b6 laboratory in medical instrumentationgari/teaching/b18/labs/labsheet jan 2013.pdf · the lab the...
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B18 /BME1 MEDI CA L
I NS TRU MEN TA TION LA BO RA TO RY
AIMS OF THE SESSION
Your aims in this laboratory are as follows:
to gain hands on experience in the acquisition of ECG and EEG signals
to understand and describe how they relate to relevant physiology and electrode
placement
to understand the role of signal conditioning (amplifiers, filters) in their
measurement and to choose suitable parameters (e.g. gain, cut off frequency,
sampling rate)
to understand and describe the main sources of error introduced in measurement
PREPARATORY WORK
Before coming into the lab, complete the preparation (Section 1) and read through the
handout, including the Lab record. Preparation should be completed in your logbook and
brought to the lab with you.
Expect to spend about one hour. You will lose marks if you do not do the preparation
Safety. Any equipment attached to the body is battery operated or electrically isolated.
Standard risks for using computers apply
LOCATION AND TIME
Location: Medical Instrumentation laboratory, off the Electrical lab, 5th
floor
Time: 11.00 am to 17.00 pm (with break for lunch – 13.00-14.00 pm)
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INTRODUCTION
There are three exercises to complete. You need to share the equipment for Exercise B
and will be assigned a time to do this at the start of the full laboratory session
Exercise A: ECG acquisition and processing
Exercise B: Frequency and signal analysis using Matlab; Einthoven’s triangle
Exercise C: EEG acquisition and processing
You will work in groups of two. We will need volunteers for the ECG and EEG signal
acquisition. If you are prepared to volunteer please wear loose clothing.
USING THE EQUIPMENT
The electrodes and connectors are delicate. Be careful how you connect them to the
amplifiers and bio-radio kit.
It is important to establish good connection between the electrodes and skin. The
demonstrators will help you attach electrodes, but you may also want to watch the videos
in B18lab/SetupVideos.
All the software works off windows and is reasonably intuitive. The demonstrators will
give you an introduction in the lab.
The quality of the data you get will be much lower than the data which would be acquired
in a proper clinical setting. However, if you see anything that concerns you in the data
you acquire, then please arrange a check up with your own doctor. No-one in the session
is qualified to give any diagnostic advice.
ASSESSMENT
B18: same as A-labs. Fill in the sections in the Lab record attached. You should get a
demonstrator to sign off your work after each exercise.
MSc: Long write up (see section at back). During the lab you should fill in the in the Lab
record.
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SECTION 1: PREPARATION
Write your answers in the first section (Preparation) of the Lab record before coming in
to the lab. MSc students – do as much as you can. You may not have had all the relevant
lectures yet.
P1: THE ECG AND THE CARDIAC CYCLE
Read through the section of your B18 physiology notes on the ECG and electrical activity
of the heart.
ECG signals are gathered to monitor heart activity. Normal commercial systems
have 12 leads, but we shall use just four (using one as an earth). The voltage gathered can
vary depending on the position of the electrodes on the body. If they are placed on the
heart muscle itself the potential may be as high as 110mV. On the skin close to the heart
they are typically around 5mV. However on the wrists and ankles, as in this experiment,
they may be as low as 1mV.
Fig 1.a and 1.2 below (from the B18/BME1 notes) show a simple model of the
heart and the three lead ECG placement. Until contact electrodes had been developed,
people had to place their limbs in buckets of salt water to form the connections!
Figure 1.1: heart electrical activity and
ECG leads
Fig 1.2: A typical trace
http://cvphysiology.com/Arrhythmias/A013a.htm
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Fig 1.3 shows and labels typical traces from a single cycle of ECG acquisition, together
with the typical time duration of significant regions. of each wave. Note the sign
convention for ECG:
‘A wave of depolarization travelling toward a particular electrode on the chest surface
will elicit a positive deflection’.
