In this study, we present a new 64-channel mobile EEG system (NeusenW, Neuracle Inc.), and compare it to a state-of-the-art wired laboratory EEG system and evaluate the EEG signal quality. Previous studies were only performed on seated participants in laboratory environments, and only a very limited number focus on motion conditions. In this study, we instead implemented experiments in standing, walking and running conditions. To preliminarily evaluate the EEG quality recorded by both EEG systems, we first compared the alpha wave (8-13 Hz) frequency band using a spectral analysis approach, due to the fact that, while a EEG user has their eyes closed, the alpha wave power is the strongest spontaneous EEG signals. Steady-state visually evoked potential (SSVEP)-based BCI spellers are one of the most popular BCI paradigms [4-5]. Here, SSVEP is a periodic response elicited by specific visual stimuli. In our approach, we further validated the mobile EEG system using a SSVEP-based BCI paradigm. Finally, to evaluate the EEG signal quality, the online and offline classification accuracies were compared.