This paper presents the development of a Brain-Computer Interface (BCI) as a neuromodulation system that detects cortical patterns related to the planning and execution of upper limb movements and closes the motor rehabilitation loop through Functional Electrical Stimulation (FES) with the H-GAIT neuroprosthesis. The foundational elements of the proposed system are biopotentials such as electroencephalography (EEG) and electromyography (EMG), cortical patterns, spatial filters, and pattern detection algorithms. Offline and online biosignal capture protocols were developed to first characterize the selected cortical pattern, then detect it online, and finally close the BCI-FES loop, resulting in a low-latency system capable of inducing neuroplasticity.