MGaming EEG‐BCI: Advancing Inclusive and Gesture‐Free Neural Interaction for Mobile Gaming Applications

This study introduces MGaming EEG‐BCI, a mobile brain–computer interface framework designed to enable gesture‐free gaming through neural activity based on motor imagery (MI). The proposed system integrates an OpenBCI Cyton + Daisy headset for noninvasive EEG acquisition with a real‐time processing pipeline, including band‐pass filtering, independent component analysis (ICA), common spatial patterns (CSPs) feature extraction, and linear discriminant analysis (LDA) classification. A Firebase‐based cloud infrastructure enables real‐time synchronization with a Unity‐developed mobile game incorporating tap‐style interaction. Fifteen participants were recruited, of whom nine completed the full protocol, including training, gameplay, and user feedback. The system achieved a mean classification accuracy of 55.29%, with peak performance reaching 98.82%. Most participants successfully exceeded the predefined gameplay score threshold. User feedback indicated strong interest in future use, despite challenges related to calibration time and device comfort. The MGaming EEG‐BCI demonstrates the feasibility of gesture‐free, EEG‐based mobile gaming and highlights its potential for inclusive and accessible interaction. The system provides a foundation for future developments in accessible entertainment, rehabilitation, and advanced human–computer interaction (HCI).