DECODING THE CORRELATION AMONG LEG MUSCLE AND BRAIN ACTIVATIONS IN DIFFERENT BODY MOVEMENTS

Abstract

We investigated the correlation among brain and leg muscle activations by analyzing Electroencephalogram (EEG) and Electromyogram (EMG) signals in different conditions. Twelve subjects performed four tasks, including (1) quarter turns, (2) U-turns, (3) bypass obstacles, and (4) repeating quarter turns and U-turns two times. Then, we quantified the alterations of the complexity of these signals by computing the fractal dimension and sample entropy. The results showed that EEG and EMG signals in the case of the first task are more complex than the second task, in which they are more complex than the third task. Furthermore, the brain and muscle signals show the least complexity in the case of the fourth task. Moreover, we found strong correlations in the variations of fractal dimension ([Formula: see text]) and sample entropy ([Formula: see text]) between EEG and EMG signals in various tasks. Therefore, brain and muscle activations are strongly correlated in different tasks. Similar analyses can be conducted in the case of other organs to decode their correlations.