Project
Proposal
EEG Based action classification
Pratyush Sinha
Mentor: Dr. Amitabha Mukherjee
Introduction:
Cognition depends on neural activity. To
study cognition, we need a way to study the neural activity. Electroencephalograms
or EEGs are electrical signals created due to the activity of neurons in the
brain. These can be recorded non-invasively from outside the scalp. EEG is an important
tool in the diagnosis of functional brain disorders, and in sleep
and epilepsy research.
EEG are complex
spatiotemporal signals. Their statistical properties depend on the state of the
subject and on external factors. Sensory stimuli, cognitive tasks, motor tasks
etc induce changes in the EEG activity. These may either be an increase in the
power corresponding to a certain frequency band known as event-related
synchronization (ERS) or the decrease in the power corresponding to certain
frequency band known as event-related desynchronization
(ERD).
Figure-1 Running power spectra computed for three
frequency bands of an EEG recording.
Taken from : http://cognet.mit.edu/library/erefs/arbib/images/figures/A076_fig002.gif
Motivation:
EEG signals can be analysed to discriminate
between different actions or imaginations. As shown by Pfurtscheller et al. 1997, EEG signals can be used to classify
the imagination of motor actions by left and right hands. I plan to do
something similar.
Proposed Methodology:
I plan to use a free online database (such as the
one available at Physionet). The database contains recordings of EEG
signals corresponding to motor actions and their imaginations for both the left
and the right hands.
I will do an ERD/ERS analysis of the signals for
various frequency bands. I will also try to find if such a characteristic is
invariant across subjects using statistical correlation.
Further possible work:
The
project can be extended to analyse motor imaginations with more than 2 possible
outputs (Ex- motion in 2D). van Gervan et al. 2009 have
tried to do something similar.
References:
2. Event-Related
Potential – Steven L. Bressler
3. EEG-based
discrimination between imagination of right and left hand movement
4.
Physionet
(G. Pfurtscheller, Ch. Neuper,
D. Flotzinger, M. Pregenzer)
5.
Attention
modulations of posterior alpha as a control signal for two-dimensional
brain–computer interfaces (Marcel van Gerven, Ole
Jensen)