We are overwhelmed in all humbleness and gratefulness to
acknowledge our depth to all those who have helped us to put these
ideas, well above the level of simplicity and into something concrete.
We would like to express our special thanks of gratitude to our teacher
Mrs. Bindu Manojkumar as well as the organizers of the competition for
giving us the golden opportunity to do this wonderful project on the
topic “Brain-Computer Interface" , which also helped us in doing a lot of
Research and we came to know about so many new things. We am
really thankful to them. Any attempt at any level can 't be satisfactorily
completed without the support and guidance of our parents, friends and
the school. We would like to thank everyone who helped us a lot in
gathering different information, collecting data and guiding us from time
to time in making this project , despite of their busy schedules ,they
gave us different ideas in making this project unique,
S.no Topic Page
1 Introduction 4
2 What is a Brain-Computer Interface? 5
3 How Does it Work? 6
4 Applications 7,8
5 Amyotrophic lateral sclerosis 9
6 Disabled people 10
7 Gaming 11
8 Neurogaming 12
9 Prosthesis 13,14
10 Vision 15
11 BCIs and Brain training 15
12 BCI Devices 16
13 Our Model(Invasive) 17,18
14 The End 19
For generations, humans have fantasized about the ability to communicate
and interact with machines through thought alone or to create devices that
can peer into person's mind and thoughts. These ideas have captured the
imagination of humankind in the form of ancient myths and modern
science fiction stories. However, it is only recently that advances in
cognitive neuroscience and brain imaging technologies have started to
provide us with the ability to interface directly with the human brain. This
ability is made possible through the use of sensors that can monitor some
of the physical processes that occur within the brain that correspond with
certain forms of thought.
What is a Brain-Computer
•A brain–computer interface (BCI), often called a mind-machine
interface (MMI), or sometimes called a direct neural
interface (DNI), synthetic telepathy interface (STI) or a brain–machine
interface(BMI), is a direct communication pathway between the brain and
an external device. BCIs are often directed at assisting, augmenting, or
repairing human cognitive or sensory-motor functions.
•Research on BCIs began in the 1970s at the University of California Los
Angeles (UCLA) under a grant from the National Science Foundation,
followed by a contract from DARPA. The papers published after this
research also mark the first appearance of the expression brain–computer
interface in scientific literature.
How Does it Work?
• Any natural form of communication or control requires peripheral nerves and muscles.
The process begins with the user’s intent. This intent triggers a complex process in
which certain brain areas are activated, and hence signals are sent via the peripheral
nervous system (specifically, the motor pathways) to the corresponding muscles, which
in turn perform the movement necessary for the communication or control task. The
activity resulting from this process is often called motor output or efferent output.
• Efferent means conveying impulses from the central to the peripheral nervous system
and further to an effector (muscle). Afferent, in contrast, describes communication in
the other direction, from the sensory receptors to the central nervous system. For
motion control, the motor (efferent) pathway is essential. The sensory (afferent) pathway
is particularly important for learning motor skills and dexterous tasks, such as typing or
playing a musical instrument.
• A BCI offers an alternative to natural communication and control. A BCI is an artificial
system that bypasses the body’s normal efferent pathways, which are the
neuromuscular output channels . Figure below illustrates this functionality Instead of
depending on peripheral nerves and muscles, a BCI directly measures brain activity
associated with the user’s intent and translates the recorded brain activity into
corresponding control signals for BCI applications. This translation involves signal
processing and pattern recognition, which is typically done by a computer. Since the
measured activity originates directly from the brain and not from the peripheral systems
or muscles, the system is called a Brain–Computer Interface.
• A BCI must have four components.
I. It must record activity directly from the brain (invasively or non-invasively).
II. It must provide feedback to the user.
III. It must do so in realtime.
IV. Finally, the system must rely on intentional control. That is, the user must choose to
perform a mental task whenever s/he wants to accomplish a goal with the BCI.
• Devices that only passively detect changes in brain activity that occur without any
intent, such as EEG activity associated with workload, arousal, or sleep, are not BCIs.
They are, as already described in the definitions above, direct artificial
output channels from the brain. Unlike other human–computer interfaces,
which require muscle activity, BCIs provide “non-muscular”
communication. One of the most important reasons that this is significant
is that current BCI systems aim to provide assistive devices for people
with severe disabilities that can render people unable to perform physical
movements. Radiation accidents like the one in the Star Trek episode
described above are unlikely today, but some diseases can actually lead
to the locked-in syndrome. Other applications include Interaction with
Virtual reality environment, Gaming, Controlling machines, Controlling a
Prosthesis and in everyday applications.
•Amyotrophic lateral sclerosis (ALS) is an example of such a disease. The
exact cause of ALS is unknown, and there is no cure. ALS starts with muscle
weakness and atrophy. Usually, all voluntary movement, such as walking,
speaking, swallowing, and breathing, deteriorates over several years, and
eventually is lost completely.
• The disease, however, does not affect cognitive functions or sensations.
People can still see, hear, and understand what is happening around them,
but cannot control their muscles. This is because ALS only affects special
neurons, the large alpha motor neurons, which are an integral part of the
motor pathways. Death is usually caused by failure of the respiratory
•Life-sustaining measures such as artificial respiration and artificial nutrition
can considerably prolong the life expectancy. However, this leads to life in
the lockedin state. Once the motor pathway is lost, any natural way of
communication with the environment is lost as well. BCIs offer the only
option for communication in such cases.
