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Developing a Brain Computer Interface


Seminar Survey On

"Brain Computer Program"

Submitted by:

Name: Sachin Kumar Spin No: 1214310301


Brain Computer Program allows users to talk to each others by using only brain activities without using any peripheral nerves and muscles of body. On BCI research the Electroencephalogram (EEG) is used for saving the electro-mechanical activity across the scalp. EEG is used to measure the voltage fluctuations caused by ionic current flows within the neurons of the mind. Hans Berger a German neuroscientist, in 1924 uncovered the electro-mechanical activity of human brain by using EEG. Hans Berger was the first one who registered an Alpha Influx from a mind.

In 1970, Protection Advanced Research Projects Firm of USA initiated this program to explore brain communication using EEG. The papers published following this research also mark the first appearance of the manifestation brain-computer software in scientific books. The field of BCI research and development has since targeted mainly on neuroprosthetics applications that purpose at restoring damaged hearing, look and movements.

Nowadays BCI research is certainly going on in a full swing using non-invasive neural imaginary technique largely the EEG. The future research on BCI will be centered generally in nanotechnology.

Research on BCI is radically increased during the last decade. From last decade the maximum information copy rates of BCI was 5-25 parts/min but at the moment BCI's maximum data transfer rate is 84. 7bit is/min.


Brain-computer user interface (BCI) is alliance between a brain and a tool that enables signs from the mind to lead some exterior activities, such as control of a cursoror a prosthetic limb.

The Brain processing interface enables a primary communications pathway between the brain and the thing to be controlled. For instance, the signal is transmitted directly from the brain to the mechanism directing the cursor moves, alternatively than taking the normal ways through the body's neuromuscular system from the brain to the finger on the mouse then directing the curser.

BCIs Research started out in the 1970s at the University of California Los Angeles(UCLA) under an allowance from the National Science Foundation, accompanied by a deal fromDARPA.

Thanks to the amazing cortical plasticity of the mind, alerts from implanted prostheses can, after adaptation, be taken care of by the mind like natural sensor or effector programs. Animal experimentation for years, the first neuroprosthetic devices implanted in humans made an appearance in the mid-1990s.

Current brain computing interface devices require determined conscious thought; some future applications, such as prosthetic control, will probably work quite easily. Development of electrode devices and/or surgical methods that are minimally intrusive is one of the biggest challenges in growing BCI technology.

Though Brain Computer User interface (BCI) facilitates direct communication between brain and computer or another device so nowadays it is trusted to improve the probability of communication for folks with severe neuromuscular disorders, spinal-cord personal injury. Except the medical applications BCI is also used for multimedia applications, which becomes possible by decoding information straight from the user's brain, as mirrored in electroencephalographic (EEG)signals which are noted non-invasively from user's scalp.


Current Developments in Graz Brain-Computer User interface (BCI)


  1. Pfurtscheller, C. Neuper, C. Guger, W. Harkam, H. Ramoser,
  2. Schl¶gl, B. Obermaier, and M. Pregenzer

The "Graz Brain-Computer Interface" (BCI) job is aimed at developing a technological system that can support communication prospects for patients with severe neuromuscular disabilities, who are specifically need of increasing reliable control via non-muscular devices.

This BCI system uses oscillatory electroencephalogram (EEG) signals, recorded during specific mental activity, as source and provides a control option by its output. The obtained result signals are presently examined for different purposes, such as cursor control, selection of characters or words, or control of prosthesis.

Between 1991 and 2000, the Graz BCI task shifted through various levels of prototypes. Inside the first years, mainly EEG patterns during willful limb movement were used for classification of solo EEG trials. In these experiments, a cursor was migrated e. g. left, right or downwards, depending on planning of remaining hand, right hand or ft. movement. Comprehensive off-line analyses have shown that classification accuracy and reliability advanced, when the suggestions features, such as electrode positions and rate of recurrence rings, were optimized in each subject matter. Aside from studies in healthy volunteers, BCI experiments were also performed in patients, e. g. , with an amputated top limb.

The main elements of any BCI system are:

Signal acquisition system: will involve the electrodes, which grab the electrical activity of the mind and the amplifier and analog filters.

The feature extractor: converts the brain signals into relevant feature components. At first, the EEG organic alerts are filtered by an electronic band pass filtration. Then, the amplitude examples are squared to get the power samples. The power examples are averaged for many tests. Finally, the transmission is smoothed by averaging over time samples.

The feature translator: classifies the feature components into reasonable controls.

The control interface: changes the logical controls into semantic settings.

The device controller: changes the semantic settings to physical device commands, which differ from one device to another with regards to the application.

Finally, these devices commands are carried out by these devices.

