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Open-Source 8-Ch BCI Board (ESP32 and ADS1299 and OpenBCI GUI)

Details

External ID
46502051
Source
HN
Company
—
Product
Open-Source 8-Ch BCI Board (ESP32 and ADS1299 and OpenBCI GUI)
Website domain
github.com
Launched
Jan. 5, 2026
Cohort
—
Upvotes
54
Upvotes percentile
0.8096179183135704
Tags
—
Fetched at
Sept. 7, 2026, 9:25 p.m.
Updated at
Sept. 7, 2026, 9:25 p.m.

Description

Hi HN, I recently shared this on r/BCI and wanted to see what the engineering community here thinks.A while back, I got frustrated with the state of accessible BCI hardware. Research gear was wildly unaffordable. So, I spent a ton of time designing a custom board, software and firmware to bridge that gap. I call it the Cerelog ESP-EEG. It is open-source (Firmware + Schematics), and I designed it specifically to fix the signal integrity issues found in most DIY hardware.I believe in sharing the work. You can find the Schematics, Firmware, and Software setup on the GitHub repo: GITHUB LINK: https://github.com/Cerelog-ESP-EEG/ESP-EEGFor those who don't want to deal with BGA soldering or sourcing components, I do have assembled units available: https://www.cerelog.com/eeg_researchers.htmlThe major features: Forked/modified OpenBCI GUI Compatibility as well as Brainflow API, and LSL Compatibility. I know a lot of us rely on the OpenBCI GUI for visualization because it just works. I didn't want to reinvent the wheel, so I ensured this board supports it natively.It works out of the box: I maintain a forked modified version of the GUI that connects to the board via LSL (Lab Streaming Layer). Zero coding required: You can visualize FFTs, Spectrograms, and EMG widgets immediately without writing a single line of Python.The "active bias" (why my signal is cleaner): The TI ADS1299 is the gold standard for EEG, but many dev boards implement it incorrectly. They often leave the Bias feedback loop "open" (passive), which makes them terrible at rejecting 60Hz mains hum. I simply followed the datasheet: I implemented a True Closed-Loop Active Bias (Drive Right Leg).How it works: It measures the common-mode signal, inverts it, and actively drives it back into the body. The result: Cleaner dataTech stack: ADC: TI ADS1299 (24-bit, 8-channel). MCU: ESP32 Chosen to handle high-speed SPI and WiFi/USB streaming Software: BrainFlow support (Python, C++, Java, C#) for those who want to build custom ML pipelines, LSL support, and forked version of OpenBCI GUI support This was a huge project for me. I’m happy to geek out about getting the ESP32 to stream reliably at high sample rates as both the software and firmware for this project proved a lot more challenging than I expected. Let me know what you think!SAFETY NOTE: I strongly recommend running this on a LiPo battery via WiFi. If you must use USB, please use a laptop running on battery power, not plugged into the wall.

Enrichment

Theme
open-source hardware and embedded electronics
Vertical
Horizontal
Function
Hardware & robotics
Audience
Developer
AI stance
Not AI
Project type
Hobby / open-source project
Normalized one-liner
open-source 8-channel brain-computer interface board
Manually corrected
False

Could you build this?

No Designing an 8-channel EEG brain-computer interface board requires specialized electrical engineering for microvolt-level analog signal filtering, custom PCB layout, and low-level firmware integration.

What it would actually take: Building an open BCI board requires multi-layer PCB design with isolated analog ground planes and extreme noise mitigation for the TI ADS1299 ADC. The firmware demands precise SPI timing, real-time interrupt handling on the ESP32, and high-throughput streaming over Wi-Fi/Bluetooth with minimal jitter. This necessitates deep expertise in biomedical instrumentation, analog/mixed-signal circuit design, and embedded C/C++ firmware development.

Discussion

20 comments analyzed.

Competitors mentioned: OpenBCI Cyton, Polar H10 heart rate monitor, EEG-based biofeedback devices with three electrodes

Concerns raised: SPI communication underspecified, causes timing violations during initialization, I2C barely works, High pricing barrier ($1,249 for Cyton), Three-electrode EEG headsets can't accurately read different brain waves from same location, BLE software implementation challenges with MAC drivers

Feature requests: 16-channel or 32-channel board for research studies, Higher channel count with daisy-chaining ADC support, Side-by-side comparison data with OpenBCI, Dedicated common-mode and differential hardware filtering to lower noise floor, Closed-loop control system integration with tACS for neurofeedback

Competitors

Other products that read as similar to this one — 54 launches clear the similarity bar, closest 8 shown.

Attention rank: #16 of 55 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 47 days after the earliest competitor.

Other launches for this product

Same idea, different domain

Nobody's really built a hardware & robotics tool for Fintech yet.