Download BRAIN COMPUTER INTERFACING ARMY RESCUE USING

BRAIN COMPUTER INTERFACING ARMY RESCUE USING
SYNTHETIC TELEPATHY THROUGH NEURAL ELECTRONICS
Manoj.N & Venkata Pavan Kumar.M
Department Of Electronics and Communication Engineering
[email protected]&[email protected]
Abstract
“I will keep the lamp of knowledge burning to
achieve the vision”
The
technology
is
constantly
attaining
improvisations at ever twinkling of eye. Yesterday
updates become tomorrow outdates. Ever evolving
technology has led to exponential changes in the
world of ‘science’.
In this paper, we the emerging engineers of the core
“Electronics & Communication branch” have
indulged in the analysis of “Brain computer
interfaced army rescue using synthetic telepathy
through neural electronics”.
Brain computer interfacing is a fascinating
technology where we employ wonders converting
thoughts to actions and other side hijacking of
Indian army by enemies is a serious threat
prevailing in our country. Technology has always
solutions to all problems. So, we have incorporated
BCI technology using synthetic telepathy exploiting
the exclusive alpha and beta waves generated at
thoughts by the neurons of the brain through
neural electronics in our army rescue.
I.INTRODUCTION:
In this paper, we have said
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
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
What is mind uploading and brainwaves
involved.
Our proposed exploitation of neurotic
elements to process able waveforms.
Inputting hijacked army’s thoughts through
EPOC headset.
Brain computer interfacing and conversion
of thoughts to binary data and consequent
rescue actions.
A. Mind uploading:
Mind uploading or whole brain emulation
(sometimes called mind transfer) is the hypothetical
process of scanning and mapping a biological brain
in detail and copying its state into a computer system
or another computational device. The computer
would have to run a simulation model so faithful to
the original that it would behave in essentially the
same way as the original brain, or for all practical
purposes, indistinguishably. The simulated mind is
assumed to be part of a virtual reality simulated
world, supported by an anatomic 3D body simulation
model. Alternatively, the simulated mind could be
assumed to reside in a computer inside (or connected
to) a humanoid robot or a biological body, replacing
its brain.
II.BRAINWAVES:
There are several types of brainwave states. It is
completely natural biological occurrence in every
human being. Our brain does not operate in only one
brainwave state at a time but instead pulses in these
entire brainwave states simultaneously, with one of
the states being dominant at any given time. The
dominant state indicates you’re "state of mind" or
level of consciousness. Because different areas of the
brain may have different activity at any given time,
you may have activity in one brainwave state in one
area of the brain while at the same time a different
brainwave state may be more active in another area
of the brain.
A. Alpha Waves:
Frequency: 8 to 12 Hz
Location: Posterior Regions of Head, Both Sides,
Higher in Amplitude on Dominion side. Central Sites
(C3-C4) At Rest
Normally: Relaxed/Reflecting, Closing The Eyes,
Also Associated With Inhibition
Control,
Seemingly With The Purpose Of Timing Inhibitory
Activity In Different Locations Across The
Brain
Wave pattern:
(It Emerges With Closing of the Eyes and With
Relaxation, and Attenuates With Eye Opening Or
Mental Exertion. The Posterior Basic Rhythm is
Actually Slower than 8 Hz in Young Children)
B. Beta Waves:
Frequency: 12 – 30Hz
Location: Both Sides, Symmetrical
Distribution, Most Evident Frontally; Low
Amplitude Waves
: Alert/Working, Active, Busy
or Anxious Thinking, Active Concentration
Normally
Wave Pattern:
(Beta activity is closely linked to motor behaviour
and is generally attenuated during active movements)
Our proposed exploitation of
neurons to neuroelectronics we have proposed to
exploit the neural reactions taking place in brain by
capturing the waves generated through a headset and
process them further by amplifying them and feed
them to computer and take necessary steps to be
performed what we have thought. Here we have
dedicated our project to our brave Indian army who
when caught in an unavoidable danger when captured
by the enemy could possibly send signaling waves as
thoughts to alert the head system to actively
participate at their rescue.
