Left-hand vs. Right-hand finger tapping experiment

The aim of Brain-Computer Interface (BCI) is to improve the autonomy of people with severe motor disabilities by new communication and control options. It is commonly known that either if you perform a movement, or you think about actually doing this movement, the same area in the brain is activated. Therefore, the point with these…

EEGLAB Tutorial: Import Events

Get your data ready EEGLAB can be used for the analysis and visualization of EEG datasets recorded using OpenBCI hardware and software. EEGLAB can work with a variety of different file types, including those that are exported from the OpenBCI GUI, as we saw in the previous post. Events File If you are working with…

EEGLAB Tutorial: Import Data

EEGLAB can be used for the analysis and visualization of EEG datasets recorded using OpenBCI hardware and software. EEGLAB can work with a variety of different file types, including those that are exported from the OpenBCI GUI, as we saw in the previous post. Get your data ready EEG Data File EEG data can be…

Research with OpenBCI

In recent years, Brain-Computer Interfaces (BCIs) have been steadily gaining ground in the market, used either as an implicit or explicit input method in computers for accessibility, entertainment or rehabilitation. Past research in BCI has profoundly neglected the human aspect in the loop, focusing mostly on the machine layer. Further, due to the high cost…

MI and ME-BCI Training with OpenBCI

MI-BCI training is based on visuo-motor imagination and together with other mental task imagination (e.g. mental subtraction, word association) is the only paradigm of endogenous nature that does not require external stimulation but only the user’s imaginative action. In addition, MI is considered the most importan type of BCI paradigm for motor function restoration. Results…

Introduction to Mu Waves

Brain-Computer Interfaces (BCI) are currently being pursued in several approaches by different researchers and people around the World. One approach is to measure the “Mu Rhythms”, or also known as “Mu Waves” from the sensorimotor area of one’s brain by registering an EEG signal. The Mu Waves are associated with the movement of the body –…