Abstract: Neuromarketing: Acquistition of EEG signals led to the

Abstract:

The Electroencephalographic (EEG) signals are those which records
the electrical status of the human brain.The signal pattern varies according to
the chemical reaction in the human brain.  The recorded waveforms reflect the cortical electrical activity.
EEG activity is quite small, measured in microvolts (mV). Acquistition of the EEG signal can be used in
many research fields. Depending on the frequency of obtained signal it can be
classified into five types they are: delta, theta, alpha and beta.

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Introduction:

The brain is the most complex part in the human body. It
controls the overall activity of our body, it consist of billions of neurons
which communicates with each other in achieving it. Inside the human brain
there will be a lot of chemical reaction taking place in it.The evolution of
the EEG signals took place in 1929.Hans Berger was the first scientist to found
about the EEG signals and on the later stages it found a drastic improvement in
the research about the various fields.The different types of brain waves have
specific frequency such as beta(14-30hz), alpha(8-13hz), theta(4-7hz) and delta
(<3.5hz). These waves have certain characteristics, by analysing those wave pattern we can do various research in different fields such as BCI (Brain computer interface), Phycological factors, neuro-imaging, etc       Neuromarketing: Acquistition of EEG signals led to the new field of science called neuromarketing.It is a new way to get the feedback that you could measure with a consumer device to discover which types of advertising are effective and useful, and which types are embrassing. Neuromarketing researchers believe that  consumers' decisions are made in a split second,  those decisions are made subconsciously. They strongly believe that decision of consumers are not factual and they are totally taken in a matter of seconds by simple attraction that the company advertises. The function of neuromarketing is to analyse how the customers emotions are triggered depending on the advertisement they see, how their sub concious mind react to it. The data it generates is extremely useful for the companies to develop an advertisement which attracts the customers they target. The data is gathered by monitoring certain biometrics, including: Eye tracking Facial coding Galvanic skin response and electrothermal activity Electroencephalography (EEG) Some neuromarketing research is conducted using fMRI, which measures brain activity by detecting changes in blood flow in response to stimuli. It yields accurate data, but it is challenging for the following reasons: It requires subjects to lie completely still in a large MRI chamber, which can be a total discomfort to the subjects. Stimuli cannot be encountered in the same way the test subject would usually be exposed to it—you can't take an MRI chamber into a retail store. It takes a lot of time and its also expensive stratergy. EEG technique, on the other hand, allow neuromarketing research to be conducted efficiently  from anywhere. This methodology helps the researchers to measure consumer response to an testing environment , such as a movie theatre, bar, mall.  Small biosensors can be placed at distinct places on the head, allowing for accurate measurement of brain activity while giving the test subject full range of motion and ensuring their comfort. Changes in state of the brain can be interpreted using the suitable technique and the current status of the individual such as sleepiness, focused state ,laziness etc can be found.  In a concentrated state, a 30 second commercial advertisement is enough to hold them to watch carefully.The EEG reading taken from that consumer in test reveals that ,he/she will be fully attentive for the first 10 seconds and lost their attention for next 10 seconds finally they pay attention at the final 10 seconds.Thus improving the middle content of the video based on the feeedback could help us to create a more creative commercial. Neuromarketing helps firms to create more effective and creative advertisements. This not only benefits the venture, but also the consumers who are exposed to hundreds of ads per day, so creating more informative, emotionally rewarding, and useful ads can enhance a customer's experience with a product or brand long before they consider buying. Brain computer interface: Introduction                 The major field where the EEG signals can be effectively utilised is the Brain Computer interface (BCI)."A brain–computer interface is a communication system that does not depend on the brain's normal output pathways of peripheral nerves and muscles." It reflects the principal reason for the interest in BCI development—the possibilities it offers for providing new augmentative communication technology to those who are paralyzed or have other severe movement deficits. All other augmentative communication technologies require some form of muscle control, and thus may not be useful for those with the most severe motor disabilities, such as late-stage amyotrophic lateral sclerosis, brainstem stroke, or severe cerebral palsy.Therefore by using this technique we can make a lot paralyzed patients to act on their own without depending on anyone. Essentials features of BCI BCI operation depends on the communication which takes place between the two adaptive controllers, the user's brain, which produces the activity (EEG signals) measured by the BCI system, and the system itself, which translates that activity into specific commands to perform the tasks. Completing the BCI operation is a new skill,it does not control our muscular organs but it controls our EEG signals as a single unit. Each BCI uses certain algorithm to translate the obtained input into required output control signals of our requirements. This algorithm might include linear or nonlinear equations, a neural network, or other methods, and might incorporate continual adaptation of important parameters to key aspects of the input provided by the user. BCI outputs can be cursor movement, letter or icon selection, or another form of device control, and provides the feedback that the user and the BCI can use to adapt so as to optimize communication. Adding to its input, translation algorithm, and output, each BCI has several other distinctive characteristics which should be monitored. These include its On/Off mechanism (e.g., EEG signals or conventional control); response time, speed and accuracy and their combination into information transfer rate, appropriate user population, applications and constraints imposed on concurrent conventional sensory input and motor Matching BCI and the Input to user. The input features of proposed BCI system should be properso that it can be broadly applied to the communication needs of users with different disabilities. Most BCI systems use EEG or single-unit features that originate mainly in somatosensory or motor areas of cortex. These areas may be severely damaged in people with stroke or neurogenerative disease. Use of features from other CNS regions may prove necessary. In EEG-based BCI system, effective multielectrode recording which are  performed initially and then periodically, can detect