ESP-EEG is an affordable 8-channel biosensing board

The Cerelog ESP-EEG is an open-source, 8-channel biosensing board based on Texas Instruments’ ADS1299 analog-digital converter, designed to deliver cleaner EEG signals at a lower cost. Developed by former SpaceX engineer Simon Hakimian, the device aims to offer an affordable alternative to commercial EEG systems while maintaining high signal quality.

The ESP-EEG utilizes the same core chip as the OpenBCI Cyton, the TI ADS1299, which provides 24-bit resolution across eight channels. Unlike the Cyton, the Cerelog version emphasizes true closed-loop active bias circuitry, which is claimed to improve signal clarity. The device currently supports USB connectivity; although it has hardware support for Bluetooth and Wi-Fi, the firmware for these features is not yet available, limiting its use to wired connections for now.

Software support includes a fork of the OpenBCI GUI via Lab Streaming Layer and BrainFlow, enabling compatibility with existing EEG data analysis tools. The project is open-source, licensed under MIT for firmware and software, but with hardware schematics under CC-BY-NC-SA, restricting commercial use. The firmware is available upon request via email, though some confusion about licensing terms has been clarified by the developer, Simon Hakimian.

Why It Matters

The ESP-EEG’s affordability and open-source design could democratize access to EEG technology for researchers, hobbyists, and developers. Its focus on signal quality and native Wi-Fi streaming offers potential improvements over existing low-cost EEG devices, making it attractive for experimental and educational use. However, its current reliance on USB and the non-commercial licensing may limit some applications.

Background

The open-source EEG hardware market has seen increased interest with devices like OpenBCI’s Cyton, which uses a PIC32 microcontroller and RFduino. Cerelog’s ESP-EEG distinguishes itself by using the ESP32 platform, aiming for high-bandwidth Wi-Fi streaming and onboard features like LiPo charging. The project emerged amid a broader trend toward accessible, customizable biosensing technology for research and DIY projects.

“I wanted to handle everything natively on the ESP32 for high-bandwidth WiFi streaming, which required a ground-up redesign. Building it from scratch helped me uncover a lot of subtle design constraints.”

— Simon Hakimian, developer of ESP-EEG

“Firmware & Software: MIT License. Hardware Schematics: CC-BY-NC-SA. I want people to build whatever they want on top of the stack, but need to protect the hardware from low-effort commercial clones.”

— Simon Hakimian, on licensing

What Remains Unclear

It is not yet clear when the Wi-Fi and Bluetooth firmware will be fully available, limiting wireless functionality. The hardware schematics are not published publicly, and licensing terms are somewhat confusing, which may affect commercial or derivative use. The actual performance improvements over existing devices remain to be validated through user testing.

What’s Next

The next steps include the release of Wi-Fi and Bluetooth firmware, broader testing of the device’s signal quality, and potential expansion of hardware features like onboard filtering. Monitoring community feedback and developer updates will clarify the device’s practical advantages and limitations.

Key Questions

What makes the ESP-EEG different from other open-source EEG boards?

The ESP-EEG uses TI’s ADS1299 chip like the OpenBCI Cyton but emphasizes true closed-loop active bias circuitry for cleaner signals. It is built on the ESP32 platform for native Wi-Fi streaming and has a focus on affordability and open-source design.

Can I use the ESP-EEG wirelessly now?

No, the firmware for Bluetooth and Wi-Fi is not yet available. Currently, it only supports USB connections, which are not electrically isolated.

Is the hardware open-source?

The schematics are licensed under CC-BY-NC-SA, restricting commercial use, but are available for non-commercial purposes. Firmware and software are licensed under MIT. The hardware files are not publicly posted, but can be requested via email.

What are the main advantages of this device?

It offers potentially cleaner EEG signals due to its active bias circuitry, native Wi-Fi streaming capabilities, and a lower price point compared to traditional research-grade EEG systems.

When will the wireless firmware be available?

The developer has not provided a specific timeline for the release of Wi-Fi and Bluetooth firmware, so users should expect some delay before full wireless functionality is supported.