P-wave: 0.08-0.10 sec
QRS: 0.06-0.10 sec
P-R interval: 0.12-0.20 sec
Fig 1.3: A single cycle of ECG activity (from http://cvphysiology.com/Arrhythmias/A009.htm)
The following description of electrical activity is taken from the ADinstruments
LabTutor:
‘Cardiac contractions are not dependent upon a nerve supply. A group of weak muscle
cells (sinoatrial or sinuatrial node, SA node) acts as the pacemaker for the heart (Figure
1). These cells rhythmically produce action potentials that spread through the fibers of
the atria. The resulting contraction pushes blood into the ventricles. The only electrical
connection between the atria and the ventricles is via the atrioventricular (AV) node. The
action potential spreads slowly through the AV node (thus giving a time delay for
ventricular filling) and then rapidly through the AV bundle and Purkinje fibers to excite
both ventricles. The large muscle mass of the ventricles allows powerful contractions.’
Exercise: See Lab record P1
P2: EINTHOVEN’S TRIANGLE .
Read the section in your B18 physiology notes on Einthoven’s triangle. This
construction may in theory be used to reduce the number of leads required, or, with all
three leads, to estimate the electrical axis of the heart. Deviation of the electrical axis
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from the norm may be indicative of cardiac irregularities (although in the lab it is more
likely to be to do with the way you gather data!).
Fig 1.4 shows an idealised measurement of the three potentials on the heart. These
connections allow us to construct a vector sum, called Einthoven’s triangle.
Lead I + Lead III = Lead II.
Each channel is interpreted as a vector potential (remember that electric field, the basis of
voltage, has direction as well as magnitude).
LA, RA –left, right arm; LL = left leg
Fig 1.4: electrode placement for the standard 3-lead configuration and Einthoven’s
triangle construction
Exercise: See Lab record P2
P3: INSTRUMENTATION
This section relates to your A2 course on instrumentation (MSc students – you may not
be able to complete all this section).
Figure 1.5: Bio amplifier configuration
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Figure 1.5 shows a typical amplifier for acquiring bio-signals. In the system you use in
the lab the microprocessor couples to a PC and allows amplifier properties such as gain to
be set using a software interface (as you will find out in the lab). Identify the purpose of
the various components.
Exercise: See Lab record P3
P4: SIGNAL PROCESSING REVISION – FOURIER ANALYSIS AND
SAMPLING
Finally, refresh your memory on
(i) the Nyquist sampling criterion and
(ii) Decomposition of a periodic signal into the sum of harmonics (Fourier series –
you don’t need any detail)
Exercise: See Lab record P4
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SECTION 2: LABORATORY WORK
PRELIMINARIES
Computing:
You will be told in the session how to login and which directories to use. Use the official
lab username not your own so you get access to the right files.
Electrode Attachment
You will be given instructions during the lab session. The quality of your results is
highly dependent on how well you apply the electrodes. Apply them carefully and please
do not waste them. Please also keep the ECG electrodes on over lunch so that you can
reuse them in the afternoon.
SESSION A: ECG DATA ACQUISITION
In this session you will acquire ECG data from medical acquisition kit. You will:
Examine the effect of filters on ECG signals
Relate the signals to physiological changes
Investigate the use of the FFT in finding power spectra
Examine the effects of artefacts such as movement
The powerlab system consists of a bioamplifier, configured as two differential amplifiers,
and supporting Windows driven data acquisition and software. A schematic for a single
differential input is given in Fig 1.3.
Time for this session: about 1.5 hours
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SECTION A1 ECG SIGNALS
You will use disposable snap electrodes. As there are only two differential inputs in the
Biomed system you cannot acquire all three signals. Select one of your group to be the
subject, and put electrodes at the wrists (left: LA and right: RA) and the ankles (LL, RL).
You will need two electrodes on the right arm; put them next to each other. In theory it
does not matter if the electrode is at the top or bottom of a limb; the limb simply acts as a
conductor.
Connect them to the bioamp inputs as
follows:
Channel 1: +LA to –RA (black to white)
Channel 2: +LL to –RA (brown to red)
Earth: RL (green)
Make sure the polarities are correct
The subject should now sit quietly (but is expected to join in the analysis at the same
time!). Start the LabChart software to acquire the signals. If the signals are very noisy it
is probably because the electrodes are not making good contact.
Move the toggle button at the bottom right of the screen to ‘monitor’ to stop the software
recording.
EXERCISE A1: SET UP THE DISPLAY PARAMETERS
If the experiments gallery box pops up; close it.
You want to display just two waveforms (see Fig A1 below). If more are showing then do
the following:
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Go to Setup – Channel settings.
(i) Set the number of channels box (bottom left) to 2.
