Brain-computer interface (BCI)
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Computer Science Clay
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Brain-computer interface (BCI)
is a collaboration between a brain and a device that enables signals from the brain to direct some external activity, such as control of a cursor or a prosthetic limb. The interface enables a direct communications pathway between the brain and the object to be controlled. In the case of cursor control, for example, the signal is transmitted directly from the brain to the mechanism directing the cursor, rather than taking the normal route through the body's neuromuscular system from the brain to the finger on a mouse.

By reading signals from an array of neurons and using computer chips and programs to translate the signals into action, BCI can enable a person suffering from paralysis to write a book or control a motorized wheelchair or prosthetic limb through thought alone. Current brain-interface devices require deliberate conscious thought; some future applications, such as prosthetic control, are likely to work effortlessly. One of the biggest challenges in developing BCI technology has been the development of electrode devices and/or surgical methods that are minimally invasive. In the traditional BCI model, the brain accepts an implanted mechanical device and controls the device as a natural part of its representation of the body. Much current research is focused on the potential on non-invasive BCI.

At the European Research and Innovation Exhibition in Paris in June 2006, American scientist Peter Brunner composed a message simply by concentrating on a display. Brunner wore a close-fitting (but completely external) cap fitted with a number of electrodes. Electroencephalographic (EEG) activity from Brunner's brain was picked up by the cap's electrodes and the information used, along with software, to identify specific letters or characters for the message.

The BCI Brunner demonstrated is based on a method called the Wadsworth system. Like other EEG-based BCI technologies, the Wadsworth system uses adaptive algorithm s and pattern-matching techniques to facilitate communication. Both user and software are expected to adapt and learn, making the process more efficient with practice.

During the presentation, a message was displayed from an American neurobiologist who uses the system to continue working, despite suffering from amyotrophic lateral sclerosis (Lou Gehrig's disease). Although the scientist can no longer move even his eyes, he was able to send the following e-mail message: "I am a neuroscientist wHo (sic) couldn't work without BCI. I am writing this with my EEG courtesy of the Wadsworth Center Brain-Computer Interface Research Program."
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i m yasmeen..
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1. Introduction
Man machine interface has been one of the growing fields of research and development in recent years. Most of the effort has been dedicated to the design of user- friendly or ergonomic systems by means of innovative interfaces such as voice recognition, virtual reality. A direct brain-computer interface would add a new dimension to man-machine interaction.
A brain-computer interface, sometimes called a direct neural interface or a brain machine interface, is a direct communication pathway between a human or animal brain(or brain cell culture) and an external device. In one BCIs, computers either accept commands from the brain or send signals to it but not both. Two way BCIs will allow brains and external devices to exchange information in both directions but have yet to be successfully implanted in animals or humans.
Brain-Computer interface is a staple of science fiction writing. In its earliest incarnations no mechanism was thought necessary, as the technology seemed so far fetched that no explanation was likely. As more became known about the brain however, the possibility has become more real and the science fiction more technically sophisticated. Recently, the cyberpunk movement has adopted the idea of 'jacking in', sliding 'biosoft' chips into slots implanted in the skull(Gibson, W.1984).Although such biosofts are still science fiction, there have been several recent steps toward interfacing the brain and computers.
In this definition, the word brain means the brain or nervous system of an organic life form rather than the mind. Computer means any processing or computational device, from simple circuits to silicon chips (including hypothetical future technologies like quantum computing).
Research on BCIs has been going on for more than 30 years but from the mid 1990’s there has been dramatic increase working experimental implants. The common thread throughout the research is the remarkable cortical-plasticity of the brain, which often adapts to BCIs treating prostheses controlled by implants and natural limbs. With recent advances in technology and knowledge, pioneering researches could now conceivably attempt to produce BCIs that augment human functions rather than simply restoring them, previously only the realm of science fiction
2. Working architecture
2.1. Introduction:

