Our Research Focus Areas

Brain-Computer Interface (BCI)

The goal of Brain-Computer Interface (BCI) is to give severely paralyzed people (say: locked in or affected by stroke) a way to communicate without depending on muscle control. BCI combines hardware, cognitive paradigm and machine learning algorithms to enable communication using brain signals. In recent years, with the availability of affordable BCI devices considerable interest in gaming/entertainment applications and monitoring of daily activities for healthy users has gained importance. We have realized a working P300 Brain Computer system (as below) which can effectively spell letters from electroencephalogram signals. Neural Engineering Lab @ IITG is working towards complete mobility and usage of BCI for out of lab scenarios.

Interested! See the demo video

Multivariate/Multimodal Algorithms for NeuroImaging Big Data

Brain function/structure measurements are rapidly improving due to the advancements in neuroimaging technologies. However, despite these improvements it is becoming increasingly necessary to make sense of the obtained high dimensional datasets which qualify to be called “big data”. Both univariate and multivariate methods have been popular in neuroimaging. Neural Engineering Lab @ IITG is developing novel algorithms to make sense of this high dimensional big neuroimaging datasets.

Click to know more