How OpenBCI_GUI is used to visualize EEG data

By /

What is OpenBCI?

  • OpenBCI is an open source brain-computer interface platform founded after the successful Kickstarter crowdfunding. It aims to make the collection of physiological signals such as EEG, EMG and EKG more approachable and scalable.
  • Its hardware boards (32-bit, older 8-bit and Ganglion boards) support EEG/EMG/EKG signal sampling and can record data via Bluetooth or SD card

1. What is OpenBCI_GUI

OpenBCI_GUI It is a cross-platform graphical interface software (written by Java + Processing) officially provided by OpenBCI. It is mainly used for:

  • Display of EEG, EMG, ECG and other signals in real time
  • Do data recording and playback
  • Quickly test whether the hardware is working
  • Forward collected data to other software (such as Unity, MATLAB, Python, LSL, etc.)

it supports Windows / macOS / Linux, can also run on Raspberry Pi Go.

2. preparations

To collect and visualize EEG data using OpenBCI_GUI, you need to prepare:

  1. hardware
    • An EEG acquisition board (such as Cyton 8 channels, Cyton+Daisy 16 channels, or Ganglion 4 channels)
    • Electrode cap or Ultracortex 3D printed helmet (or directly with patch electrodes)
    • Wireless communication module (USB Dongle / WiFi Shield)
  2. software
    • from OpenBCI GUI Releases Download and install the GUI
    • Install the corresponding driver (such as the FTDI Driver）

3. Connection and startup process

  1. Connect the hardware
    • Connect EEG electrodes to the head according to the designated channel positions (e.g., international 10-20 system)
    • Power up the board (battery or USB)
    • Plug in USB Dongle to your computer
  2. launcher GUI
    • Open the OpenBCI_GUI application
    • Select the data source (“Live (from OpenBCI)”) on the launch interface
    • Select the plate type (Cyton / Cyton+Daisy / Ganglion)
    • Select serial port (COMx / /dev/ttyUSBx) or WiFi
    • click Start System

4. Introduction to interface functions

After entering the real-time data interface, you will see multiple data visualization windows:

  • Time Series(Time waveform diagram)
    The raw EEG waveform of each channel, in µV, is easy to detect signal quality.
  • FFT / Power Spectrum(Spectrum diagram)
    Display the power in each frequency band (Delta, Theta, Alpha, Beta, Gamma) for observing the EEG rhythm.
  • Head Plot(Scalp distribution map)
    The potential distribution of each channel is displayed using a 2D head-type thermogram.
  • Band Power Bar(Band Energy Histogram)
    Displays the energy changes of each channel in specific frequency bands (such as Alpha waves 8 – 12 Hz), often used for relaxation or concentration detection.
  • Accelerometer Data
    If the hardware has a built-in accelerometer, head movement information will be displayed (for easy detection of motion artifacts).

5. Data recording and forwarding

  • recording data
    click Start Data Stream → Record Data, select the save path. GUI will be generated .txt or .csv Format for subsequent analysis (such as Python / MATLAB).
  • data forwarding
    Enabled in the GUI Networking Function to transfer data through:
    • LSL (Lab Streaming Layer) → Provide EEG Lab, BCILAB and other scientific research software
    • UDP / OSC → Provide real-time interactive programs such as Unity, TouchDesigner, Max/MSP
    • Serial → To Arduino / Microcontroller

6. using skills

  • Signal quality check: You can cut to the GUI Signal Quality Mode, check the impedance of each electrode. Green is the best, and red indicates poor contact.
  • filtering: You can select high-pass, low-pass, and notch filtering (such as 50/60 Hz power frequency interference) in the GUI.
  • channel switch: If some channels are noisy, they can be temporarily closed.
  • playback mode: Select the data source as Playback from File, you can use the GUI to replay previously collected data.

Official website:https://openbci.com/
Github：https://github.com/OpenBCI
Oil tubing:

Scroll to Top