III.NUERAL NETWORK:
Simple artificial neural network
The human brain contains about 100 billion nerve
cells called neurons, each individually linked to other
neurons by way of connectors called axons and
dendrites. Signals at the junctures (synapses) of these
connections are transmitted by the release and
detection of chemicals known as neurotransmitters.
The established neuro scientific consensus is that the
human mind is largely an emergent property of the
information processing of this neural network.
"Consciousness is part of the natural world. It
depends, we believe, only on mathematics and logic
and on the imperfectly known laws of physics,
chemistry, and biology; it does not arise from some
magical or otherworldly quality."
The concept of mind uploading is based on this
mechanistic view of the mind, and denies the vitalise
view of human life and consciousness.
Many
eminent
computer
scientists
and
neuroscientists have predicted that computers will be
capable of thought and even attain consciousness
However, even though uploading is dependent upon
such a general capability it is conceptually distinct
from general forms of AI in that it results from
dynamic reanimation of information derived from a
specific human mind so that the mind retains a sense
of historical identity (other forms are possible but
would compromise or eliminate the life-extension
feature generally associated with uploading). The
transferred and reanimated information would
become a form of artificial intelligence, sometimes
called an info morph or "no morph."
IV.THEORETICAL BENEFITS:
A.
Immortality/Backup:
In theory, if the information and processes of the
mind can be disassociated from the biological
body, they are no longer tied to the individual
limits and lifespan of that body. Furthermore,
information within a brain could be partly or
wholly copied or transferred to one or more
other substrates (including digital storage or
another brain), thereby reducing or eliminating
mortality risk.
B.
Speedup:
A computer-based intelligence such as an upload
could potentially think much faster than a human
even if it were no more intelligent. Human neurons
exchange electrochemical signals with a maximum
speed of about 150 meters per second, whereas the
speed of light is about 300 million meters per second,
about two million times faster. Also, neurons can
generate a maximum of about 200 to 1000 action
potentials or "spikes" per second, whereas the
number of signals per second in modern computer
chips is about 2 GHz and expected to increase by at
least a factor 100.
However, in practice this massively parallel
implementation
would
require
separate
computational units for each of the hundred billion
neurons and each of the hundred trillion synapses.
That requires an enormously large computer or
artificial neural network in comparison with today's
super-computers. In a less futuristic implementation,
time-sharing would allow several neurons to be
emulated sequentially by the same computational
unit. Thus the size of the computer would be
restricted, but the speedup would be lower.
(Simple neuron model: Black-box dynamic nonlinear signal processing system)
Scanning and mapping scale of an individual:
database showing the connections between the
neurons must be extracted from an anatomic model
of the brain. This network map should show the
connectivity of the whole nervous system, including
the spinal cord, sensory receptors, and muscle cells.
Destructive scanning of the human brain including
synaptic details is possible as of end of 2010. A full
brain map should also reflect the synaptic strength of
each connection. It is unclear if the current
technology allows that.
It is proposed that short-term memory and working
memory is prolonged or repeated firing of neurons, as
well as intra-neural dynamic processes. Since the
electrical and chemical signal state of the synapses
and neurons may be hard to extract, the uploading
might result in that the uploaded mind perceives a
memory loss of the events immediately before the
time of brain scanning.
A full brain map would occupy less than 2 x 1016
bytes and would store the addresses of the connected
neurons, the synapse type and the synapse "weight"
for each of the brains' 1015 synapses.
C.
Serial sectioning:
A possible method for mind uploading is serial
sectioning, in which the brain tissue and perhaps
other parts of the nervous system are frozen and then
scanned and analysed layer by layer, thus capturing
the structure of the neurons and their
interconnections.[19] The exposed surface of frozen
nerve tissue would be scanned and recorded, and then
the surface layer of tissue removed. While this would
be a very slow and labour intensive process, research
is currently underway to automate the collection and
microscopy of serial sections. The scans would then
be analysed, and a model of the neural net recreated
in the system that the mind was being uploaded into.
