The Neurorobotics research group at the Department of Mechatronics Engineering, Air University has been working on various research issues related to brain-machine interface, brain-robot interface, bio-robotics, biomedical engineering, artificial intelligence, pattern recognition and classification techniques. The group is focusing on real time brain signal acquisition for brain-machine interfacing using Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS).
BRAIN COMPUTER INTERFACE
Brain-Computer Interface (BCI) is a direct communication/control pathway between brain and external devices by bypassing the peripheral nervous system. Methods used to acquire brain signals for BCI purposes can be invasive or noninvasive. Our group is carrying out research using noninvasive techniques for example, Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), to develop a real-time BCI for multidimensional control of external devices.
ABOUT BRAIN SIGNALS
The brain signals are acquired using a noninvasive technique such as fNIRS or EEG, the signals acquired are pre-processed using suitable adaptive filters to remove high or low frequency components such as due to heart beat, Mayer waves and respiration. Features are then extracted for classification and a suitable machine learning algorithm is designed to classification those features. Finally, control commands for the control of an external device (Spelling devices, Robotics arms or wheelchair etc.) are generated.