The delay optimization for the alpha rhythm phase-locked neuromodulation system

Closed-loop neuromodulation systems have gained significant attention due to their ability to adapt stimulation parameters based on real-time brain activity, potentially reducing individual variability and enhancing treatment efficacy compared to open-loop approaches. This study investigates the impact of system latency on the performance of alpha rhythm phase-locked neuromodulation systems. Offline analysis revealed that signal transmission delays significantly affect phase estimation accuracy. A comparison between BrainAmp and OpenBCI EEG devices showed notable differences in latency, with BrainAmp exhibiting a latency of $74.4 \pm 7.9 \mathrm{~ms}$ while the embedded OpenBCI system achieved minimal transmission delays ($\lt \lt 1 \mathrm{~ms}$). Online implementation demonstrated that despite OpenBCI’s lower signal quality, its reduced transmission delays resulted in higher accuracy in phase estimation at the 0 -moment, with Mean Absolute Circular Error (MACE) values improving by over 0.25 in both eyes-open and eyes-closed conditions. The findings emphasize the importance of minimizing system latencies in closed-loop neuromodulation systems to enhance the effectiveness of phaselocked stimulation. By addressing both algorithmic sophistication and system latency, this research contributes to the development of more precise and efficient neuromodulation techniques for applications in neurological and psychiatric disorders.