Kyle Mathewson
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# EEGEdu
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EEGEdu is an educational website to learn about working with electroencephalogram (EEG) data. It is a teaching tool that allows for students to quickly interact with their own brain waves.
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`EEGEdu` is an interactive educational website to learn about working with electroencephalogram (EEG) data. It is a teaching tool that allows for students to interact with their own brain waves.
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It is an interactive web page that you interact with multiple demonstrations of working with EEG data. It is partially inspired by [EEG101](https://github.com/NeuroTechX/eeg-101) but it is strictly web-based. This allows students to interact with EEG brain data without having to install any software.
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`EEGEdu` has been inspired by multiple works that came before. It is inspired by [EEG101](https://github.com/NeuroTechX/eeg-101), but `EEGEdu` is web-based. Being web-based allows students to interact with EEG brain data without having to install any software. Others have used [Neurotech EEG-notebooks in python](https://github.com/NeuroTechX/eeg-notebooks) for data collection and analysis with [muse-lsl](https://github.com/alexandrebarachant/muse-lsl). These software support the Interaxon MUSE headset but require a bluetooth low-energey (BLE) dongle to work with common operating systems (e.g. Windows or Mac OSX). These tools also required the editing `pyglatt` code to connect to Muse headsets. Thus, previous software are cumbersome and serve as a barrier to entry for many students learning about EEG. `EEGEdu` aims to provide students with an accesible introduction to working with their own brain waves.
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This is a useful set of tools that has been inspired by multiple works that came before. Previously, others in the field have been using [Neurotech EEG-notebooks in python](https://github.com/NeuroTechX/eeg-notebooks) for data collection and analysis with [muse-lsl](https://github.com/alexandrebarachant/muse-lsl). These software support the Interaxon MUSE headset but required a bluetooth low-energey (BLE) dongle to work with Windows of Mac systems. It also required the editing of some pyglatt code to connect properly. These software are cumbersome, and serve as a barrier to entry for many students learning about EEG.
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Visit [https://eegedu.com/](https://eegedu.com/]) for the live website.
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# Installation for Development
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If you are interested in developing EEGEdu, here are some instructions to get you started.
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Note: Currently EEGEdu development requires a Mac OSX operating system.
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To start, you will need to install [Homebrew](https://brew.sh) and [yarn](https://yarnpkg.com/lang/en/docs/install/#mac-stable). These are easy one-line installations for Mac users:
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```sh
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# Install homebrew
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/usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
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# Install yarn
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# NOTE: this will also install Node.js if it is not already installed.
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brew install yarn
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# Node.js must be version 10.x for Muse interaction
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# Thus, if you are getting version issues, install n and switch versions
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# sudo npm install -g n
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# sudo n 10.16.0
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```
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Then, in terminal, clone the git repo and enter the folder:
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```sh
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git clone https://github.com/kylemath/EEGEdu
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cd EEGEdu
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```
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You then need to install the required packages for EEGEdu
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```sh
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yarn install
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```
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## Local Development Environment
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Then, you can run the *Development Environment* of EEGEdu:
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```sh
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yarn start dev
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```
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If it is working correctly, the EEGEdu application will open in a browser window at http://localhost:3000.
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## Local Production Environment
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To start the *Local Production Environment*, you can use the following commands:
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```sh
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yarn cache clean
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yarn run build
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serve -s build
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```
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## Deployment
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[EEGEdu](https://eegedu.com) is running on [Firebase](https://firebase.google.com/) and deployment happens automagically using GitHub post-commit hooks, or [Actions](https://github.com/kylemath/EEGEdu/actions), as they are commonly called. You can see how the application is build and deployed by [inspecting the workflow](https://github.com/kylemath/EEGEdu/blob/master/.github/workflows/workflow.yml).
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Currently this is not working and we are deploying locally with firebase
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```sh
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firebase deploy
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```
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after settings up one time with
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```sh
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firebase login
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```
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browser opens and login to accoun
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then
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```sh
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firebase init
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```
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options: Hosting Sites only
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public directory: build
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single-page app: No
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Overwrite - No
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Overwrite - No
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after first installing with
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```sh
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sudo brew install firebase
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sudo yarn global add firebase-tools
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sudo yarn global add firebase
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```
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# Contributing
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The guide for contributors can be found [here](https://github.com/kylemath/EEGEdu/blob/master/CONTRIBUTING.md). It covers everything you need to know to start contributing to EEGEdu.
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# Development Roadmap
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We are aiming to include chances for students to interact with EEG-based brain signals. So we might break down a curriculum into 10 lessons as follows:
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`EEGEdu` is served live at [https://eegedu.com/](https://eegedu.com). This website is served from the software in this repository. So, all you need to do to try the system out is head to [EEGEdu](https://eegedu.com/).
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# EEGEdu Curriculum
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EEGEdu provides an step-by-step incremental tutorial for students to interact with EEG-based brain signals. So, we break down the curriculum into 10 lessons as follows:
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1. Connect + hardware
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Biophysics + signal viewing
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@@ -120,19 +22,154 @@ Biophysics + signal viewing
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9. Neurofeedback p5js demos
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10. BCI trainer
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# References
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# Installation for Development
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* https://github.com/urish/muse-js - based toolbox for interacting with muse
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* https://github.com/NeuroJS/angular-muse - demo with streaming data in Angular, record button,
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* https://github.com/tanvach/muse-fft - starting point react demo
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* https://github.com/neurosity/eeg-pipes - easy pipable operations on eeg data from muse-js
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* https://reactjs.org/ - React for web development
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* https://www.chartjs.org/docs/latest/ - interactive charts
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* https://github.com/urish/muse-lsl - maybe useful to stream to LSL
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If you are interested in developing EEGEdu, here are some instructions to get the software running on your system. *Note*: Currently EEGEdu development requires a Mac OSX operating system.
