Our main research goal is to develop advanced machine learning algorithms to analyze and interpret neural signals such as EEG, EMG, and fNIRS. Our objective is to gain a better understanding of neural activity and its implications. This understanding is key to creating new, non-invasive methods for recording and interpreting brain activity, particularly in the improvement of brain-computer/machine interface technology.
We use a multidisciplinary approach combining robotics, computer science, neuroscience, and psychology. Our research could benefit assistive technologies, virtual reality, gaming interfaces, medical diagnostics, therapeutics, and cognitive enhancement tools. The multidisciplinary approach pushes technological boundaries and contributes to sectors that can benefit from enhanced brain understanding and interfacing.
For more information or if you are interested in joining our team, please contact us at [email protected].
A Motor Imagery Brain-Computer Interface to control a computer cursor through brain signals derived from imagining motor movements.
https://www.youtube.com/watch?v=4eJlkvwNT2U
A Motor Imagery Brain-Computer Interface to control a computer a robotic manipulator
https://youtu.be/MeZ9Orcptkc?si=T2RSGH2xTrRDWZY2