Done by

Jayanarayan

Jayakumar

Akshay

sudheeshRahul reji

Acknowledgement

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,

Team

Index

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

Introduction

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

Interface?

•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.

THE INFINITE POSSIBILITIES

Applications

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

•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

muscles.

•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.

disabled people

• 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

industrial PCs.

• 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.

Gaming

•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.

Neurogaming

•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 .

Prosthesis

• 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.

Prosthesis

VisionInvasive 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

efficiently

BCIs and Brain

training

BCI Devices

Our

Model(Invasive)

Our

Model(Invasive)