The early work of BCI was done by intrusive methods with electrodes placed in to the brain tissue to read the impulses of a single neuron. However the spatio-temporal image resolution was high and the results were highly exact, there were problems in the long run. These were typically due to the scar tissue formation, which contributes to a progressive weakening of the signal and even complete signal loss within a few months as a result of brain tissue response towards the overseas objects.

A proof concept test was done by Nicolelis and Chapin on monkeys to regulate a robotic arm instantly using the invasive method.

Recently, less intrusive methods have been employed by applying a range of electrodes in the subdural space over the cortex to track record the Electrocorticogram (ECoG) indicators. It has been found that common Electroencephalogram pickup alerts are averaged over several EEG signal bands (Hz) square ins, whereas ECoG electrodes can measure the electrical activity of brain cells over the much smaller area, thereby providing higher spatial resolution and an increased signal to noise ratio because of the thinner barrier tissue between the electrodes and the mind cells. The superior potential to record the gamma strap signals of the brain tissue is another important good thing about this type of BCI system. Gamma rhythms (30-200 Hz) are made by skin cells with higher oscillations, which are not easy to record by normal EEGs. The individual skull is a thick filtration system, which blurs the EEG signals, especially the higher frequency rings (i. e. gamma music group).

Noninvasive techniques were exhibited usually by electroencephalographs (EEG). Others used efficient Hz, Magneto-Resonance Imaging (fMRI), Positron Electron Tomography (Dog or cat), Magneto encephalography (MEG) and Sole Photon Emission Computed Tomography There (SPECT). EEGs have good thing about higher temporal resolution, achieving a few milliseconds and are relatively low cost.

Recent EEG systems have better spatiotemporal resolution of up to 256 electrodes over the full total area of the head. Nevertheless, it cannot record from the deep parts of the brain. This is the primary reason why the multimillion money fMRI systems remain the preferred way for the functional research of the brain. However, EEG systems remain the best applicant for BCI systems spatial because they are simple to use, lightweight and cheap.

The main problems that reduce the trustworthiness and correctness of BCI and which prevent this technology from being medically useful, are the sensory interfacing problems and the translation algorithm problems. In order to make a medically useful BCI the accuracy and reliability of the detection of intention must be high and certainly much higher than the presently achieved accuracy with different types of BCI.

The intermediate compromise between exactness and security is the ECoG centered BCI, which has shown considerable promises. The sensory arrays of electrodes are

less invasive and provide comparable precision and high spatial resolution set alongside the implanted type. The ECoG founded BCI needs much less training than the EEG based BCI and research workers have shown that highly correct and fast response.

4. Techie DETAILS

REASON At the rear of WORKING:

The reason a BCI works whatsoever is because of the way our brains function. Our brains are filled with neurons, individual nerve cells linked to one another by dendrites and axons. Each and every time we think, move, feel or bear in mind something, our neurons are at work. That work is completed by small electric alerts that zip from neuron to neuron as fast as 250 mph. The signs are produced by dissimilarities in electric potential transported by ions on the membrane of each neuron.

Although the paths the signs take are covered by something called myelin, a few of the electric transmission escapes. Scientists can identify those indicators, interpret what they indicate and use them to direct a tool of some kind. It can also work the other way around.

For example, experts could find out what alerts are sent to the mind by the optic nerve when someone considers the color red. They could rig a camera that could send those exact signs into someone's brain whenever the camera found red, allowing a blind person to "see" without eye.

BCI Suggestions AND End result:

One of the biggest obstacles facing brain-computer interface researchers today is the essential technicians of the interface itself.

The least complicated and least invasive method is a set of electrodes -- a tool called an electroencephalograph(EEG) -- attached to the scalp. The electrodes can read brain indicators. However, the skull blocks a lot of the electrical transmission, and it distorts what does get through.

To get a higher-resolution sign, scientists can implant electrodes directly into the gray subject of the mind itself, or on the top of brain, under the skull. This enables for much more immediate reception of electric impulses and allows electrode positioning in the specific section of the brain where in fact the appropriate indicators are generated. This process has many problems, however. It needs intrusive surgery to implant the electrodes, and devices kept in the mind long-term tend to cause the formation of scar tissue formation in the gray matter. This scar tissue ultimately blocks impulses.

Regardless of the positioning of the electrodes, the basic system is the same: The electrodes evaluate minute variations in the voltage between neurons. The indication is then amplified and filtered. In current BCI systems, it is then interpreted by the computer program, although you may be familiar with elderly analogue encephalographs, which shown the impulses via pens that automatically composed out the patterns on a continuous sheet of newspaper.

In the case of any sensory type BCI, the function happens in reverse. A computer turns a sign, such as one from a video camera, into the voltages essential to result in neurons. The impulses are sent to an implant in the proper section of the brain, in case everything works accurately, the neurons open fire and the subject receive a aesthetic image corresponding from what the camera considers.