Before moving to real implications of BCI and its application let us first discuss the three types of BCI. These types are decided on the basis of the technique used for the interface. Each of these techniques has some advantages as well as some disadvantages. The three types of BCI are as follows with there features:
2.2. Invasive BCI:
Invasive BCI are directly implanted into the grey matter of the brain during neurosurgery. They produce the highest quality signals of BCI devices . Invasive BCIs has targeted repairing damaged sight and providing new functionality to paralyzed people. But these BCIs are prone to building up of scar-tissue which causes the signal to become weaker and even lost as body reacts to a foreign object in the brain.
2.3. Partially Invasive BCI:
Partially invasive BCI devices are implanted inside the skull but rest outside the brain rather than amidst 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.
Electrocorticography(ECoG) uses the same technology as non-invasive electro-encephalography, but the electrodes are embedded in a thin plastic pad that is placed above the cortex, beneath the dura mater. ECoG technologies were first trailed in humans in 2004 by Eric Leuthardt and Daniel Moran from Washington University in St Louis. In a later trial, the researchers enabled a teenage boy to play Space Invaders using his ECoG implant. This research indicates that it is difficult to produce kinematic BCI devices with more than one dimension of control using ECoG.
Light Reactive Imaging BCI devices are still in the realm of theory. These would involve implanting laser inside the skull. The laser would be trained on a single neuron and the neuron’s reflectance measured by a separate sensor. When 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.
2.4. Non-Invasive BCI :
As well as invasive experiments, there have also been experiments in humans using non-invasive neuroimaging technologies as interfaces. Signals recorded in this way have been used to power muscle implants and restore partial movement in an experimental volunteer. Although they are easy to wear, non-invasive implants produce poor signal resolution because the skull dampens signals, dispersing and blurring the electromagnetic waves created by the neurons. Although the waves can still be detected it is more difficult to determine the area of the brain that created them or the actions of individual neurons.
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send ppt and report of brain computer interface
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As the power of modern computers grows alongside our understanding of the human brain, we move ever closer to transforming some spectacular science fiction into reality. Imagine transmitting signals directly to someone's brain that would allow them to see, hear or feel specific sensory inputs. Consider the potential to manipulate computers or machinery with nothing more than a thought. It isn't just about convenience - for severely disabled people, development of a brain controlled interface or brain-computer interface (BCI) can easily be called the most important technological breakthrough in decades.

Some years ago, the lives of completely paralysed patients automatically ended due to the restricted (and in most cases, lack of) movement of the affected areas. Later, it was realized that as long as the parts of the brain controlling those affected areas weren’t damaged during the accident, the brain signals for those affected areas were still fully functional. This discovery opened up a world that had lived only in the minds of the science fiction dreamer, giving victims of debilitating injuries something to put their hopes on (Wolpaw et al., 2000).
This study has many statements as described by the different groups of scientists who embarked on this study but the summary of them all is:
“To create a union between the human body and the computer that will herald mankind to a higher level of living and give him a better understanding of himself”.
The human body is one of the most complex (if not the most complex) entities and has been a well-researched topic. This study is geared towards creating a feasible relationship between the human body and a computer system which will, of course, make human living a lot more comfortable and sophisticated.
This study has many significances but the most significant of these significances is the medical aspect, which entails controlling a device e.g. computer, wheelchair or a neuroprothesis by human intention which does not depend on the brain’s normal output pathways of peripheral nerves and muscles (Wolpaw et al., 2000).
1. The equipments needed are expensive, with the cheapest as expensive as $5,145 (which is approximately equivalent to N771, 750).
2. In the case where a device (even one as tiny as a logic gate) is been implanted on the brain, the medical procedure is very delicate and complications can arise practically from nowhere in the twinkle of an eye.
3. Lack of awareness and fear of its long-term effects have discouraged a lot of patients from becoming willing ‘guinea pigs’,
4. Specialists that are experienced enough to carry out the necessary operations are few due to the fact that this study is still being researched.
5. There are about 100billion neurons in a human brain. Each neuron is constantly sending & receiving signals through a WEB of connections. This makes designing a device as seemingly simple as an arm having grippers (in place of fingers) difficult.
Fig, 1: Grippers attached to a prosthetic arm
6. EEG measure tiny voltage potentials, and sometimes a simple as the blinking eyelids of the subject can generate much stronger signals than can be read by the EEG.
7. Some brain controlled interfaces still require a wired connection to the equipment, & those that are wireless require the subject to carry a computer that can weigh around 10pounds.
A typical brain controlled interface is

