Association between spectral characteristics of paraspinal muscles and functional disability in low back pain patients: a cohort study

Abstract

Objectives. Characteristics of muscle activity, represented by surface electromyography (EMG), have revealed differences between patients with low back pain and healthy adults; how they relate to functional and clinical parameters remains unclear. The purpose of the current study was to examine the correlation between frequency characteristics of EMG (analysed using continuous wavelet transform (CWT) analysis) and patients’ self-rated score of disability. Design and setting. This is a case control study with fifteen patients with mechanical low back pain (LBP) without radicular symptoms. Patients were recruited from the orthopaedic clinic at Charing Cross Hospital. Ten healthy adults were recruited from the staff working in the hospital and associated university. Patients completed the Roland-Morris Disability Questionnaire (RMDQ) and bilateral EMG activity was obtained from erector spinae at vertebral levels L4 and T12. Subjects performed 3 brief maximal isometric voluntary contractions (MVCs) of the back extensors and the torque was measured using a dynamometer. CWT was applied to the EMG signals of each muscle in a 200ms window centred around the peak torque obtained during the MVCs. The ratio (low/high frequencies) of the energy, the peak power, and the frequency of the peak power were calculated for each recording site, averaged and correlated with the individual’s RMDQ score. Results. Patients had lower peak power (T12 and L4) and lower frequency of the peak power (at T12) than the healthy adults. Additionally, RMDQ positively correlated to the average ratio of energy at T12 (rho=0.63; p=0.012), i.e. greater self-rated disability corresponded to a dominant distribution of energy in the lower frequencies. Conclusion. The current findings reveal alterations in EMG profile and its association with self-related back pain disability, suggesting that spectral characteristics of EMG reflect muscle function.