Create stunning neuro- and biofeedback experiences with ease using neuromore Studio!
The Studio is designed to enable everyone from neuroscientists, therapists and clinicians to neuroenthusiasts to build biofeedback applications without writing code. Drag and drop nodes together and create immersive biofeedback applications at the speed of thought.
neuromore Studio provides you with a hardware-agnostic interface that includes medical grade EEG amplifiers, consumer EEG headsets, and heart and GSR sensors. Those devices include:
- Neurosity Crown, Notion, & Notion 2
- Interaxon Muse 2
- OpenBCI Cyton, Daisy, Ganglion
- G.Tec Unicorn (via Brainflow)
- Ant Neuro eego mini 8 and mini 24
- Brainmaster Discovery
- Mitsar EEG 201
- Polar 10
- All Brainflow devices
- ... and many more
Have a look at the devices section in our docs to see a full list of supported devices. We're always interested in extending this list together with our community so if you have a request or want to integrate a device, please reach out and we can find a way to make it work with the Studio.
Create immersive end-to-end experiences from protocol to visualization. The Studio comes with 4 pre-built games in which you can control the speed of a car, the weather, screen effects and volume. You can also choose to play videos or audio files and control their brightness and volume for personalized neurofeedback training. And if you want to go one step further, you can also make your application control your Unity game, your favorite audio production, or your visualizer of choice via the Open Sound Control protocol. The only limit is our imagination!
Analyze raw and processed EEG and other bio-signals in real-time using various signal views, a 3D LORETA brain representation, power spectograms, and more.
- Live biodata viewer
- 3D LORETA visualization
- Feedback visualizations
- Power spectrograms
- Completely configurable layouts
Analyze your own sessions or sessions of your patients in the cloud under account.neuromore.com using various graphs and statistics.
Click here to learn about neuromore Licensing
- Create a free neuromore community cloud account.
- Download the latest neuromore Studio from our github releases, Mac App Store or build it yourself.
- Start neuromore Studio, sign-in with the created community account from step 1, accept the license and you're ready to go.
- Check out the wiki for specific device information or examples on how to get started
- Watch the tutorials on YouTube for more info
What | Minimum |
---|---|
OS | Windows 10, Ubuntu 20.04, macOS 10.15 |
CPU | Intel* or ARM**, 32 or 64 Bit, Dual-Core, ~2Ghz |
RAM | 4GB |
GPU | OpenGL 2.x compatible |
Display | 1920x1080 |
* Intel 64-Bit Build requires CPU released past ~2010 with SSE4.2, AVX and other modern instructions
** Supports ARMv7-a (32-Bit) and ARMv8-a (64-Bit)
- You can delete this folder to fully reset your installation
- The logfile is stored there
Platform | Folder |
---|---|
WIN | %LOCALAPPDATA%\neuromore\NMStudio |
LINUX | ~/.local/share/neuromore/NMStudio |
MACOS | ~/Library/Containers/com.neuromore.studio/Data/Library/Application Support/neuromore/NMStudio |
See this for more information about how to compile neuromore Studio.
See this for more information about the third party software included in this repository.
Have a look at our Github Discussions forum to ask questions, brainstorm about future ideas, and connect to other community members.
Q: Can I build an offline version of neurmore studio (one that does not require your backend)?
A: This is a work in progress. We don't provide an option for that. For now, access to our backend is mandatory.
Q: Is the backend code included or available so that I can host it myself?
A: No. The backend code and database design is not included in this repository.
Q: How do I reset my password?
A: https://account.neuromore.com/#/login
- Run the muse-2 in neuromore - https://github.com/naxocaballero/muse2-neuromore - thanks to @naxocaballero
- There's also an LSL to OSC converter by @ViacheslavBobrov that works with the muse.
- BrainFlow configuration by @Andrey1994