The most typical and oldest way to use a BCI is a cochlear implant. For the average indivdual, sound waves enter into the ear and go through several small organs that eventually pass the vibrations to the auditory nerves by means of electric signals. If the mechanism of the ear is severely harmed, see your face will struggle to listen to anything. However, the auditory nerves may be performing perfectly well. They just aren't receiving any signs.

A cochlear implant bypasses the non performing part of the ear, functions the sensible waves into electric alerts and passes them via electrodes right to the auditory nerves. The effect: A recently deaf person is now able to hear. He could not hear flawlessly, but it allows him to comprehend conversations.

The processing of aesthetic information by the mind is much more complex than that of sound information, so artificial vision development isn't as advanced. Still, the process is the same. Electrodes are implanted in or close to the visual cortex, the region of the mind that processes visible information from the retinas. A set of glasses positioning small cams is connected to a computer and, subsequently, to the implants. After an exercise period like the one used for remote control thought-controlled movement, the subject can see. Again, the eye-sight isn't perfect, but refinements in technology have upgraded it greatly since it was initially attempted in the 1970s. Jens Naumann was the receiver of a second-generation implant. He was completely blind, but now he can navigate NY City's subways by himself and even drive a car around a parking lot. In conditions of research fiction becoming truth, this technique gets very close. The terminals that hook up the camera eyeglasses to the electrodes in Naumann's brain act like those used to hook up the VISOR (Aesthetic Instrument and Sensory Organ) worn by blind anatomist official Geordi La Forge in the "Star Trek: ANOTHER Era" TVshow and movies, and they are both essentially the same technology. However, Naumann isn't able to "see" invisible helpings of the electromagnetic spectrum.


Applications of BCI are described as follows:


Currently, there is a new field of gaming called Neurogaming, which uses non-invasive BCI in order to boost gameplay so that users can connect to a system without the use of a normal controller. Some Neurogaming software use a player's brain waves, heart rate, expressions, pupil dilation, and even feelings to complete duties or influence the disposition of the overall game. For instance, game developers at Emotiv have created non-invasive BCI that will determine the ambiance of a player and adjust music or landscapes accordingly.

This video games experience will add a real-time experience in gaming and will expose the capability to control a video game by thought.

Prosthesis control:

Non-invasive BCIs are also applied to permit brain-control of prosthetic top and lower extremity devices in people with paralysis. For example, Gert Pfurtscheller of Graz University of Technology and acquaintances showed a BCI-controlled functional electrical excitement system to restore upper extremity movements in a person with tetraplegia anticipated to spinal-cord harm. Between 2012 and 2013, research workers at the University or college of California, Irvine showed for the first time that it's possible to use BCI technology to revive brain-controlled walking after spinal cord injury.

Synthetic telepathy/silent communication:

In a $6. 3 million Army initiative to invent devices for telepathic communication, Gerwin Schalk, underwritten in a $2. 2 million grant, found that you'll be able to use ECoG alerts to discriminate the vowels and consonants embedded in spoken and in imagined words. The results reveal the distinct mechanisms associated with production of vowels and consonants, and could supply the basis for brain-based communication using imagined talk. On Feb 27, 2013Duke University researchers successfully connected the brains of two rats with electronic digital interfaces that allowed those to directly talk about information, in the first-ever immediate brain-to-brain interface.

MEG and MRI:

Magnetoencephalography (MEG) and useful magnetic resonance imaging (fMRI) have both been used successfully as non-invasive BCIs. Within a widely reported experiment, fMRI allowed two users being scanned to experience Pongin real-time by modifying their haemodynamic response or brain blood circulation through biofeedback techniques.

fMRI measurements of haemodynamic reactions instantly are also used to regulate robot biceps and triceps with a seven second delay between thought and movement.

Neural Internet:

Access to the internet starts an array of opportunities for those with severe disabilities, including shopping, entertainment, education, and possibly even occupation. Neural control users cannot control a cursor with a great degree of detail, so, therefore, the task of adapting a browser for neural control is to make links-which are spatially organized-accessible. The School of Tuebingen developed a web browser controller to be used with the thought translation device, but it needs the user to select from an alphabetized list of links, causing problems if the hyperlink names are indistinguishable. They have developed a neurally handled browser that serializes the spatial internet software and allows logical control of a web application.

BrainTrainer-Subject Training:

The BrainTrainer project researches the most effective ways of instructing a person the brain-signal control needed to interact with a device. The BrainTrainer toolset allows experts to compose tests by giving simple jobs, such as concentrating on, navigation, selection, and timing, that can be combined to create an appropriate-level task for a specific subject.

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