Improving mobile EEG signal processing [placeholder title]

The brain generates electrical signals which can be measured with electrodes placed on the head of a person (EEG). However, muscles also generate electrical signals (EMG) which have similar characteristics. Strong muscle activity is not limited to facial muscles but, for example, during exercise, a multitude of muscles generate artefacts. Here, muscles from the whole body will stray into the EEG, with the muscles closest to the EEG cap bearing the strongest influence. With recent advances in mobile neuroimaging technologies, when people are actively moving, a solution is needed to apply adaptive filtering of muscle artifacts in realtime, and which can also work with a limited number of electrodes. Our proposed solution is based on the idea that EEG is local under a specific electrode, but that EMG originates further afield. This offers the opportunity to subtract the EMG from the EEG. Realtime noise reduction allows now to a) leave the lab and record in unknown environments and dynamically changing artefacts and b) to record low power gamma & beta activity which is related to cognitive processes beyond motor readiness potentials. Thus, we will raise the bar substantially to arrive at real solutions impacting both EEG device development and cognitive EEG recordings during activities in sport and outside in natural environments.