Download Brain Computer Interface - Department of Electrical, Computer and

Non-Invasive BCI
1929
 Hans Berger – Discovered the EEG
 Electroencephalograph –
 Signal Reflecting the electrical field produced by trillions
of individual synaptic connections in the cortex and
subcortical structures of the brain
EEG
EEG
EEG
 Niels Birbaumer –
 Trained severely paralyzed people to self-regulate the slow
cortical potentials in their EEG in such a way that these
signals could be used as a binary signal to control a
computer cursor (1990s)
 Tests included writing characters with the cursor
 System users require training just as any person is trained
to use a keyboard or a computer
Those who depend
ALS
 Amyotrophic Lateral sclerosis –
 Muscle weakness and atrophy throughout the body caused
by the degeneration of upper and lower motor neurons.
 Individuals may ultimately lose ability to initiate and
control all voluntary movement
 For the most part, cognitive function is preserved
 Sensory nerves and the autonomic nervous system are
generally unaffected
ALS
 BCI systems have the ability to allow a paralyzed,
“locked-in” patient to communicate words, letters and
simple commands to a computer interface that
recognizes different outputs of EEG signals and
translates them through use of assigned algorithms into
a specific function or computing output that the user
has the ability to control.
 A complex mechanical BCI system would allow a user to
control an external system possibly an artificial limb by
creating an output of specific EEG frequency
P300 Speller
 User observes 6x6 matrix where each cell contains a
character or symbol
 User receives stimuli that coordinate with a specific
output
 User learns to recognize certain stimuli that exist in
relation to a specific output
 System created successful feedback when tested among
the ALS population
EEG Rhythms
 For analyzing EEG signals, studies suggest that
frequencies of 8-12 Hz (mu) and 13-28 Hz (Beta) are
most sensible for human control
 The form or magnitude of a voltage change evoked by a
stereotyped stimulus is known as an evoked potential
and can serve as a command
 ie. The amplitude of the EEG in a particular frequency
band, can be used to control movement of a cursor on a
computer screen
Non-Invasive BCI
 Forefront of human experimentation
 Cost effective
 No implantation
 Susceptible to noise
 Cranial barrier dampens signal
What about right now
 Today, BCIs are already being incorporated into modern
technologically dependent society
As they were once thought to be strictly
a bridge between a neurologically
disconnected brain to an outside mechanism
of replacing neuromuscular function,
the commercial exploitations have already
begun as devices can now be purchased that
allow users to control an exterior system
and navigate and control a graphical
Interface using only EEG output signals
NeuroSky
 Developers at NeuroSky created the Brainwave, a
comprehensive non-invasive BCI that connects the user
to iOS and Android platforms, and transfers all signal
information through Bluetooth as opposed to radio.
 The EEG outputs for this setup are controlled primarily
by variations in brain-state. In order to achieve a
specific level of EEG the user may be prompted to relax
or improve focus, thus altering the specific output of
brain energy and ultimately changing the level of
expressed EEG signals
Emotiv
 Devolped a BCI called the EPOC
 16 sensors capture EEGs to the extent of which the
system can return feedback to let the user know
whether or not they blinked, or sneezed, or smiled
 The device allows a user to connect to a computer, and
perform all basic functions that they otherwise would
control using a keyboard, but with the mind. That
includes control of gaming platforms as well
Future
 For the future, BCI technology seems very applicable in
a wide variety of areas whether it be medically or
commercially
 The possibilities of how far the systems can go is
virtually limitless
 Control of subvocalization and more advanced EEG
processing could lead to telepathic communication and
active learning mechanisms
 This all would bring up an unfeasible amount of ethical
discomfort and confrontation
Bibliography

Curran , E., & Stokes , M. (2002). Learning to control brain activity: A review of the production and control of eeg components for driving
brain-computer interface systems . Academic Press , Retrieved from http://hossein69.persiangig.com/.uZ900jjmWN/sdarticle.pdf

Wikipedia: Biomedical Engineering <en.wikipedia.org/wiki/ Biomedical_engineering>.

"Disruptions: Brain Computer Interfaces Inch Closer to Mainstream." Bits Disruptions Brain Computer Interfaces Inch Closer to Mainstream
Comments. N.p., n.d. Web. 23 Sept. 2013."Brain–computer Interface." Wikipedia. Wikimedia Foundation, 21 Sept. 2013. Web. 23 Sept.
2013.

Sellers , E. (2013 ). New horizons in brain computer interface research . U.S national library of medicine, Retrieved from
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3658460/

Naci , L., Cusack, R., Jia , V., & Owen, A. (2013). The brain's silent messenger: Using selective attention to decode human thought for
brain-based communication . The Journal of Neuroscience , Retrieved from http://www.cusacklab.org/downloads/nacietal_jon2013.pdf

Wolpaw , J., McFarland , D., & Vaughan, T. (2000). Brain-computer interface research at the wadsworth center . IEEE Transaction on
Rehabilitation Engineering , 8(2), 222-226. Retrieved from http://www.cs.hmc.edu/~keller/eeg/Wolpaw.pdf

Schalk, S., McFarland , D., Hinterberger, T., Birbaumer, N., & Wolpaw , J. (2004 ). Bci2000: A general-purpose brain-computer interface
(bci) system . IEEE Transactions on Biomedical Engineering , 51(6), 1034-1043. Retrieved from http://bpv-tese.googlecode.com/hghistory/095dce5394352001ef2ddaefe6f10678ca6413d5/src/referencias/10.1.1.115.7600.pdf

Heetderks , W., McFarland , D., Hinterberger, T., Birbaumer, N., Wolpaw , J., Peckham, P., Donchin, E., & Quatrano, L. (2000). Braincomputer interface technology: A review of the first international meeting . IEEE Transactions on Rehabilitation Engineering , 8(2), 164173. Retrieved from http://www.ocf.berkeley.edu/~anandk/neuro/BCI Overview.pdf