In 1848, Duboi-Reymond reported the presence of electrical signals in the human brain. Research on this led to Caton’s discovery in 1875 that “feeble” currents can be measured on the scalp. In 1924, Mr Hans Berger discovered the EEG ( ), a device that theoretically measured electrical signals. However, this wasn’t proven until 1929 by Berger. He analysed the interrelation of EEG and brain diseases
o Berger (1929) measured electrical signals with EEG
o 1930-50s EEG used in psychiatric and neurological sciences relying on visual inspection of EEG patterns
o 1960s-70s witness emergence of Quantitative EEG and confirmation of hemispheric specialization, e.g., left brain verbal and right brain spatial.
o 1980s+ observation of biofeedback
• 1970: First developments to use brain waves as input
• ARPA has vision of enhanced human
First step in the right direction
• 1990: First successful experiments with monkeys
• Implanting electrode arrays into monkey brains
• Recording of monkeys‘ brain waves
• 2000: Monkeys control robots by thoughts
• More non-invasive than invasive approaches
• Brain reading by eg. EEG, MEG or fMRI
• 2004: First human benefits from research
Early research used monkeys with implanted electrodes. The monkeys used a joystick to control a robotic arm. Scientists measured the signals coming from the electrodes. Eventually, they changed the controls so that the robotic arm was being controlled only by the signals coming from the electrodes, not the joystick. By 2000, the group succeeded in building a BCI that reproduced owl monkey movements while the monkey operated a joystick or reached for food.
In May 2008 photographs that showed a monkey operating a robotic arm with its mind at the Pittsburgh University Medical Centre were published in a number of well known science journals and magazines.
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A brain-machine interface is a communication system that does not depend on the brains normal output pathways of peripheral nerves and muscles. It is a new communication link between a functioning human brain and the outside world. These are electronic interfaces with the brain, which has the ability to send and receive signals from the brain. BMI uses brain activity to command, control, actuates and communicates with the world directly through brain integration with peripheral devices and systems. The signals from the brain are taken to the computer via the implants for data entry without any direct brain intervention. BMI transforms mental decisions and/or reactions into control signals by analyzing the bioelectrical brain activity.
While linking the brain directly with machines was once considered science fiction, advances over the past few years have made it increasingly viable. It is an area of intense research with almost limitless possibilities. The human brain is the most complex physical system we know of, and we would have to understand its operation in great detail to build such a device. An immediate goal of brain-machine interface study is to provide a way for people with damaged sensory/motor functions to use their brain to control artificial devices and restore lost capabilities. By combining the latest developments in computer technology and hi-tech engineering, paralyzed persons will be able to control a motorized wheel chair, computer painter, or robotic arm by thought alone. In this era where drastic diseases are getting common it is a boon if we can develop it to its full potential. Recent technical and theoretical advances, have demonstrated the ultimate feasibility of this concept for a wide range of space-based applications. Besides the clinical purposes such an interface would find immediate applications in various technology products also.
Picture a time when humans see in the UV and IR portions of the electromagnetic spectrum, or hear speech on the noisy flight deck of an aircraft carrier; or when soldiers communicate by thought alone. Imagine a time when the human brain has its own wireless modem so that instead of acting on thoughts, war fighters have thoughts that act. Imagine that one day we will be able to download vast amounts of knowledge directly to our brain! So as to cut the lengthy processes of learning everything from scratch. Instead of paying to go to university we could pay to get a "knowledge implant" and perhaps be able to obtain many lifetimes worth of knowledge and expertise in various fields at a young age.
When we talk about high end computing and intelligent interfaces, we just cannot ignore robotics and artificial intelligence. In the near future, most devices would be remote/logically controlled. Researchers are close to breakthroughs in neural interfaces, meaning we could soon mesh our minds with machines. This technology has the capability to impact our lives in ways that have been previously thought possible in only sci-fi movies.
Brain-Machine Interface (BMI) is a communication system, which enables the user to control special computer applications by using only his or her thoughts. It will allow human brain to accept and control a mechanical device as a part of the body. Data can flow from brain to the outside machinery, or to brain from the outside machinery. Different research groups have examined and used different methods to achieve this. Almost all of them are based on electroencephalography (EEG) recorded from the scalp. Our major goal of such research is to create a system that allows patients who have damaged their sensory/motor nerves severely to activate outside mechanisms by using brain signals.
Cyber kinetics Inc, a leader in neurotechnology has developed the first implantable brain-machine interface that can reliably interpret brain signals and perhaps read decisions made in the brain to develop a fast, reliable and unobtrusive connection between the brain of severely disabled person to a personal computer.