• The semi-autonomous wheelchair Rolland III can deal with different input modalities, such
as low-level joystick control or high-level discrete control. Autonomous and semi-
autonomous navigation is supported. The rehabilitation robot FRIEND II (Functional Robot
Arm with User Friendly Interface for disabled People) is a semiautonomous system designed
to assist disabled people in activities of daily living.
• It is system based on a conventional wheelchair equipped with a stereo camera system, a
robot arm with 7 degrees-of-freedom, a gripper with force/torque sensor, a smart tray with
tactile surface and weight sensors, and a computing unit consisting of three independent
• FRIEND II can perform certain operations completely autonomously. An example of such
an operation is a “pour in beverage” scenario. In this scenario, the system detects the bottle
and the glass (both located at arbitrary positions on the tray), grabs the bottle, moves the
bottle to the glass while automatically avoiding any obstacles on the tray, fills the glass with
liquid from the bottle while avoiding pouring too much, and finally puts the bottle back in
its original position – again avoiding any possible collisions.
•Currently, there is a new field of gaming called Neurogaming, which uses non-
invasive BCI in order to improve gameplay so that users can interact with a
console without the use of a traditional controller. Some Neurogaming software
use a player's brain waves, heart rate, expressions, pupil dilation, and even
emotions to complete tasks or effect the mood of the game. For example, game
developers at Emotiv have created non-invasive BCI that will determine the
mood of a player and adjust music or scenery accordingly. This new form of
interaction between player and software will enable a player to have a more
realistic gaming experience. Because there will be less disconnect between a
player and console, Neurogaming will allow individuals to utilize their
"psychological state"] and have their reactions transfer to games in real-time.
•However, since Neurogaming is still in its first stages, not much is written
about the new industry. The first NeuroGaming Conference was held in San
Francisco on May 1–2, 2013.
• Motor Imagery - Motor imagery involves the imagination of the movement of various body
parts resulting in sensorimotor cortex activation, which modulates sensorimotor oscillations
in the EEG. This can be detected by the BCI to infer a user’s intent.
• Bio/Neurofeedback for Passive BCI Designs - Biofeedback is used to monitor a subject’s
mental relaxation. In some cases, biofeedback does not monitor electroencephalography
(EEG), but instead bodily parameters such as electromyography(EMG), galvanic skin
resistance (GSR), and heart rate variability (HRV).Many biofeedback systems are used to
treat certain disorders such as attention deficit hyperactivity disorder (ADHD), sleep
problems in children, teeth grinding, and chronic pain.
• Visual Evoked Potential (VEP) - A VEP is an electrical potential recorded after a subject is
presented with a type of visual stimuli. There are several types of VEPs. Steady-state visually
evoked potentials (SSVEPs) use potentials generated by exciting the retina, using visual
stimuli modulated at certain frequencies. SSVEP’s stimuli are often formed from alternating
checkerboard patterns and at times simply use flashing images .
•In fact, several approaches have been investigated to control prostheses with
invasive and non-invasive BCIs .Ideally, the control of prostheses should
provide highly reliable, intuitive, simultaneous, and proportional control of
many degrees-of-freedom. In order to provide sufficient flexibility, low-level
control is required. Proportional control in this case means the user can
modulate speed and force of the actuators in the prosthesis. “Simultaneous”
means that several degrees-of-freedom (joints) can be controlled at the same
time. That is, for instance, the prosthetic hand can be closed while the wrist of
the hand is rotated at the same time. “Intuitive” means that learning to control
the prosthesis should be easy. Non-invasive approaches suffer from limited
bandwidth, and will not be able to provide complex, high-bandwidth control in
the near future. Invasive approaches show considerable more promise for such
control in the near future. However, then these approaches will need to
demonstrate that they have clear advantages over other methodologies such as
myoelectric control combined with targeted muscle reinnervation (TMR).
•Non-invasive BCIs have also been applied to enable brain-control of prosthetic
upper and lower extremity devices in people with paralysis. For example, Gert
Pfurtscheller of Graz University of Technology and colleagues demonstrated a
BCI-controlled functional electrical stimulation system to restore upper
extremity movements in a person with tetraplegia due to spinal cord
injury. Between 2012 and 2013, researchers at the University of California,
Irvine demonstrated for the first time that it is possible to use BCI technology to
restore brain-controlled walking after spinal cord injury. In their study, a person
with paraplegia due to spinal cord injury was able to operate a BCI-robotic gait
orthosis to regain basic brain-controlled ambulation.
Invasive BCI research has targeted repairing damaged sight and providing
new functionality for people with paralysis. Invasive BCIs are implanted
directly into the grey matter of the brain during neurosurgery. Because they
lie in the grey matter, invasive devices produce the highest quality signals
of BCI devices but are prone to scar-tissue build-up, causing the signal to
become weaker, or even non-existent, as the body reacts to a foreign object
in the brain.
A brain-computer interface is a direct communication pathway between the
brain and an external device with the purpose of assisting, augmenting, or
repairing cognitive and/or motor functions. The computer measures electrical
activity in the brain by means of an electroencephalogram (EEG) and interprets
the signals for display. All of us produce a variety of electrical wave patterns
that reflect what our brain is doing at any given time. These patterns can be
compared to age-matched reference databases and/or to pre-treatment
measurements of an individual to identify dysfunctional networks.
Brain training is the use of a brain-computer interface to learn to treat the
dysfunctional networks and re-regulate cognitive and mental
functioning. Through brain training, the individual can learn to control the
specific dysfunctional network, essentially teaching the brain to function more
BCIs and Brain