiology ; Lumbosacral Region - physiopathology ; Male ; Middle Aged ; Muscle, Skeletal - physiopathology ; Pattern recognition ; Pattern Recognition, Automated ; Predictive Value of Tests ; Principal Component Analysis ; Reproducibility of Results ; Statistics as Topic ; Synergists ; Temporal patterns ; Trunk muscles</subject><ispartof>Clinical biomechanics (Bristol), 2002-11, Vol.17 (9), p.621-629</ispartof><rights>2002 Elsevier Science Ltd</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c361t-ef47b661b7a63169a0e9d9172c6b310b538835d43ff0259282f08a716c7a79be3</citedby><cites>FETCH-LOGICAL-c361t-ef47b661b7a63169a0e9d9172c6b310b538835d43ff0259282f08a716c7a79be3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/12446158$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hubley-Kozey, C.L.</creatorcontrib><creatorcontrib>Vezina, M.J.</creatorcontrib><title>Differentiating temporal electromyographic waveforms between those with chronic low back pain and healthy controls</title><title>Clinical biomechanics (Bristol)</title><addtitle>Clin Biomech (Bristol, Avon)</addtitle><description>Objectives. Temporal activation patterns from abdominal and lumbar muscles were compared between healthy control subjects and those with chronic low back pain.
Study design. A cross-sectional comparative study.
Background. Synergist and antagonist coactivity has been considered an important neuromuscular control strategy to maintain spinal stability. Differences in onset times and amplitudes have been reported from trunk muscle EMG recordings between healthy subjects and those with low back pain;however, evaluating temporal EMG waveforms should demonstrate whether differences exist in the ability of those with and those without low back pain to respond to changing perturbations.
Methods. The Karhunen–Loève expansion was applied to the ensemble-average EMG profiles recorded from four abdominal and three trunk extensor muscle sites while subjects performed a leg-lifting task aimed at challenging lumbar spine stability. The principal patterns were derived and the weighting coefficients for each pattern were the main dependent variables in a series of two-factor (group and muscle) mixed
anova models.
Results. Three principal patterns explained 96% of the variance in the temporal EMG profiles. The
anovas revealed statistically significant group and muscle main effects (
P<0.05) for the principal pattern and significant group by muscle interactions (
P<0.05) for patterns two and three. Post hoc analysis showed that patterns were not different among all muscle sites for the healthy controls, but differences were significant for the low back pain group.
Conclusions. The healthy group coactivated all seven sites with the same temporal pattern of activation. The low back pain group used different activation patterns indicative of a lack of synergistic coactivitation among the muscle sites examined.
Relevance
These results provide a foundation for developing a diagnostic classifier of neuromuscular impairment associated with low back pain, that could be used to evaluate the effectiveness of therapeutic interventions to improve muscle coactivation.</description><subject>Abdominal Muscles - physiology</subject><subject>Abdominal Muscles - physiopathology</subject><subject>Adult</subject><subject>Algorithms</subject><subject>Back - physiology</subject><subject>Back - physiopathology</subject><subject>Chronic Disease</subject><subject>Coactivation</subject><subject>Electromyography</subject><subject>Electromyography - methods</subject><subject>Electromyography - statistics & numerical data</subject><subject>Exercise Test</subject><subject>Humans</subject><subject>Low Back Pain - diagnosis</subject><subject>Low Back Pain - physiopathology</subject><subject>Lumbosacral Region - physiology</subject><subject>Lumbosacral Region - physiopathology</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Muscle, Skeletal - physiopathology</subject><subject>Pattern recognition</subject><subject>Pattern Recognition, Automated</subject><subject>Predictive Value of Tests</subject><subject>Principal Component Analysis</subject><subject>Reproducibility of Results</subject><subject>Statistics as Topic</subject><subject>Synergists</subject><subject>Temporal patterns</subject><subject>Trunk muscles</subject><issn>0268-0033</issn><issn>1879-1271</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2002</creationdate><recordtype>article</recordtype><recordid>eNqFkMFu1DAURS0EotPSTwB5hWAR-mwndrJCVaGAVKkL6NpynOfGkNjB9nQ0f0_aGcGS1duce6_eIeQ1gw8MmLz4Dly2FYAQ74C_B2AgKvaMbFiruopxxZ6TzV_khJzm_BMAat6ol-SE8bqWrGk3JH3yzmHCULwpPtzTgvMSk5koTmhLivM-3iezjN7SnXlAF9OcaY9lhxhoGWNGuvNlpHZMMazQFHe0N_YXXYwP1ISBjmimMu6pjWHtm_Ir8sKZKeP58Z6Ru-vPP66-Vje3X75dXd5UVkhWKnS16qVkvTJSMNkZwG7omOJW9oJB34i2Fc1QC-eANx1vuYPWKCatMqrrUZyRt4feJcXfW8xFzz5bnCYTMG6zVlxxaCRfweYA2hRzTuj0kvxs0l4z0I-y9ZNs_WhSA9dPsjVbc2-OA9t-xuFf6mh3BT4eAFzffPCYdLYeg8XBp1WuHqL_z8QfQ_uQTg</recordid><startdate>20021101</startdate><enddate>20021101</enddate><creator>Hubley-Kozey, C.L.</creator><creator>Vezina, M.J.