As noticed by Peach and McGill, the drawback of discriminant analysis is inconsistent selection of input parameters which they attributed to overfitting of the data or not using the holdout group. There is no apparent explanation for this dominance or occasional use of linear regression. The most dominant classification methods were different types of discriminant analysis. The trend of classification only between LBP and NLBP groups continues in recent investigations exploring classification potential of large array surface electromyography. Only smaller part of the research was directed to development of sEMG-based classification models enabling differentiation to LBP and NLBP groups, and none of these investigated problems whether LBP patients could be further classified to homogenous groups such as a low back pain with radiculopathy (LBPR). The results suggest possibility of differentiating low back pain patients to subgroups depending on clinical symptoms.ĭifferences in spectral variables of surface EMG (sEMG) signals recorded over low back muscles of subjects with low back pain (LBP) and those without (NLBP) have been thoroughly explored in the past. The achieved overall accuracy of the implemented decision tree classification model was at best 86.8%. There was no significant difference between CLBP patients and control subjects. Student's t-test detected that regression line slope of the median frequency is significantly different ( p < 0.05) only between low back pain patients with radiculopathy and other two groups. As a descriptor of spectral changes, the median frequency of the power spectrum (MDF) was estimated by use of Hilbert–Huang transform. Surface EMG signals were recorded over the paraspinal muscles at L1–L2 and L4–L5 interspace level. A variant of the Roman chair was used to perform static contractions, where subject's own upper body weight was used to induce muscle fatigue in low back muscles.

In this paper, a classification model based on surface EMG parameter is introduced to differentiate low back pain patients with radiculopathy from chronic low back pain (CLBP) patients and control subjects. The classification potential of surface electromyographic (EMG) parameters needs to be explored beyond classification of subjects onto low back pain subjects and control subjects.

Emg for lower back pain