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I CONTROLLED A ROBOT ARM WITH MY BRAIN, USING THIS HIGH-TECH HEADSET

A 3D-printed headset that reads your brainwaves and turns them into commands that move robotic hands, drones, or cursors — no surgery, no implant.

by OpenBCI (Conor Russomanno, Joel Murphy, and community)

FULL CAD BOM FIRMWARE DOCS

Open-hardwareScience

difficulty
●●●●○
time
several weekends
license
MIT
repo
repo ACTIVE950 stars

WHAT YOU’LL NEED

  • 3D printer + filament — printable parts — files are in the repo
  • Electronic parts — full list with part numbers in the repo BOM
  • Dev board / microcontroller — runs the project firmware

Partner

Show off your build — Record and edit your build video by editing the transcript, not the timeline.Try Descript
1

COMPAREE VERDICT

OpenBCI is the real thing: a non-invasive brain-computer interface you can build at home. The Ultracortex headset is 3D-printed, the electrodes sit on your scalp, and the biosensing board (Cyton or Ganglion, bought from OpenBCI) reads the tiny electrical signals your brain and muscles produce. The open-source GUI turns those signals into commands, and people have used it to move robotic arms, fly drones, and control cursors. The wow is that it works and it is fully open. The hard part is getting reliable control — EEG signals are noisy, electrode placement matters, and you will spend real time on signal processing and calibration before you get a clean command. This is not plug-and-play; it is a research-grade tool that happens to be open source. If you want to explore BCIs without waiting for a consumer product or a lab, this is the project. If you want a weekend demo that just works, you will be disappointed. The single thing most likely to go wrong: expecting consistent control on day one. Budget time for learning the signal chain, not just printing the headset.

NOT IN THE REPO

  • —The Ultracortex headset is fully open hardware (STLs, BOM, assembly guide).
  • —The Cyton or Ganglion biosensing board is bought from OpenBCI — you do not solder it from scratch.
  • —GUI software is MIT-licensed and cross-platform (Windows/Mac/Linux).
  • —Getting reliable control takes real work — signal processing, electrode placement, and a lot of calibration.
  • —Not a medical device; community-supported, not a polished consumer product.
  • —Licence is MIT for software, CC BY-SA 4.0 for Ultracortex hardware — commercial use is allowed.

Can I build this?

PrintUltracortex Mark IV headset frame and electrode mounts (several prints, PLA or PETG)
BuyCyton or Ganglion biosensing board from OpenBCI, gold cup electrodes, electrode gel, conductive paste, header pins, jumper wires, optional WiFi shield
Tools3D printer, soldering iron for board headers, computer running Windows/Mac/Linux for the GUI, optional oscope or multimeter for signal debugging
SkillsIntermediate 3D printing, basic soldering, comfort with signal processing concepts — the GUI is approachable but getting clean signals requires patience and iteration
TimeA weekend to print and assemble the headset, then several sessions to calibrate and get reliable control — real BCI work, not a quick demo
Cost$$ — biosensing board is the bulk (Cyton around $500, Ganglion around $200), headset print and electrodes add another $50-100
SafetyNone beyond ordinary electronics care — non-invasive, low voltage signals only. Not a medical device, do not use for diagnosis or treatment.

Build at your own risk. Projects involve tools, electronics and sometimes mains voltage — follow the creator’s safety notes.

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Gallery

Start here

Navigation into the creator’s own docs — we don’t rewrite the guide, we route you to the source.

  1. 1.Decide which biosensing board to buy — Cyton (8 channels, more expensive, more research-grade) or Ganglion (4 channels, cheaper, still capable).(The board is not built from scratch; you buy it from OpenBCI and solder the header pins.)
  2. 2.Print the Ultracortex Mark IV frame and electrode mounts from the GitHub repo. (STLs, BOM, and assembly instructions are in the repo. Print settings matter for fit.)
  3. 3.Order gold cup electrodes, electrode gel, and conductive paste (links in the BOM).(Cheap electrodes give noisy signals; the BOM specifies tested parts.)
  4. 4.Download and install the OpenBCI GUI on your computer. (Cross-platform, well-documented, and actively maintained.)
  5. 5.Assemble the headset, connect the board, and start with the GUI's impedance check to verify electrode contact.(Good contact is everything — expect to iterate on placement and paste.)

Resources

Documentation, files and community threads for this build — we link straight to the original sources and never rehost the creator’s files.

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KNOWN ISSUES

  • Buying the wrong board for your use case — Ganglion is cheaper but has fewer channels; if you want to explore motor imagery or serious signal work, Cyton is the better start.
  • Expecting clean control on day one — EEG signals are tiny (microvolts) and noisy, and getting a reliable command takes real calibration time.
  • Skimping on electrodes or paste — cheap electrodes add noise, and dry paste ruins contact; the BOM exists for a reason.
  • Printing the headset without checking fit — the frame needs to hold electrodes snugly against your scalp, and head sizes vary; test fit early.
  • Not budgeting time to learn the signal chain — the GUI is approachable, but understanding FFT, bandpass filters, and artefact rejection is part of the work if you want robust control.
  • Treating it like a consumer product — this is a research tool with community support, not a polished kit; expect to read docs and ask questions.

Do I build the biosensing board from scratch?

No — the Cyton or Ganglion board is bought from OpenBCI as a finished PCB; you solder on the header pins and optionally add a WiFi shield. The open part is the GUI software and the Ultracortex headset.

Can I actually control things reliably, or is this a demo?

Both — people have used it for real control (moving robotic hands, flying drones, cursor control), but getting there takes work. Signal quality depends on electrode placement, your environment, and calibration. It is not plug-and-play.

What is the difference between Cyton and Ganglion?

Cyton has 8 channels and better specs (higher sample rate, more research-grade); Ganglion has 4 channels and costs less. Ganglion is enough for basic BCI experiments; Cyton is better if you want to go deep.

Is this safe to use?

Yes — it is non-invasive, reads signals from your scalp, and operates at low voltages. It is not a medical device and should not be used for diagnosis or treatment.

What can I control with it?

Anything that accepts serial or OSC commands — robotic arms, drones, games, cursors. The GUI has examples and integrations, but you will likely need to write or adapt code for your specific use case.

Community builds

No community builds yet — be the first, we feature the best ones.

Discussion1

FROM THE COMPAREE TEAM

The hardest part is not printing the headset or buying the board — it is getting clean, consistent signals through the noise. What would you try to control first, and how much calibration time would you budget before expecting it to work reliably?

CompareeTEAM29d agoedited

Practical notes from our verification: the Ultracortex repo has STLs, a full BOM, and assembly docs; the GUI repo is actively maintained and cross-platform. The biosensing board is bought from OpenBCI, not built from components — the open part is the software and the headset. The Business Insider demo is real (Conor Russomanno moving a robotic hand with alpha-wave concentration), but it is the result of setup and calibration, not a first-run wow. The single biggest thing to know before starting: this is not a weekend demo kit; it is a research-grade tool that requires real time on signal processing and electrode tuning to get reliable control. If you are comfortable with that, it is the most accessible open BCI available.

OpenBCI (Conor Russomanno, Joel Murphy, and community)

OpenBCI started as a Kickstarter in 2013 to make brain-computer interfaces accessible outside labs. The project grew into a full platform — biosensing boards, open-source software, and a printed headset — all designed to let people explore BCIs without waiting for consumer products or research budgets.

GitHub

Star the project on GitHub

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GitHub repo