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To start, you will need to install [Homebrew](https://brew.sh) and [yarn](https://yarnpkg.com/lang/en/docs/install/#mac-stable). These are easy to install with the following Terminal / `bash` commands:
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```sh
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## Install homebrew
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/usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
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## Install yarn
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# NOTE: this will also install Node.js if it is not already installed.
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brew install yarn
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# NOTE: Node.js must be version 10.x for Muse interaction
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# Thus, if you are getting version issues, install n, with the following command:
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# sudo npm install -g n
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# Then, you can switch to version 10.x with the following command:
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# sudo n 10.16.0
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```
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Then, in Terminal/`bash`, clone this Git repository and change directory into the newly cloned folder:
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```sh
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git clone https://github.com/kylemath/EEGEdu
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cd EEGEdu
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```
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Then, you can install the required `yarn` packages for EEGEdu:
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```sh
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yarn install
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```
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## Local Development Environment
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Then, you can run the *Local Development Environment* of EEGEdu:
|
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|
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```sh
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yarn start dev
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```
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If it is working correctly, the EEGEdu application will automatically open in a browser window at http://localhost:3000.
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|
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## Local Production Environment
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|
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To start the *Local Production Environment*, you can use the following commands:
|
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|
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```sh
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yarn cache clean
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yarn run build
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serve -s build
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```
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## Local Testing of Changes
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1. Install any new packages `yarn install`
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1. Start the *Local Development Environment* `yarn start dev`
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1. Look for errors in terminal log
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1. Open's browser to http://localhost:3000
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1. Open Javascript console
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1. Look for errors in console
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1. Connect Mock data stream by clicking Connect button
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1. Run through the `checkFunction` below with Mock data.
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1. Disconnect Mock data stream
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1. Turn on Interaxon Muse headband
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1. Connect Muse data stream
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1. Repeat the `checkFunction` below with Muse data.
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```sh
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# Pseudocode for checking EEGEdu functionality
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checkFunction = {
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view raw data
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change sliders
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make sure data changes and no errors
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click spectra
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move sliders
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make sure changes
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click bands
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move sliders
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make sure changes
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}
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```
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## Deployment
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[EEGEdu](https://eegedu.com) is running on [Firebase](https://firebase.google.com/) and deployment happens automagically using GitHub post-commit hooks, or [Actions](https://github.com/kylemath/EEGEdu/actions), as they are commonly called. You can see how the application is build and deployed by [inspecting the workflow](https://github.com/kylemath/EEGEdu/blob/master/.github/workflows/workflow.yml).
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Currently this automagic deployment is not working, so we can deploy to firebase manually:
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First, install the Firebase deployment tools:
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```sh
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sudo brew install firebase
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sudo yarn global add firebase-tools
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sudo yarn global add firebase
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```
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The first deployment requires login and initialization once:
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```sh
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firebase login
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```
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Browser opens, and login to Google account authorized for Firebase deployment:
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```sh
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firebase init
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```
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* options: Hosting Sites only
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* public directory: build
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* single-page app: No
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* Overwrite - No
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* Overwrite - No
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||||
Then, deployment to Firebase happens with the following commands:
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```sh
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# clean the local cache to ensure most recent version is served
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yarn cache clean
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# build the latest version of the site
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yarn run build
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# deploy the latest version to firebase
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firebase deploy
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```
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# References and Related Tools
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* [Muse 2016 EEG Headset JavaScript Library (using Web Bluetooth)](https://github.com/urish/muse-js)
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* [Muse 2016 + Web Bluetooth demo app in Angular](https://github.com/NeuroJS/angular-muse)
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* [Explore Muse headband data in frequency domain](https://github.com/tanvach/muse-fft)
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* [Pipeable RxJS operators for working with EEG data in Node and the Browser](https://github.com/neurosity/eeg-pipes)
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* [React, A JavaScript library for building user interfaces](https://reactjs.org/)
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* [Simple yet flexible JavaScript charting for designers & developers](https://www.chartjs.org/docs/latest/)
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* [Muse 2016 EEG Headset LSL (NodeJS)](https://github.com/urish/muse-lsl)
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* [Electroencephalogram (EEG) Recording Protocol for Cognitive and Affective
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Human Neuroscience Research](https://static1.squarespace.com/static/5abefa62d274cb16de90e935/t/5df7db5956ec9170a9b402e1/1576524637645/Electrode_Application_Protocol_Final_Compressed.pdf)
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# Contributing
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The guide for contributors can be found [here](https://github.com/kylemath/EEGEdu/blob/master/CONTRIBUTING.md). It covers everything you need to know to start contributing to EEGEdu.
|
||||
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# Credits
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`EEGEdu` - An Interactive Electrophysiology Tutorial with the Interaxon Muse brought to you by Mathewson Sons
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`EEGEdu` - An Interactive Electrophysiology Tutorial with the Interaxon Muse brought to you by Mathewson Sons.
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# License
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