International Journal of Advanced Research in Computer and Communication Engineering

Abstract: Brain–Computer Interfaces (BCIs) enable direct communication between human cognitive activity and electronic systems without requiring physical movement. Recent advancements in wearable EEG technology, microcontroller processing capabilities, and low-cost sensor fusion techniques have opened new pathways for neuro-controlled robotic systems. This research presents the development and validation of a non-invasive, EEG-triggered nano-drone lift-off system using the Neuro-Sky MindWave Mobile 2 headset and an ESP32 microcontroller.
EEG Attention signals are acquired over Bluetooth using the Think Gear protocol, decoded on the ESP32, and passed through a carefully tuned threshold-based decision algorithm that activates the propulsion system. A complementary filtering method, combined with a PID-based stability controller, integrates real-time orientation data from an MPU6050 6-axis gyroscope–accelerometer to ensure stable flight. Two DRV8833 dual-channel motor drivers drive four brushed DC motors attached to a custom 3D-printed nano-quadcopter frame.
The system successfully demonstrates hands-free lift-off triggered purely through cognitive focus, achieving reliable activation, stable hover behaviour, and low-latency control. The prototype proves that low-cost, single-sensor EEG systems can be effectively integrated with autonomous nano-drones, paving the way for scalable, accessible neuro-controlled robotic platforms. This work has implications in assistive technology, rehabilitation robotics, telepresence applications, and future human–machine interaction research.

Keywords: Brain Computer Interface, Neuro-Sky, EEG, Drone Control, Assistive Technology, Signal Processing, Real-Time Systems.

Downloads: | DOI: 10.17148/IJARCCE.2025.141286