Contribution differential electromyographic diagnostics of low back pain and radiculopathy : doctoral thesis - Ostojić, Saša (S. Ostojić ; Fakultet elektrotehnike i računarstva, 2019)
Low back pain is one of the leading causes of absence from work. Diagnosing low back pain patients or mere differentiation from healthy subjects is therefore an interesting problem. One way to diagnose comes from properties of surface EMG signals to reflect complex changes occurring within skeletal muscles during fatiguing static contractions. This doctoral work introduces differentiation of low back pain patients with radiculopathy from chronic nonspecific low back pain patients and from healthy subjects based only on four surface EMG signals. The measurement protocol was simplified, and subject’s own upper body weight is used to induce muscle fatigue in low back muscles. Surface EMG signals were recorded during static contractions above m. erector spinae. The adaptive time-frequency method, Hilbert-Huang transform, was utilized to estimate power spectrum of the recorded surface EMG signals. As a descriptor of surface EMG spectral changes, the regression line of slope of the median frequency of the power spectrum was calculated and used as classification feature for the decision tree classification. Proposed measurement protocol, defined classification feature and classification model enable electromyographic differentiation of low back pain patients with radiculopathy and chronic nonspecific low back pain patients, where achieved overall accuracy of classification is up to 86.8 %. Keywords: biomedical signal processing; classification; electromyography; Hilbert–Huang transform; low back pain; radiculopathy.