What the project tests
Each run turns Muse 2 EEG into short temporal windows, then evaluates whether a model can separate the REST/OPEN/CLOSE action-state label and identify the active finger when movement is present.
The deployment path adds a finger-applicability head, confidence thresholds, smoothing, stability checks, and same-finger hold logic before any prediction is treated as a robot-hand command.