brain computer interfacing project - review - the eeg

7/30/2019 Brain Computer Interfacing Project - Review - The EEG

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www.robots.ox.ac.uk/~parg/projects/bci/rev1.html

Brain Computer Interfacing Project

Introduction

Review

Off-line BCI

On-line BCI

Technical

Developments

Data

Links

PARG Pages

BCI Review - The EEG

The EEG is recorded between electrodes placed in standard positions on

the scalp and has a typical amplitude of 2-100 microvolts and a frequency

spectrum from 0.1 to 60 Hz. Most activity occurs within the followingfrequency bands; delta (0.5 - 4 Hz), theta (4-8 Hz), alpha (8-13 Hz), beta

(13-22 Hz) and gamma (30-40 Hz).

The potential at the scalp derives from electrical activity of large

synchronised groups of neurons inside the brain. The activity of single

neurons or small groups is attenuated too much by the skull and scalp to be

detected at the scalp surface.

EEG activity in particular frequency bands is often correlated with particular

cognitive states. Signals in the alpha band, for example, are associatedwith relaxation. Thus, an electrode placed over the visual cortex that

detects alpha band signals is detecting visual relaxation. An electrode over

the motor cortex picking up alpha band signals is detecting motor relaxation

(the mu rhythm).
http://www.robots.ox.ac.uk/~parg/projects/index.htmlhttp://www.robots.ox.ac.uk/~parg/projects/bci/links.htmlhttp://www.robots.ox.ac.uk/~parg/projects/bci/data.htmlhttp://www.robots.ox.ac.uk/~parg/projects/bci/technical.htmlhttp://www.robots.ox.ac.uk/~parg/projects/bci/online.htmlhttp://www.robots.ox.ac.uk/~parg/projects/bci/offline.htmlhttp://www.robots.ox.ac.uk/~parg/projects/bci/review.htmlhttp://www.robots.ox.ac.uk/~parg/projects/bci/index.html


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Brain-Computer interfaces use EEG signals which can be controlled by the

user. These types of EEG signals fall into two main classes; evoked

responses which are EEG components evoked by a specific sensory

stimulus, such as a flashing light, and spontaneous EEG signals which

consist of EEG components that occur without stimulus, such as the alpha

rhythm or the mu rhythm. Note, however, that some spontaneous EEG

signals such as the mu rhythm can be affected by stimuli.

The ability of subjects to produce at will strong spontaneous EEG rhythms

such as the alpha rhythm or the mu rhythm can be enhanced by the use ofbiofeedbackor operant conditioning. This is a process whereby the user is

given an indication as to how well he/she is controlling a device (eg. by

looking at it). This constitutes the `feedback'. The subject then changes

their EEG signal in response to this feedback. In this way, the subject to

learns control the device through a learning process which can take several

hours, days or weeks to complete. BCI systems developed in the 1960s

and 1970s relied on biofeedback. It has the advantage of being simple but

requires long training times for each user.

Evoked Responses used in BCI research fall into three main classes;Evoked Potentials (DC changes in response to continuous evoking

stimulus), Event-Related Potentials (DC changes in response to a discrete

event) and Event-Related Desynchronisations (AC changes in response to

a discrete event).

Evoked Potentials (EPs) require a specific external stimulus and originate

in sensory cortex areas. A typical evoked potential is the Visual Evoked

Potential (VEP). In response to a strobe light, for example, the EEG over

the visual cortex will vary at the same frequency as the stimulating light.


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u ec s can e ra ne o con ro e s reng o e r s ea y s a e

with the use of biofeedback. This forms the basis of other BCI systems.

Because the EEG control signal is at a precise, known and controllable

frequency it is very easy to detect. This means that the subsequent signal

processing and pattern recognition tasks are very simple . The

disadvantage of such methods is the need for an external stimulus and the

long training time required.

Event-Related Potentials (ERPs) occur in response to, or in advance ofparticular `events'. The P300 ERP, for example, occurs 300 ms after an

event occurs to which the subject has been told to respond. The event

must be one in a series of Bernouilli events (ie. one of two types) and have

a low probability of occuring.

Event-Related Synchronizations or Desynchronizations (ERS/ERD) are AC

changes which occur in response to events (whereas ERPs are DC

changes). The mu rhythm, for example, is desychnronized by movement,

tactile stimulation or by planned movement (the pictures below show

images of the head from above - the left image is for a subject planning a

right hand movement and the right image is for planned left hand movement

- dark areas correspond to strong mu rhythm ERD).

Interfaces based on ERPs and ERDs do not, in principle, require any

training of the user. The user does not, for example, have to learn to control

his ERD - it is already present in any subject who intends to move his

finger. This advantage is offset by the fact that ERDs are harder to detect.

EPs, ERPs and ERDs are signals between 2 and 10 microvolts in strength.

They are therefore difficult to detect in the background EEG signal of 100

microvolts. In clinical research a signal averaging method is used whereby

the stimulus or event is repeated a large number of times and the

responses are averaged. In this way. the parts of the EEG signal that are

not relevant to the 'event' are averaged out. This takes many minutes or

hours of signal capture. On-line BCI systems cannot use this method as

they must respond within seconds. They must therefore use the non-

averaged EEG. Thus more complex signal processing methods are used

which require more computer power.

Electrode placement and the subsequent signal processing can be guided

by what is known of the neurophysiology of the mechanisms that generate

the EEG signals. Thus, for example, systems using the mu rhythm ERD will


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brain computer interfacing project - review - the eeg

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