the changes in the user's performance and, and can thereby guide selection of optimal recording locations and EEG features. Some areas of the brain may not be effectively used for the interaction because of slow potentials and rhythms. BCI system should be designed such that it works on the  wide variety of EEG signals.A system works on the slow potentials,rhythms,P300 potentials, etc are under the research. Signal analysis and translation algorithms: Signal analysis is done in the BCI system in order to enhance the signal-to-noise ratio (SNR) of the EEG or single-unit features that carry the user's messages and commands. To accomplish this, consideration of the major sources of noise is essential. Noise has two types of sources  both nonneural sources (e.g., eye movements, EMG, 60-Hz line noise) and neural sources (e.g., EEG features other than those used for communication). Noise detection and eliminating those noises will be very difficult if the frequency, amplitude and other parameters of noises are similar to the required system.. While they can enhance the signal-to-noise ratio, they cannot directly address the impact of changes in the signal itself. Factors such as motivation, intention, frustration, fatigue, and learning affect the input features that the user provides. From that we can state that proper interaction between the user and the system and a effective signal processing methods helps in the BCI development. A translation algorithm is a series of computations that transforms the BCI input features derived by the signal processing stage into actual device control commands. Stated in a different way, a translation algorithm takes abstract feature vectors  that encodes the message that the user wants to communicate and transforms those vectors into application-dependent device commands. Different BCI's use different translation algorithms . Each algorithm can be classified in terms of three key features: transfer function, adaptive capacity, and output. The transfer function can be linear (e.g., linear discriminant analysis, linear equations) or nonlinear (e.g., neural networks). The algorithm can be adaptive or nonadaptive. Adaptive algorithms can use simple handcrafted rules or more sophisticated machine-learning algorithms. The output of the algorithm may be discrete (e.g., letter selection) or continuous (e.g., cursor movement). The diversity in translation algorithms among research groups is due in part to diversity in their intended real-world applications. Nevertheless, in all cases the goal is to maximize performance and practicability for the chosen application. BCI application: Figure shows the various fields in which the BCI's are used.   Application of EEG signals in epilepsy diagnosis: Epilepsy: Epilepsy is a  disorder that causes different types of seizures. A seizure is a sudden surge in the electrical conditions in the brain . It consist of two main types. Generalized seizures which affects the whole brain. Focal, or partial seizures, which affect just one part of the brain . Impacts of seizures vary according the type which the person is affected. There are several symptoms for epilepsy fever, stroke, etc It is a common disorder which affects millions of people around the world.Types of seizures are   Focal (partial) seizures, A simple partial seizure and Complex partial seizures . Generalized seizures Generalized seizures affects the whole brain. The different types are they are Absence seizures,Tonic seizures , Atonic seizures , Clonic Myoclonic seizures  and Tonic seizures EEG Analysis: An EEG test only decribes about the electrical activity of the brain at the time of the test bring conducted. If a person is affected by the seizure he/she has unusal brain activity. At other time  brain activity is normal. So, if your EEG test results  are normal, it usually means that there is no epileptic activity in your brain at the time the test is being done. People affected by epilepsy have unusual electrical activity in their brain all the time, even when they are not having a seizure. From the test results a doctor can recognise the pattern of waves and he/she can diagnose it. Some people may have unusal brain patterns but they wont have epilepsy . These could be caused by other medical conditions, problems with their vision, or brain damage.So it may found that this technique may not be correct everytime.It can also show up some types of seizure. But it might not show up some focal (partial) seizures .The EEG signals only gives the brain activity and not the location of affected areas.There's a very small risk that you could have a seizure during an EEG test. This could be caused by looking at a flashing light or breathing deeply. These activities are usually part of the test.Your doctor may ask you to reduce your epilepsy medicine or have less sleep than usual before you have some types of EEG tests. This would also increase the risk that you would have a seizure around the time of having the test.If you hold a driving licence, having a seizure could mean that youshould not drive  until you have been seizure free for 12 months. There are several ways an EEG test can be done. Standard EEG tests . You may be asked to breathe deeply for some minutes and also to look at a flashing light. These activities can change the electrical activity in your brain, and this will show on the computer.You will be asked to keep as still as possible during the test. Any movement can change the electrical activity in your brain, which can affect the results.Routine EEG recordings usually take 20 to 40 minutes. Sleep EEG tests EEG test is taken when you are asleep.Before the test, you may be given some medicine to make you go to sleep. The test lasts for one to two hours.It is useful when epilepsy is suspected in children under 5. This is because there are some types of epilepsy which are common in young children, where seizures mainly happen in sleep. Sleep-deprived EEG tests These  tests are done when you have had less sleep than usual. At that time, there is more chance of unusual electrical activity in the brain.It can show up subtle seizures,. Before you have a sleep-deprived EEG test, your doctor may ask you not to go to sleep at all the night before.The patient sleeping timings should be altered. You may then fall asleep while recording the activity in your brain. It extends upto few hours. Ambulatory EEG tests These tests are conducted when the patient is walking. It is designed to record the activity in your brain over a few hours, days or weeks. This means there is more chance that it will pick up unusual electrical activity in your brain, than during a standard or sleep EEG test.However, the electrodes that are attached to your head are plugged in to a small machine that records the results. You can wear the machine on a belt, so you are able to go about your daily business. You don't usually stay in hospital .The person should keep track of activities which they do. Diagnosis:  Identifying  what kind of seizure is the patient is being affected is the most critical step in diagnosis of epilepsy.Different seizures are to be treated in the unique way ,if it is not clearly identified  false treatment may affect the patient in a greater level. The diagnosis includes meditation, medicines, etc