Using deep learning to "read your thoughts" -- with Keras and EEG

When saying a word in your mind, your brain does not fully decouple the process of "sub-vocalizing" that word from speaking it, which can result in either minor or imperceptible movements of the mouth, tongue, larynx or other facial muscles.* The act of activating a muscle is not just a single "command" as we'd imagine in the digital world, but involves the repeated firing of multiple motor units (collections of muscle fibers and neuron terminals), at a rate of somewhere between 7–20 Hz, depending on the size and structure of the muscle. These firings will be providing us the electrical signal we are looking for, which we can read using an EMG sensor. To read the signals I used an OpenBCI board, technically designed for EEG, which I had on hand from some previous biofeedback experiments. EEG typically requires higher resolution, so if anything, this should help in picking up the weaker EMG signals we are looking for.