A Brain–Computer Interface (BCI) sometimes called a direct neural interface is a direct technological interface between a brain and a computer. It is a system that uses electric, magnetic or hemodynamic brain signals to control external devices such as switches, wheel chairs, computers or neuroprosthesis. BCI systems are especially invaluable for patients who suffer from severe motor impairments (late stage of Amyotrophic Lateral Sclerosis – ALS, severe cerebral palsy, head trauma, and spinal injuries).
Due to the advancement of modern medical sciences, people with severe paralysis can now live a long life. Although their minds function perfectly, some may not even be able move a single muscle in the body to communicate with outside world. A Brain Computer Interface (BCI) system would enable these severely physical disable people to communicate with outside world via computer voice in his or her native language (in Sinhala, Tamil or English) and / or control equipment such as wheel chairs and televisions. These types of communicating abilities could greatly improve the quality of their lives.
Aim of the BCI group is three fold.
To identify new mental activities that can alter electroencephalogram (EEG) signals up to a level where it can be detected by signal processing methods.
to develop new methods to improve the detection and decoding of brain signals acquired by EEG
to design and construct low cost hardware and software for BCI to be used in Sri Lanka
The Low cost 8 channel EEG/EOG (Electrooculogram) /EMG (Electromylogram) amplifier which has been constructed in our laboratory was later modified to be used with Real Time Brain Computer system (Figure 1).
A complete software package for recording EEG, EMG and EOG signals from this amplifier was developed. Further, an EEG based Brain computer interface system (named GENIE) was constructed to accept and classify signals from subjects in real time.
IMTE can be used to carry out signal processing and classifications of EEG data. IMTE has a Graphical User Interface (GUI) with user friendly features and supports various signal processing techniques.
The research assistant in the BCI research project obtained an MPhil degree from Postgraduate Institute of Science at University of Peradeniya.
Asiri Nanayakkara and Zahmeeth Sakkaff, ‘Fixed distance neighbor classifiers in Brain Computer Interface systems’ Journal of National Science Foundation, Sri Lanka 40, 195 (2012)
Zahmeeth Sakkaff and Asiri Nanayakkara, ‘New set of cognitive tasks in EEG based Brain Computer Interface’ 2010 5th IEEE International Conference on Information and Automation for Sustainability, ICIAfS 2010, pp. 87-90 (Received the best paper award in the area of machine learning)
Asiri Nanayakkara and Zahmeeth Sakkaff ‘Automated dimensionality reduction in EEG based Brain Computer Interface’ 2010 5th IEEE International Conference on Information and Automation for Sustainability, ICIAfS 2010, pp. 70-74
Zahmeeth Sakkaff and Asiri Nanayakkara , ‘Comparison of new mental tasks with Imaginary motor movements in EEG based Brain Computer Interface (BCI)’ Proceedings of the Technical Sessions, 26 (2010) Institute of Physics Sri Lanka
Zahmeeth Sakkaff and Asiri Nanayakkara, ‘Removal of ocular artifacts from EEG signals in Brain Computer Interface’, Proceedings of the Technical Sessions, 24 (2008) 51-57 Institute of Physics Sri Lanka
Registered for M.Phil Degree in Electronics
Mr. D.M.V.Y.S. Bandara