The system
The neural oscillation in electroencephalogram (EEG) signals is highly related to people’s psychological cognitive ability. To achieve an optimal real-time modulation effect on the alpha wave, we first conduct comprehensive delay analysis and technology selection to propose the ideal architecture of a neural feedback system.
After measurement and analysis of hardware and software delay, we implement an OpenBCI version of a phase-locked feedback control system for real-time alpha wave regulation. Compared with the distributed architecture across Brainamp, PC and Arduino in previous work, the new system integrates all modules — signal acquisition, phase estimation and applying stimulation — on one chip. The delay for signal transmission is therefore effectively eliminated, which leads to better accuracy for phase estimation in phase-locked feedback control.
Results
The results show the effectiveness of the proposed system for alpha wave regulation, with significant modulation advantages in amplitude and frequency compared to distributed BrainProduct architectures. We also developed a PyQtGraph-based visualization tool for real-time monitoring on the host computer, streaming data from the OpenBCI board over Bluetooth 2.0.
