EEG Based Experiments and pre-processing of
EEG data
Isabella Hinterleitner, 0006380
Abstract - The article explains how to teach basic EEG skills for engineering students based on the
example of three experiments to measure Alpha, Beta and Theta waves. It explains the conditions how
they were conducted and the interpreted results.
Key Words – Biofeedback, Neurofeedback, EEG, Progressive Muscle Relaxation Method, Pattern
Recognition Methods
1 Introduction
Biofeedback as a field has been growing since the late 1960s. Of particular interest to
psychologysts is the electrcal functioning of the brain. The form of biofeedback that enables
people to alter brain electrical is called “neurofeedback” (or EEG biofeedback).
The reason that neurofeedback is of special concern to psychologists is, because the brain is a
central contributor to the emotions, physical symptom, thoughts and behaviours that define
many problems for which people seek psychological consulation.
The goal of my work is to design EEG biofeedback experiments for students. The
experiments deal with measuring Alpha, Beta and Theta waves during a specific task, the
students have to solve. For measurement, there is used the 10/20 electrode placement system.
The results of the experiments will be pre-processed by using LMS Least Mean Square
filtration method. The results will serve for development of a set of tasks that will constitute a
basis for training of, for example, better concetration during tasks solving or relaxation when
the person feels tired.
2 Motivations
The aim of the study was to design experiments that support teachers, professors and
assistents in teaching EEG based techniques.
There is an extremly high afford to do this since teaching these methods requires teachers to
spend time in labs and to assist their students in the experimenting tasks.
By designing these experiments it was taken in account that teachers have a lot of students to
supervise and little time to actually assist them.
I tend to prefer the method of student tutoring where younger students learn from older
students. The article explains three basic EEG experiments in depths and explains how
teachers can conduct them.
Morover it gives an opprtunity for extension and deepening the work by mentioning some
extra tasks.
To control the lab work it is assumed that the student monitor their results via a lab protocol.
In each group there sould be at least one patient, a coordinator, whose task is to read the tasks
to the patient and a protocoll writer. So the minimum group size will be three people.
The tutors should supervise the work of the students done in the lab course – the actual
measurement and the pre-processing of the data in MatLab.
The professor is able to review the results via the posting of the students in an online forum
and gets an overview of the work at the final examination.
3 Methods
The first experiments deal with measuring Alpha waves using the 10/20 electrode placement
system [5], which means that the electrodes are placed on the head at specific locations that
are 10% or 20% of a measured length from a known landmark on the head. The eqippment
supplied will be an EEG measuring device, which can be accessed by the students in the
labratory environment.
The goal is that by using Muscle Relaxation Method the patient
should get into a relaxed state. Progressive Muscle Relaxation is
a method used where patients relax their muscles step by step
until their whole body is relaxed. It is used to decrease stress. [6]
The duration of the experiment will be 20 minutes.
Figure 1 - EEG
Measurement Device
To produce modifications, the tested person varies with either eyes staying open or eyes
staying shut. There should be a different result due to this condition, which will be evaluated
by the students in a protocol.
The second experiment deals with measuring Theta wave [1], with a frequency band between
4-8Hz. The goal is that the patient has to remind himself/herself of an emotional incident back
in his past. The duration of the recalling process is limited with 5 minutes. During the
recalling of the incident the person will be measured.
The third experiment focuses on measuring Beta waves, when the frequency band is between
15-30Hz. The person has to solve an analytical mathematical problem during a given time.
Though it is not important that the task is fullfilled with the correct result. The experiment
takes 20minutes.
Each of the experiments will be protocolled precisely by a student protocoll covering
important parameters on the measuring situation.
4 Results
The output of the experiments will be converted into .ASCI for further pre-processing in Mat
Lab. The sampling frequency was set on 250 mHz. The result of the first experiment before
filtering should be examined from the the students as regards artefacts, sich as blinking from
the person who was measured. The blinking represents a good way to test, if the measuring
device is working.
Within the frame of the student experiments the filtering is done by using Mat Lab. The filter
used will be a low pass filter with a sampling frequency of 128Hz. For pre-processing the
meausred data students may use a special Mat Lab library for Filtering.
