A Personalized Approach to Student Mental Health: Real-Time EEG Biofeedback for Stress and Focus Management

Real-time monitoring of student stress and focus requires low-cost EEG systems, but fixed spectral thresholds may not transfer reliably across users because EEG amplitude and band power vary between individuals and recording conditions. This study investigates a subject-specific thresholding approach using a two-channel Brain BioAmp acquisition setup (FP1 and FP2) and an ESP32-based FFT pipeline. Beta/Alpha and Theta/Alpha ratios are calculated from spectral band estimates and compared with thresholds derived from Baseline, Focused, and Stressed task-condition recordings. In the reported pilot results, the mean Beta/Alpha ratio increased from 2.76 during Baseline to 2.80 during Focused and 2.88 during Stressed conditions. The Theta/Alpha ratio was lowest during Focused (0.95) and highest during Stressed (1.04), compared with 0.99 during Baseline. These are descriptive observations; classification accuracy, statistical significance, and generalization across participants have not been established. The signal-processing calculations and plotted frequency ranges should be checked against the original implementation before these values are treated as final.