Basics of EEG-based Brain-Computer Interfaces

In this event, current brain-controlled wheelchair project lead Adam Del Rosso will cover the basics of building a non-invasive EEG-based BCI system. An overview of the many disciplines that contribute to the neurotech field will be provided, including neuroscience, signal processing, and machine learning. Then, Adam will provide a status of work within the brain-controlled wheelchair team and demonstrate the current capabilities of their low-cost BCI system featuring OpenBCI technology.

How to set up an Open BCI Board (Cyton) - 2018

Learn how to setup OpenBCI on Windows 10.

Written instructions here

Data Collection, Preprocessing, and Feature Extraction - NXT @ RIT

Here is discussed means of filtering, noise management, machine learning in context, some simple feature extraction techniques and a few which have recently been popular. Feature reduction, class and feature dimensionality problems, and potential solutions such as PCA and NCA and hierarchical classification are mentioned and explained.

Produced by NXT and ArgZero Technologies LLC

EEG, EOG, EMG and Machine Learning in MATLAB - NXT @ RIT

A basic introduction to biosignal collection, some descriptions of the signals of interest and some potential approaches to machine learning of these signals. Also discussed is the basics of machine learning as applied to some of these biosignals.

Produced by NXT and ArgZero Technologies LLC

Using Lab Streaming Layer (LSL) For Brain-Computer Interfaces

Here we show as a proof of concept why LSL should be used in our projects and an example of how to do it in our lab as well as an example use case using a Transradial Prosthetic Simulator.

Produced by NXT and ArgZero Technologies LLC