A brain-machine interface (BMI) is an attempt to mesh our minds with machines. It is a communication channel from a human's brain to a computer, which does not resort to the usual human output pathways as muscles. It is about giving machine-like capabilities to intelligence, asking the brain to accommodate synthetic devices, and learning how to control those devices much the way we control our arms and legs today. These experiments lend hope that people with spinal injuries will be able to someday use their brain to control a prosthetic limb, or even their own arm. A BMI could, e.g., allow a paralyzed patient to convey her/his intentions to a computer program. But also applications in which healthy users can benefit from the direct brain computer communication are conceivable, e.g., to speed up reaction times. Initially theses interactions are with peripheral devices, but ultimately it may be interaction with another brain. The first peripheral devices were robotic arms. Our approach bases on an artificial neural network that recognizes and classifies different brain activation patterns associated with carefully selected mental tasks. Using BMI artificial electrical signal can stimulate the brain tissue in order to transmit some particular sensory information.
All of it happens in the brain. The brain is undoubtly the most complex organ found among the carbon-based life forms. So complex it is that we have only vague information about how it works. The average human brain weights around 1400 grams. The most relevant part of brain concerning BMI’s is the cerebral cortex. The cerebral cortex can be divided into two hemispheres. The hemispheres are connected with each other via corpus callosum. Each hemisphere can be divided into four lobes. They are called frontal, parietal, occipital and temporal lobes. Cerebral cortex is responsible for many higher order functions like problem solving, language comprehension and processing of complex visual information. The cerebral cortex can be divided into several areas, which are responsible of different functions. This kind of knowledge has been used when with BCI’s based on the pattern recognition approach. The mental tasks are chosen in such a way that they activate different parts of the cerebral cortex.
Main principle behind this interface is the bioelectrical activity of nerves and muscles. It is now well established that the human body, which is composed of living tissues, can be considered as a power station generating multiple electrical signals with two internal sources, namely muscles and nerves.
We know that brain is the most important part of human body. It controls all the emotions and functions of the human body. The brain is composed of millions of neurons. These neurons work together in complex logic and produce thought and signals that control our bodies. When the neuron fires, or activates, there is a voltage change across the cell, (~100mv) which can be read through a variety of devices. When we want to make a voluntary action, the command generates from the frontal lobe. Signals are generated on the surface of the brain. These electric signals are different in magnitude and frequency.
By monitoring and analyzing these signals we can understand the working of brain. When we imagine ourselves doing something, small signals generate from different areas of the brain. These signals are not large enough to travel down the spine and cause actual movement. These small signals are, however, measurable. A neuron depolarizes to generate an impulse; this action causes small changes in the electric field around the neuron. These changes are measured as 0 (no impulse) or 1 (impulse generated) by the electrodes. We can control the brain functions by artificially producing these signals and sending them to respective parts. This is through stimulation of that part of the brain, which is responsible for a particular function using implanted electrodes.
