Researchers in neuroscience computing experience difficulties when they try to carry out neuro analysis in practice or when they need to design an explainable brain-computer interface (BCI) with a quick setup and minimal training phase. There is a need for interpretable computational intelligence techniques and new brain states decoding for a more understandable interpretation of the sensory, cognitive, and motor brain processing. We propose a general-purpose fuzzy software system shell for developing a custom EEG BCI system. It relies on the bursts of the ongoing EEG frequency power synchronization/desynchronization at scalp level and supports quick BCI setup by linguistic features, ad hoc fuzzy membership construction, explainable IF-THEN rules, and the concept of the Internet of Things (IoT), which makes the BCI system device and service independent. It has a potential for designing both passive and event-related BCIs with options for visual representation at a scalp-source level in response to time. The feasibility of the proposed system has been proven by real experiments and bursts for and frequency power have been detected in real-time in response to evoked visuospatial selective attention. The presence of the proposed new brain state decoding can be used as a feasible metric for the interpretation of the spatiotemporal dynamics of the passive or evoked neural oscillations.