</creator><general>Elsevier Ltd</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>7X8</scope></search><sort><creationdate>20021101</creationdate><title>Differentiating temporal electromyographic waveforms between those with chronic low back pain and healthy controls</title><author>Hubley-Kozey, C.L. ; Vezina, M.J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c361t-ef47b661b7a63169a0e9d9172c6b310b538835d43ff0259282f08a716c7a79be3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2002</creationdate><topic>Abdominal Muscles - physiology</topic><topic>Abdominal Muscles - physiopathology</topic><topic>Adult</topic><topic>Algorithms</topic><topic>Back - physiology</topic><topic>Back - physiopathology</topic><topic>Chronic Disease</topic><topic>Coactivation</topic><topic>Electromyography</topic><topic>Electromyography - methods</topic><topic>Electromyography - statistics & numerical data</topic><topic>Exercise Test</topic><topic>Humans</topic><topic>Low Back Pain - diagnosis</topic><topic>Low Back Pain - physiopathology</topic><topic>Lumbosacral Region - physiology</topic><topic>Lumbosacral Region - physiopathology</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Muscle, Skeletal - physiopathology</topic><topic>Pattern recognition</topic><topic>Pattern Recognition, Automated</topic><topic>Predictive Value of Tests</topic><topic>Principal Component Analysis</topic><topic>Reproducibility of Results</topic><topic>Statistics as Topic</topic><topic>Synergists</topic><topic>Temporal patterns</topic><topic>Trunk muscles</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hubley-Kozey, C.L.</creatorcontrib><creatorcontrib>Vezina, M.J.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Clinical biomechanics (Bristol)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hubley-Kozey, C.L.</au><au>Vezina, M.J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Differentiating temporal electromyographic waveforms between those with chronic low back pain and healthy controls</atitle><jtitle>Clinical biomechanics (Bristol)</jtitle><addtitle>Clin Biomech (Bristol, Avon)</addtitle><date>2002-11-01</date><risdate>2002</risdate><volume>17</volume><issue>9</issue><spage>621</spage><epage>629</epage><pages>621-629</pages><issn>0268-0033</issn><eissn>1879-1271</eissn><abstract>Objectives. Temporal activation patterns from abdominal and lumbar muscles were compared between healthy control subjects and those with chronic low back pain.
Study design. A cross-sectional comparative study.
Background. Synergist and antagonist coactivity has been considered an important neuromuscular control strategy to maintain spinal stability. Differences in onset times and amplitudes have been reported from trunk muscle EMG recordings between healthy subjects and those with low back pain;however, evaluating temporal EMG waveforms should demonstrate whether differences exist in the ability of those with and those without low back pain to respond to changing perturbations.
Methods. The Karhunen–Loève expansion was applied to the ensemble-average EMG profiles recorded from four abdominal and three trunk extensor muscle sites while subjects performed a leg-lifting task aimed at challenging lumbar spine stability. The principal patterns were derived and the weighting coefficients for each pattern were the main dependent variables in a series of two-factor (group and muscle) mixed
anova models.
Results. Three principal patterns explained 96% of the variance in the temporal EMG profiles. The
anovas revealed statistically significant group and muscle main effects (
P<0.05) for the principal pattern and significant group by muscle interactions (
P<0.05) for patterns two and three. Post hoc analysis showed that patterns were not different among all muscle sites for the healthy controls, but differences were significant for the low back pain group.
Conclusions. The healthy group coactivated all seven sites with the same temporal pattern of activation. The low back pain group used different activation patterns indicative of a lack of synergistic coactivitation among the muscle sites examined.
Relevance
These results provide a foundation for developing a diagnostic classifier of neuromuscular impairment associated with low back pain, that could be used to evaluate the effectiveness of therapeutic interventions to improve muscle coactivation.</abstract><cop>England</cop><pub>Elsevier Ltd</pub><pmid>12446158</pmid><doi>10.1016/S0268-0033(02)00103-1</doi><tpages>9</tpages></addata></record> |
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| subjects | Abdominal Muscles - physiology Abdominal Muscles - physiopathology Adult Algorithms Back - physiology Back - physiopathology Chronic Disease Coactivation Electromyography Electromyography - methods Electromyography - statistics & numerical data Exercise Test Humans Low Back Pain - diagnosis Low Back Pain - physiopathology Lumbosacral Region - physiology Lumbosacral Region - physiopathology Male Middle Aged Muscle, Skeletal - physiopathology Pattern recognition Pattern Recognition, Automated Predictive Value of Tests Principal Component Analysis Reproducibility of Results Statistics as Topic Synergists Temporal patterns Trunk muscles |
| title | Differentiating temporal electromyographic waveforms between those with chronic low back pain and healthy controls |
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