V.BRAINWAVE INFORMATION
CAPTURED BY EPOC HEADSET:
(T
he movement of positively-charged ions through the
ion channels controls the membrane electrical action
potential in an axon).
When modelling and simulating the brain of a
specific individual, a brain map or connectivity
perfected, this technology takes its cues from a
person’s thoughts, converting these signals into
digital information that a computer-game system can
use to play the game. The company behind this
method, emotiv systems users, what it calls the
brain/computer interface. Company information
states that the technology can recognize and use up to
30 different emotions, actions and expressions. These
are transferred to the character or object on the
screen.
Here our Emotiv System is going to claim the
headset which will make it possible for army
force to be controlled and influenced by the
soldier's mind, and facial expressions. It
connects wirelessly with our head PC which
would be signalled consequently.
Emotiv EPOC uses the human brain as a source
for creating movement in the operation. That’s
right; this system uses a headset that receives
brain waves. This technology can tell the game
system what you want to do within your virtual
world.
Inputs of the headset:
The EPOC has 14 electrodes. It has a two-axis gyro
for measuring head rotation.

Because the brain sends out a level of electrical
energy the correct technology certainly could use this
energy to power action operations. The knowledge of
brain waves and of energy that sends a signal from
one neuron to another is not new. Scientists and
doctors have used equipment to measure brain waves
for well over a century. It’s the basis of the
electroencephalogram .This technology is now being
adapted and applied to interactive gaming. The
Emotiv EPOC headset mimics in a way the EEG that
has electrodes/disks that pick up the brain activity.
The signals are sent through wires for amplification.
The foundation for using EEG technology in gaming
lies with trying to interpret a person’s thoughts based
on the brain wave signals being captured. Scientists
have found that brain activity corresponds to a
patient’s apparent state of mind and thought
processes. When measured, a person’s brain waves
have patterns that appear only with specific emotions
or thoughts.
With Emotiv EPOC seven pairs of electrodes are
used to capture the brain-wave signals. When
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Conscious thoughts (Cognitive suite):
Imagining 12 kinds of movement- those were in
the demo application 6 directions (left, right, up,
down, forward, and "zoom") and 6 rotations
([anti-]clockwise rotation, turn left and right, and
sway backward and forward)- plus 1 other
visualization ("disappear") that can be detected .
The Emotive guy used his heads to try and cue
himself to think the same way every time.
Emotions (Affective suite): "Excitement",
"Engagement/Boredom", "Meditation", and
"Frustration" can currently be measured.
Facial expressions (Expressive suite):
Individual eyelid and eyebrow positions, eye
position in the horizontal plane, smiling,
laughing, clenching, and smirking can currently
be detected. Other expressions may be added
prior to release. The expressions are detected by
the EEG sensors picking up signals to facial
muscles, rather than by reading brainwaves.
Unlike reading mental activity, these detections
are very fast (10ms) conveying a decisive
advantages.
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Based on the developments in neuro technology
Emotiv has revolutionary interface for humancomputer interaction. The Emotiv EPOC wireless
neuro headset captures, understand and processes the
thoughts in our brain to carry out actions on PC. The
real life application possibilities across army sides
such as immediate escape from enemies, automatic
plane control, especially in terrorist attack etc.
Emotiv is also actively involving the developer
community to create applications that can be
controlled by your mind. A brain–computer interface
(BCI) with wireless technology by effective headset,
sometimes called a direct neural interface or a brain–
machine interface, is a direct communication
pathway between a brain and an external device.
BCIs are often aimed at assisting, augmenting or
repairing human cognitive or sensory-motor
functions.
The Emotiv EPOC detects and processes real time
brain wave patterns using an EEG like device that
measures electrical activity in the brain. Through the
use of non-invasive sensors, the Emotiv EPOC
measures a wide range of thoughts and emotions.
Unlike earlier technologies which can only detect
basic and well-known mental states such as
‘concentration”,
Emotiv
can
simultaneously
differentiate between particular thoughts such as
‘push’ and ‘lift’ and emotions such as ‘excitement’ or
‘calmness’.
