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 ($\approx 0.08~μ\text{V}_{\text{RMS}}$), tightly bounded sampling jitter ($0.56~μ\text{s}$ standard deviation), and negligible long-term drift ($< 1~\text{ppm}$). 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 $112~\text{dB}$ under balanced conditions, with a localized $26.9~\text{dB}$ degradation observed under source-impedance mismatch. Closed-loop validation achieved $99.17\%$ online accuracy and an information transfer rate of $27.66~\text{bits/min}$. These results position the proposed system as a quantitatively characterized embedded EEG measurement and processing platform for real-time SSVEP decoding.

翻译：本文提出了一种基于ESP32-S3微控制器和ADS1299模拟前端的嵌入式脑电仪器平台，用于实时稳态视觉诱发电位解码。该系统完全在设备上执行8通道脑电采集、零相位带通滤波和典型相关分析，同时支持无线通信和闭环操作，无需外部计算。一个核心贡献在于对该平台测量完整性的定量表征。报告结果表明其具有稳定的短路输入噪声基底（约0.08微伏有效值）、严格受限的采样抖动（0.56微秒标准差）以及可忽略的长期漂移（小于1ppm）。数值保真度分析显示混合精度嵌入式处理流程与64位双精度参考模型之间达到100%的决策一致性。在平衡条件下，有效共模抑制超过112分贝，在源阻抗失配时观察到局部26.9分贝的性能下降。闭环验证实现了99.17%的在线准确率和27.66比特/分钟的信息传输速率。这些结果表明，所提出的系统是一个经过定量表征的、用于实时SSVEP解码的嵌入式脑电测量与处理平台。