(ii) Check that the computed input is set to the right raw data inputs (look at the
bioamp inputs on the hardware; on some sets they are inputs 1, 2 and others
they are 3, 4.). If not, set them up correctly.
Now set up the other channel parameters
i. Set sampling frequency to 400Hz (top right button).
ii. Determine a suitable time scale for the horizontal axis on the screen – probably
you want a ratio of about 5:1 to display a few cycles.
iii. Determine a suitable vertical scale for each channel so the whole trace is
displayed (click the channel number to the right of the display; select input
amplifier)
Note your settings: Lab record Exercise A1
Fig A1
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EXERCISE A2: FILTERING – TIME AND FREQUENCY
(i) Remove all filters. Set the system to record and take a section of data (Start ..
stop). Make sure the PQRST complexes are visible in each trace (this checks
your connections).
(ii) Now apply a bandpass filter (bandpass, 0.3Hz – 30Hz) - see ‘set up input’ button,
Fig A.2. Use the default frequency transition band (frequency range over
which signal is attenuated from 1% to 99% attenuation), and a value of 20%
fc. The system uses a type of filter called a Kaiser window – a more flexible
type of filter to the one in the introduction. It allows sidebands to be
controlled as well as the attenuation. You may find too that there is a
significant delay until the trace appears. This is because the filter is
implemented as a digital filter and uses a number of input samples to create
each output – hence it needs to acquire a complete before it can start (after
that it only needs to acquire the new sample each time).
Lab record: Exercise A2.1 Note how the signal changes when the filter is applied
(iii) Now examine the frequency content of the signal through applying the FFT.
With the mouse, highlight a portion of the ECG trace on the screen which you
consider to be of good quality (take as many cycles as possible). Go to the
spectrum window. Select channel 1 or 2. The spectrum should be displayed.
Fig A2
Select
channel
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Use the set parameters button to alter the view mode to ‘display as connected
points’ (as in the diagram), and set the number of points to 16k. Use the zoom tool
(+/- buttons) to magnify the useful part of the display; select one of the frequency
scale markings and move it with the mouse). Ask for help if necessary.
Identify the main frequency components and observe the effect of changing the
number of samples you use in the FFT (use the Settings parameters button to
change the number of samples in the FFT, from 1k to 32k)..
** See Lab record: Exercise A2.2
EXERCISE A3 THE ECG TRACE
Select a suitable portion of data of one channel on the screen using the mouse. To select
two channels go to Commands and Selection; select the channels you want. Check the
print preview (under the File menu) to make sure that you are only printing out that
data - and print.
Measure the R-R cycle time of a few cycles and fill in the Table in Exercise A3.
Repeat this while you breathe regularly and deeply – does it alter?
** See Lab record: Exercise A3.
EXERCISE A4 ARTEFACTS
A number of patients are monitored continuously over 24hours using an ECG harness, to
measure the heart activity in daily life. In this section you look at the effects of two
artefacts which affect the signal. In each case record the signal over several seconds and
examine the spectrum over a few cycles.
1. Movement. Vibrate the hand at a few Hz (eg 5Hz simulates the tremor in
Parkinson’s disease). Make it as regular as you can so you will see it as a spike in
the spectrum. Note the effects in the time domain and the spectrum
2. Breathing. Can you observe a breathing frequency in the spectrum?
** See Lab record: Exercise A4.
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EXERCISE A5: EFFECT OF EXERCISE
1. Get the subject to jump up and down a few times to get the heart rate up (hold the leads
steady!) and examine the ECG signal as soon as he stops.
2. Use the Marker and Waveform Cursor to make the following time measurements from
the displayed waveform, as shown in Figure 3.
a) P-R time interval
b) QRS duration
c) S-T time interval
d) T-P time interval
e) Whole cycle time interval (R-R)
** See Lab record: Exercise A5.
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SESSION B (OPTIONAL FOR MSC STUDENTS)
In this session you will acquire data from a 3 lead ECG recording and then use it to
construct Einthoven’s triangle to estimate the angle of the electrical axis. A time to do
this will be assigned to you at the start of the laboratory session as you need to share
equipment.
Time for this session: about 1 hour
EXERCISE B1: DATA ACQUISITION
For this you use the bioradio kit. It is noisier than the other systems but it has more
channels. Use electrodes at each wrist and at each ankle (see B18_lab/videos).