Electroencephalography (EEG) is a method used in measuring the electrical activity of the brain. The brain generates rhythmical potentials which originate in the individual neurons of the brain. These potentials get summated as millions of cell discharge synchronously and appear as a surface waveform, the recording of which is known as the electroencephalogram.
The neurons, like other cells of the body, are electrically polarized at rest. The interior of the neuron is at a potential of about –70mV relative to the exterior. When a neuron is exposed to a stimulus above a certain threshold, a nerve impulse, seen as a change in membrane potential, is generated which spreads in the cell resulting in the depolarization of the cell. Shortly afterwards, repolarization occurs.
The EEG signal can be picked up with electrodes either from scalp or directly from the cerebral cortex. As the neurons in our brain communicate with each other by firing electrical impulses, this creates an electric field which travels though the cortex, the dura, the skull and the scalp. The EEG is measured from the surface of the scalp by measuring potential difference between the actual measuring electrode and a reference electrode.
The peak-to-peak amplitude of the waves that can be picked up from the scalp is normally 100 microV or less while that on the exposed brain, is about 1mV. The frequency varies greatly with different behavioral states. The normal EEG frequency content ranges from 0.5 to 50 Hz.
Frequency information is particularly significant since the basic frequency of the EEG range is classified into five bands for purposes of EEG analysis. These bands are called brain rhythms and are named after Greek letters.
Five brain rhythms are displayed in Table.2. Most of the brain research is concentrated in these channels and especially alpha and beta bands are important for BCI research. The reason why the bands do not follow the Greek letter magnitudely (alpha is not the lowest band) is that this is the order in which they were discovered.
The alpha rhythm is one of the principal components of the EEG and is an indicator of the state of alertness of the brain.
What are the thoughts the user thinks in order to control a BMI? An ideal BMI could detect the user’s wishes and commands directly. However, this is not possible with today’s technology. Therefore, BMI researches have used the knowledge they have had of the human brain and the EEG in order to design a BMI. There are basically two different approaches that have been used. The first one called a pattern recognition approach is based on cognitive mental tasks. The second one called an operant conditioning approach is based on the self-regulation of the EEG response.
In the first approach the subject concentrates on a few mental tasks. Concentration on these mental tasks produces different EEG patterns. The BCI (or the classifier in particular) can then be trained to classify these patterns.
In the second approach the user has to learn to self-regulate his or her EEG response, for example change the beta rhythm amplitude. Unlike in the pattern recognition approach, the BMI itself is not trained but it looks for particular changes (for example higher amplitude of a certain frequency) in the EEG signal. This requires usually a long training period, because the entire training load is on the user.

