Design and Quantitative Evaluation of an Embedded EEG Instrumentation Platform for Real-Time SSVEP Decoding

This paper presents an embedded EEG instrumentation platform for real-time steady-state visually evoked potential (SSVEP) decoding based on an ESP32-S3 microcontroller and an ADS1299 analog front end. The system performs 8-channel EEG acquisition, zero-phase bandpass filtering, and canonical correlation analysis entirely on-device, while supporting wireless communication and closed-loop operation without external computation. A central contribution is the quantitative characterization of the platform's measurement integrity. Reported results demonstrate a stable shorted-input noise floor (≈ 0.08~μVRMS), tightly bounded sampling jitter (0.56~μs standard deviation), and negligible long-term drift (< 1~ppm). Numerical fidelity analysis shows 100% decision agreement between the mixed-precision embedded pipeline and a 64-bit double-precision reference. Effective common-mode attenuation exceeded 112~dB under balanced conditions, with a localized 26.9~dB degradation observed under source-impedance mismatch. Closed-loop validation achieved 99.17% online accuracy and an information transfer rate of 27.66~bits/min. These results position the proposed system as a quantitatively characterized embedded EEG measurement and processing platform for real-time SSVEP decoding.