Welcome to VIP-BCI documentation!

Hello, navigating this documentation is fairly straight foward, you can see the component tree in the navigation bar at the left. Each description unit serves a specific porpuse, perhaps you will find particularly interesting the Installation and Tutorials sections, as the information there is enough to give you working knowledge of the platform (installing, training, testing and extending it for your personal use cases). This is, however, surface knowledge; to delve into the advanced tutorials you will need to look into the Component Description section, to have a notion of the organization of the application. Further more, if you want to modify, remove or add functionality, exploring the source code is mandatory. Theory section and Statistics and Performance section is not required, but are valuable assets if you ever want to replicate some of the things we do here.

General Objective

Our principal purpose is to build brain interfaces that can be used by general people in two applications: gaming and robotic hand control. The brain-computer interface has to establish a communication with the application without the employment muscles. To use the software knowledge about the usage of electroencephalographic (EEG) sensors, signal processing, machine learning and programming skills is required.

Limitations

This project is subject to several limitations, the first one comes from the motivation itself, and it is that the system must be non-invasive and should rely only brain signals that reach the cerebral cortex. Also, due to the limited amount of sensors for data acquisition only 8 sections of said cortex can be explored at the same time. The type of signal that can be extracted with this limitations enables us to differentiate between two states: whether the region is consideration is under stress or it is relaxed. See the Theory section for further information.

Objectives

So, what can you expect from our work, well here are the objectives we set our minds in:

  • Use the data acquired with each sensor, determine the stress state of each region of the brain in a given time (by measuring power in frequency ranges)
  • Train a classifier that takes the said data and determines the action the user is thinking about (only two actions are possible)
  • Build different gaming platforms to test the classifying algorithm

Specific Capabilities

With this application you can do basically the following things:

  • Train the system to recognize LEFT and RIGHT brain signals of a specific individual
  • Train the system to recognize whether the user is under mental concentration or is relaxed
  • Play to different games: a box moving game and a car race game with your brain (using the data acquired in the training stages)