The interpretion of the signal involves examining the quantification of the signal strenght and
regognizing the different EEG patterns dependent on the frequency rate.
Latter can be done by comparing the signal patterns to each other as it is done in figure 2 and
3 below.
For further classification students use advanced methods, such as Local Neural Classifiers or
Neural Networks.
The result of the first experiment was concerned measuring Alpha waves. The experiment
was carried out with eyes closed.
Figure 2 Results of the first experiment - Alpha wave measurement
Figure 3 - Table of Wavelengths - Alpha.
Beta, Theta, Delta
The students shall classify their results according to the characteristics of Alpha, Beta, Theta
waves. See figure below.
The second experiment was measuring Theta waves, where the student has to remind himself
of a stressful incident, such as anger or grief. During the experiment he has his eyes closed
and it is important not to move because of artefacts.
Theta waves are in general measured during strong emotions but can also be encountered
during sleep and daydreaming.
The third experiment was concerned with measuring Beta waves. During the experiment the
student had to calculate rows of numbers, which is presented by reading it to him. The student
can not see the numbers in front of him. For example: 12+4-3+14-23+12-15.
The student has his/her eyes closed during the experiment.
Figure 4 Results of the third experiment - Beta Waves measurement
Finally there will be a quantitative EEG analysis by quantifying the properties of measured
EEG, using power spectral density and modelling the ouput of a time varying system.
Successively there will be done the quantitative analsysis by quantifiying the properties of
measured EEG signals. If the signal is stationary the quantitative analysis is done by power
spectral density. The non-stationary EEG recordings shall be modelled as an output of a time
Varying system. In the analysis pf non-stationary EEG it is important to estimate the time
varying spectral properties of the signal. The time varying parameter estimation problem can
be solved with adaptive algorithms, such as the least mean square (LMS) [2] or dividing
non-stationary signals into stationary segments either adaptive or constant segmentation [3].
5 Conclusions
The eperiments provide an opportunity to the students to study the basics of EEG
measurement and biofeedback. They may deepen their interest with further questions to the
experiments in their research protocol.
The experiments can be set in the frame of a semester project to encourage the students to get
deeper into certain parts.
An extension of the experiment is connceted with the study from A. Blood and R. Zatorre. [4]
Their idea was to measure the chill effect, when someone listens to music he/she likes, by
measuring for example the skin tension, pulse, heart rate and body temperature.
The extension will be to measure the chill effect using EEG as a method of investigation.
For this the students has to bring some sample music he/she likes in order to achive the effect.
The students measured should be with musical background experience, as it was carried out in
the scope if the experiment from 2001 done by A. Blood and R.Zatorre.
The question is asked is, if it is possible to detect the chill effect by measuring the EEG.
Finaly there should be an evaluation process of all experiments, where students have the
opportunity to modify and make extensions if needed for understanding. The results of the
students should be discussed with a tutor or teacher after each measuring step.
At the end each student group presents the work in a student conference and will be examined
crtically.
References:
[1] Cappa S.F., Cognitive Neurology An Introduction, Imperial College Press, 2001:82-85
[2] Olkkonen H., Pesola P, Valjakka A, Tuomisto L. Gain optimized cosine transform domain
LMS algorithm for adaptive filtering of EEG. Comput Biol Med. 1999 Mar;29(2):129-36
[3] Rieger J., Lhotská L., Krajca V, Matousek M.; Application of Quantitative Methods in
Signal Processing to Automatic Classification of Long-Term EEG Records. In: Biological and
Medical Data Analysis. 2004, s. 333-343.
[4] Blood, A. J., & Zatorre, R. J. (2001). Intensely pleasurable responses to
music correlate with activity in brain regions implicated in reward
and emotion. Proc Natl Acad Sci U S A, 98(20), 11818-11823.
[5] http://www.piercecollege.edu/faculty/pandeyc/ElectrodePlacement.html Electrode
Placement last accessed on 19.5.07
[6] http://www.breastcancer.org/comp_med_pmr.html What is progressive Muscle Relaxation
Last accessed on 19.05.07