EEG Prototype

EEG Prototype — Wireless Brain Activity Acquisition System

A prototype electroencephalograph (EEG) for acquiring and recording the brain's electrical activity, with real-time visualization in both time and frequency domains.

Developed as a degree project at Universidad Politécnica Territorial de Aragua "Federico Brito Figueroa" (Venezuela).

---

Overview

This project implements a complete EEG acquisition system composed of:

• Analog front-end: Low-noise biopotential acquisition circuit with instrumentation amplifier, eighth-order active filter with butterworth topology, non-inverting adder for an offset to adapt the signal to logical level required for ADC and microcontroller, notch filter to mitigate the 60Hz noise
• Digital processing: ESP32 microcontroller with websockets for communication
• Wireless communication: WiFi for real-time data streaming
• Web interface: Browser-based visualization of EEG signals in time and frequency domains with FIR and IIR digital filters

The system captures brain electrical activity on the ESP32, streams raw 16-bit samples over WebSocket, and applies digital filtering (31-tap FIR with Hamming window, 1st-order IIR, both low-pass and high-pass) in the browser for real-time visualization in the time and frequency domains.

---

Specifications

---

Design Highlights

• Analog biopotential amplification: Circuit based on the AD620 due to its low noise and high CMRR
• Complete system integration: Analog acquisition + digital processing + wireless communication + web visualization in a single project.
• Digital signal processing: FIR and IIR filters implemented in JavaScript on the client-side, with configurable low-pass and high-pass modes.
• Frequency-domain analysis: Real-time power spectrum computed via FFT.
• Wireless data streaming: WiFi WebSocket server streams EEG data to any browser.
• Cross-platform visualization: Works on PC, tablet, or smartphone without installing any application.
• Open hardware design: Full KiCad schematic, PCB, and Gerbers included.

---

Repository Structure

• hardware/ — KiCad schematic, PCB, Gerbers, BOM
• firmware/ — ESP-IDF source project
• docs/ — Design documentation, calculations, thesis summary

---

Signal Processing

FIR Filter

• Topology: 31-tap FIR
• Window: Hamming
• Configurations: Low-pass and high-pass

IIR Filter

• Topology: 1st-order IIR
• Configurations: Low-pass and high-pass

Frequency Analysis

• FFT-based power spectrum
• Real-time display in web interface

---

Web Interface

The web interface allows visualization of EEG signals from any device with a browser (PC, tablet, smartphone) connected to the same WiFi network.

Features:

• Real-time time-domain plot
• Real-time frequency-domain plot (power spectrum)
• Filter selection (FIR/IIR, LP/HP)

---

Tools Used

• KiCad — Schematic capture, PCB layout
• ESP-IDF / PlatformIO — ESP32 firmware development
• C — Firmware programming language
• HTML/CSS/JavaScript — Web interface

---

Team

• David Obregon
• Diosey Lugo

Tutor: Prof. Carlos Aponte

Institution: Universidad Politécnica Territorial de Aragua "Federico Brito Figueroa" Date: April 2026

---

Author Contact

• Gmail: dioseyadolfolugo@gmail.com
• GitHub: https://github.com/diosey
• LinkedIn: http://www.linkedin.com/in/adolfodiaz01