With technology in hand and a gaming audience in
mind, Emotiv Systems approached IDEO to create a
sleek and beautiful headset that could house the 16
sensors and the electronics to make the device’s 30+
detections a reality. With the goal of fitting 98% of
head sizes and hair styles, Emotiv Systems wanted a
clever mix of industrial design and engineering that
would result in a durable, easy-to-use product.
Referencing previous knowledge from head-centric
work, the IDEO team began by creating a number of
three-dimensional models. Challenged by the need to
have contact points in specific locations, designers
needed to make sure sensors were adjustable as well
as pliable.
The final headset relies on an established and familiar
headphone-like behavior to maintain pressure on the
scalp for the sensors to capture EEG signals. The
headset is molded from ABS plastic with soft rubber
accents to allow for proper fit and user customization.
Intuitive to use and durable enough for active gamers,
the headset is available in Emotiv’s signature orange
and white, or in a sleek black option. Inside the
headset, a unique EEG graphic reminds the user who
and what is making this headset actually work
Partially invasive BCI technologies are implanted
inside the skull but rest outside the brain rather than
within the grey matter. They produce better
resolution signals than non-invasive BCIs where the
bone tissue of the cranium deflects and deforms
signals and have a lower risk of forming scar-tissue
in the brain than fully-invasive BCIs.
Electro corticography (ECOG) measures the
electrical activity of the brain taken from Beneath the
skull in a similar way to non-invasive
electroencephalography, but the electrodes are
embedded in a thin plastic pad that is placed above
the cortex. Light Reactive Imaging BCI devices are
still in the realm of theory. These would involve
implanting a laser inside the skull. The laser would
be trained on a single neuron and the neuron's
reflectance measured by a separate sensor. When the
neuron fires, the laser light pattern and wavelengths it
reflects would change slightly. This would allow
researchers to monitor single neurons but require less
contact with tissue and reduce the risk of scar-tissue
build-up.
In EPOC headset, each electrode is connected to one
input of a differential amplifier; a common system
reference electrode is connected to the other input of
each differential amplifier. These amplifiers amplify
the voltage between the active electrode and the
reference. In analog EEG, the signal is output as the
deflection of pens as paper passes underneath. Most
EEG systems these days, however, are digital, and
the amplified signal is digitalized via an analog-todigital converter, after being passed through an antialiasing filter.
The digital EEG signal is stored electronically and
can be filtered for display. Typical settings for the
high-pass filter and a low-pass filter are 0.5-1Hz and
35-70Hz, respectively. The high-pass filter typically
out slow artifact, such as electro galvanic signals and
movement artifact, whereas the low-pass filter filters
out
high
frequency
artifacts,
such
as
electromyography signals. An additional notch filter
is typically used to remove artifact caused by
electrical power lines. Thus this processed waveform
interfaces are efficiently transported via any recent
wireless technologies transported via any recent
wireless technologies like wi-fi or wimax to our
destination PC and from there rescue actions can be
made which have to be pre-recorded there.
VI .CONCLUSION:
Thus our brain computer interfaced army rescue
project using synthetic telepathy through neural
electronics could possibly bring revolution in the
army rescue pattern and save a huge amount
spending every fiscal year there. These further
guarantees efficient rescue schema and can be
upgraded to the latest trend.
VII.REFERENCES:
Book: How brain waves and neurons interact? ----Dr. Rycharde Manne.
Kay KN, Naselaris T, Prenger RJ, Gallant JL (March
2010). "Identifying natural images from human brain
activity". Nature 452 (7185): 352–5.
Goertzel, Ben (Dec 2009). "Human-level artificial
general intelligence and the possibility of a
technological singularity: a reaction to Ray
Kurzweil's The Singularity Is Near, and McDermott's
critique of Kurzweil". Artificial Intelligence 171 (18,
Special Review Issue): 1161–1173.
doi:10.1016/j.artint.2007.10.011.
http://scholar.google.com/scholar?hl=sv&lr=&cluster
=15189798216526465792.