Gait Analysis of Electromyographic Spectral Differences in Stroke Survivors and Healthy Controls

Surface electromyography (sEMG) is a commonly used technique to evaluate neuromotor disorders. The study of spectral components of sEMG signals can provide insights into the behavior of muscles. This study assessed the activity of the tibialis anterior (TA) muscle during gait of individuals affected by stroke and healthy controls. Spectral methods were used to study distinctive features of stroke gait, to differentiate the paretic side of stroke patients from their nonparetic side and to compare it to healthy reference. Spectrograms of sEMG signals were used as a visual tool to intuitively display power output along gait phases. These observations were then verified with the computation of mean frequency (MNF) and median frequency (MDF) from the power spectral density (PSD). Results indicated that MNF and MDF were significantly reduced in paretic and nonparetic limbs compared to healthy controls (p < 0.001). A decrease in MNF and MDF was also observed in paretic vs. nonparetic in stance (pMNF = 0.018) and swing (pMNF < 0.001, pMDF < 0.015) phases. In general, a decrease in the activation power of high frequencies of TA muscle was observed, suggesting the presence of foot drop. Spectral differences between affected and unaffected sides of stroke patients were analyzed, which may be expanded in future studies using other time-frequency domain techniques, such as wavelets. This work demonstrated the viability of frequency domain approaches to characterize gait asymmetries in stroke. In consequence, this method may complement traditional clinical evaluation of the severity and evolution of patients when subjected to intervention and/or rehabilitation strategies.