Study Design: A comparative analysis of electromyogram (EMG) signals of patients of cervical pain and normal controls.

Objectives: To determine the differences between frequency and time domain parameters of EMG signals of patients of cervical pain and normal controls.

Summary Of Background Data: No diagnostic technique has emerged as a satisfactory tool for identification of spinal pain.

Method: Seventeen male and 17 female chronic neck pain patients without cervical radiculopathy were recruited through neurology EMG clinic. The controls consisted of 30 male and 33 female subjects with no history of neck pain in the past 12 months. All subjects performed flexion, left anterolateral flexion, left lateral flexion, left posterolateral extension, and extension to pain threshold/20% maximum voluntary contraction and pain tolerance/maximum voluntary contraction in random order. The descriptive statistics for body weight normalized strength, normalized peak EMG, time to onset, time to peak, median frequency, mean power frequency, and frequency bands were calculated. These variables were subjected to analysis of variance and logistic regression to distinguish between patients and controls.

Results: The normalized peak EMG of patients was significantly greater than those of controls in both maximal and submaximal exertions (P < 0.01). Whereas there was no consistent pattern in time to peak EMG, the time to onset of EMG revealed that the left sternocleidomastoid was always recruited before the onset of torque. A lack of significant difference in the median frequency of the 2 samples indicates that the pain did not disturb the muscle conduction velocity. Using discriminant logistic regression on frequency domain and time domain parameters, up to 97% of patients and controls were correctly classified with the resubstitution method.

Conclusion: Surface EMG can be used successfully in distinguishing chronic pain patients and controls, and efficacy of treatment regimes.

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http://dx.doi.org/10.1097/01.brs.0000259927.85981.31DOI Listing

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