The BMI consists of several components: 1.the implant device, or chronic multi-electrode array, 2.the signal recording and processing section, external device the subject uses to produce and control motion and 4.a feedback section to the subject. The first component is an implanted array of microelectrodes into the frontal and parietal lobes—areas of the brain involved in producing multiple output commands to control complex muscle movements. This device record action potentials of individual neurons and then represent the neural signal using a rate code .The second component consists of spike detection algorithms, neural encoding and decoding systems, data acquisition and real time processing systems etc .A high performance dsp architecture is used for this purpose. The external device that the subject uses may be a robotic arm, a wheel chair etc. depending upon the application. Feedback is an important factor in BCI’s. In the BCI’s based on the operant conditioning approach, feedback training is essential for the user to acquire the control of his or her EEG response. However, feedback can speed up the learning process and improve performance.
A brain-machine interface (BMI) in its scientific interpretation is a combination of several hardware and software components trying to enable its user to communicate with a computer by intentionally altering his or her brain waves. The task of the hardware part is to record the brainwaves– in the form of the EEG signal – of a human subject, and the software has to analyze that data. In other words, the hardware consists of an EEG machine and a number of electrodes scattered over the subject’s skull. The EEG machine, which is connected to the electrodes via thin wires, records the brain-electrical activity of the subject, yielding a multi-dimensional (analog or digital) output. The values in each dimension (also called channel) represent the relative differences in the voltage potential measured at two electrode sites.
The software system has to read, digitize (in the case of an analog EEG machine), and preprocess the EEG data (separately for each channel), “understand” the subject’s intentions, and generate appropriate output. To interpret the data, the stream of EEG values is cut into successive segments, transformed into a standardized representation, and processed with the help of a classifier. There are several different possibilities for the realization of a classifier; one approach – involving the use of an artificial neural network (ANN) – has become the method of choice in recent years.
tasks. The user is thinking task number 2 and the BCI classifies it correctly and provides feedback in the form of cursor movement.
Now the BMI components are described as follows
The EEG is recorded with electrodes, which are placed on the scalp. Electrodes are small plates, which conduct electricity. They provide the electrical contact between the skin and the EEG recording apparatus by transforming the ionic current on the skin to the electrical current in the wires. To improve the stability of the signal, the outer layer of the skin called stratum corneum should be at least partly removed under the electrode. Electrolyte gel is applied between the electrode and the skin in order to provide good electrical contact.
Usually small metal-plate electrodes are used in the EEG recording. Neural implants can be used to regulate electric signals in the brain and restore it to equilibrium. The implants must be monitored closely because there is a potential for almost anything when introducing foreign signals into the brain.
There are a few major problems that must be addressed when developing neural implants. These must be made out of biocompatible material or insulated with biocompatible material that the body won’t reject and isolate. They must be able to move inside the skull with the brain without causing any damage to the brain. The implant must be chemically inert so that it doesn’t interact with the hostile environment inside the human body. All these factors must be addressed in the case of neural implants; otherwise it will stop sending useful information after a short period of time.
There are simple single wire electrodes with a number of different coatings to complex three-dimensional arrays of electrodes, which are encased in insulating biomaterials. Implant rejection and isolation is a problem that is being addressed by developing biocompatible materials to coat or incase the implant.
One option among the biocompatible materials is Teflon coating that protects the implant from the body. Another option is a cell resistant synthetic polymer like polyvinyl alcohol. To keep the implant from moving in the brain it is necessary to have a flexible electrode that will move with the brain inside the skull. This can make it difficult to implant the electrode. Dipping the micro device in polyethylene glycol, which causes the device to become less flexible, can solve this problem. Once in contact with the tissue this coating quickly dissolves. This allows easy implantation of a very flexible implant.
Three-dimensional arrays of electrodes are also under development. These devices are constructed as two-dimensional sheet and then bent to form 3D array. These can be constructed using a polymer substrate that is then fitted with metal leads. They are difficult to implement, but give a much great range of stimulation or sensing than simple ones..
A microscopic glass cone contains a neurotrophic factor that induces neuritis to grow into the cone, where they contact one of several gold recording wires. Neuritis that is induced to grow into the glass cone makes highly stable contacts with recording wires. Signal conditioning and telemetric electronics are fully implanted under the skin of the scalp. An implanted transmitter (TX) sends signals to an external receiver (RX), which is connected to a computer.
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18-04-2011, 08:39 AM

This is what the actual it is. These types are decided on the basis of the technique used for the interface. Each of these techniques has some advantages as well as some disadvantages. It is amazing.
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Brain-Computer Interfaces

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History – Discovering the Basics

1924: Hans Berger discovers the EEG
Analyses the interrelation of EEG and brain diseases
1970: First developments to use brain waves as input
ARPA has vision of enhanced human
First step in the right direction

Reading the brain…

Direct Neural Contact

Most accurate method
Highly invasive
Not possible with current technologies
Perhaps possible in future with e.g. nanobots


Measures electical activity in brain
Susceptible to noise
Easy to use + low cost + portable
Most commonly used device in BCIs

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