Decoding knee angles from EEG signals for different walking speeds

Recent studies have hypothesized that the motor cortex is particularly active during specific phases of gait cycle. It has been found that cortical coherence appearance differs in time depending on walking speed. In this work, we analyze the influence of walking speed by decoding knee angles from low frequency EEG components. Linear regression models are applied to show significant correlations between actual and decoded angles while different walking speeds are performed. Additionally, a comparison between walking speeds suggests that the decoding correlation increases with lower speeds.