title: Differentiating temporal electromyographic waveforms between those with chronic low back pain and healthy controls.
abstract: OBJECTIVE
  Temporal activation patterns from abdominal and lumbar muscles were compared between healthy control subjects and those with chronic low back pain.
  
  
  METHODS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Motion Analysis Laboratory, School of Physiotherapy, Dalhousie University, 5869 University Avenue, Halifax, NS, Canada B3J 3H5. clk@dal.ca
authors.forename: C L
authors.initials: CL
authors.lastname: Hubley-Kozey
authors.forename: M J
authors.initials: MJ
authors.lastname: Vezina
mesh_terms: D000009:Abdominal Muscles / Q000502:physiology / Q000503:physiopathology; D000328:Adult; D000465:Algorithms; D001415:Back / Q000502:physiology / Q000503:physiopathology; D002908:Chronic Disease; D004576:Electromyography / Q000379:methods* / Q000706:statistics & numerical data*; D005080:Exercise Test; D006801:Humans; D017116:Low Back Pain / Q000175:diagnosis* / Q000503:physiopathology*; D008161:Lumbosacral Region / Q000502:physiology / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D018482:Muscle, Skeletal / Q000503:physiopathology*; D010363:Pattern Recognition, Automated; D011237:Predictive Value of Tests; D025341:Principal Component Analysis; D015203:Reproducibility of Results; D013223:Statistics as Topic