Analysis of the EEG Rhythms Based on the Empirical Mode Decomposition During Motor Imagery When Using a Lower-Limb Exoskeleton. A Case Study - Ortiz, Mario; Iáñez, Eduardo; Contreras-Vidal, José L.; Azorín, José M. (Frontiers in Neurorobotics, 2020)
The use of brain-machine interfaces in combination with robotic exoskeletons is usually based on the analysis of the changes in power that some of the brain rhythms experiment during a motion event. However, this variation in power is frequently obtained through frequency filtering and power estimation by using the Fourier analysis. This paper explores the decomposition of the brain rhythms based on the Empirical Mode Decomposition, as an alternative for the analysis of electroencephalographic (EEG) signals, due to its adaptive capability to the local oscillations of the data, showing it as a viable tool for future BMI algorithms based on motor related events.