Wavelet Coherence Analysis of Brain and Muscle Electrical Activities in Lower Limb Movements

Abstract

Corticomuscular coherence (CMC), which represents the link between the electroencephalogram (EEG) and the electromyogram (EMG), is frequently used to investigate the functional relationship between the human brain and muscles. The wavelet coherence function will be used in this study to evaluate EEG-EMG coherence. Datasets comprising simultaneous EEG-EMG signals from ten subjects walking on flat surfaces, stairs, and ramps that are publicly accessible are used. EEG signals from the motor cortex region (C1, C2, and CZ) and EMG signals from the tibialis anterior (TA) are subjected to the wavelet coherence function. The paper looks at how the theta (0.5–4 Hz), delta (4–8 Hz), alpha (8–12 Hz), beta (14–30 Hz), and gamma (30–50 Hz) frequency bands interact with the EEG and EMG signals. The results reveal a notable coherence across a variety of activities between the electrical activity of the brain and that of the muscular system. Various activities also show various frequency-band interactions. The Kruskal-Wallis non-parametric one-way ANOVA test is used to assess the statistical significance of the results, which reveals that during level walking activities the theta and alpha frequency bands and coherence values in the C2-TA and CZ-TA groups are significantly higher than those in the control group (p < 0.05) Still, none of the three channels show notable numbers in the other frequency range. Still, none of the three channels show significant data in the other frequency range. Especially in the alpha frequency range (8–12 Hz), the results showed that C1-TA had an MSC level of 3.12 for the highest coherence levels. Natural techniques are used in this work to cover all typical frequency bands. Results for different walking patterns across separate EEG channels show that the theta and alpha frequency bands have considerably stronger coherence than the others. This is pertinent to clinical methods of CMC analysis and provides fascinating content for further CMC research.