ECG data collection
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(i) Set up the connections on the Bioradio using the black jumper leads as required shown
in the diagram above. Channels 1-3 record leads I – III.
(ii) Run the program PClab/B18/Capturelite. Press the green ‘START’ button (towards
top left of screen). Three channels of ECG activity should scroll across the screen.
(iii) Start the Capturelite software (Raw Data mode) to acquire the signals. You should
see 3 traces roll across the screen.
(iv) You may want to filter the data. To set filters use the button DSP settings (on the
right underneath DSP settings). Specify low pass filter, 4th
order, 30Hz for each channel.
Go back to the raw data screen and toggle the filter to on (click in the shadow area just
below the switch icon below the DSP settings).
See Lab record., Exercise B.1
EXERCISE B.1. ACQUIRE DATA:
Select save data.
Enter a filename. Save the data in a directory with your initials in the B18 Medical
Common Area
(i) The subject should sit down with arms apart.
Press Start. The data should roll across the screen. When you have enough, press Stop.
Check the file you created using Windows Explorer to make sure that it exists!
Collect data for about 20 secs. sitting quietly and still. Save in a file in your home
directory: filename. To save the data stop the trace. Press ‘save data’ and type in a
filename. Then press ‘start’ and saving will begin. To stop saving press ‘stop’
(ii) If time permits repeat with the subject lying down.
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EXERCISE B.2 EINTHOVEN’S TRIANGLE
(i) First load in the data you saved. In the main Matlab window change the directory
to Matlab/Mfiles, and import the file you saved (File – import data).
(ii) Plot the data: plot(filename) and identify a region containing about 3-4 spikes,
which looks of good quality. Transfer this region into a new variable:
ecg = filename(N1:N2,1:3);
where N1 and N2 are the sample numbers at the start and end of the region you
identified. .
Depending on the filters you used, the signal may be very messy still. The main sources
of contamination in the signal are likely to be close to d.c. and at 50Hz. It may be worth
doing some more filtering in Matlab.
(iii)To remove d.c. it is simplest to use the Matlab command detrend:
ecg0=detrend(ecg);
(iv) To remove the 50Hz signal, run a low pass filter for cut off frequency, fc, = 20Hz.
I suggest you use a fourth order filter and run the following Matlab code:.
norder =4;
fc=20;
ecg20=lpfilter(ecg0, norder, fs, fc);
(v) Plot leads I, II and III of one set of filtered data, using a new figure for each trace:
figure; plot(ecg20(:,1)); figure; plot(ecg20(:,2)); figure; plot(ecg20(:,3));
(vi) Determine the maximum value of the PQRS complex in each signal using the
Matlab data cursor in the figure window. To use the data cursor: click on the
figure and then on ‘Tools’. Choose ‘data cursor’. Move the cursor (with the
mouse) until you are over the point selected, then left click. The X and Y
values should be given; if not you are probably not over a point on the trace)
(vii) Now for each one determine the corresponding value of using the equation
in the introduction. You may want to use Matlab, for example
R1=[ value1, value2, value]; etc %values from lead 1; same for R2, R3
for i=1:3
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theta(i)=acos((R1(i)*R1(i)+R2(i)*R2(i)-R3(i)*R3(i))/(2*R1(i)*R2(i)))*180/pi
end;
mean_theta=average(theta)
var_theta=sqrt(var(theta));
See Lab record., Exercise B.2
(viii) If time permits gather data with the subject lying down and do the same
analysis.
See Lab record., Exercise B.3
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SESSION C: EEG DATA ACQUISITION
In this session you will acquire EEG data from the PowerLab kit as in the first
experiment. You will:
(i) Find the spectrum of EEG signals and relate the signals to physiological changes
(ii) Identify alpha waves on pre-recorded data
(iii) Identify alpha and possibly beta waves acquired in the session
(iv) Examine the effects of artefacts such as eye movement
Time for this session: about 1.5 hours
If you haven’t done so already, create a directory for yourselves in the common disk area
to save temporary data.
BACKGROUND
Figure C.1
Fig C.1 shows the structure of the cerebral cortex. Various types of information in the
form of nerve impulses are transmitted and processed. More details are given in the
handout: EEG-1 available in the lab. The EEG signal can be broken down into different
rhythms. The two frequency ranges you are hoping to observe are identified as primary
components as in the table below.
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Rhythm When it occurs Typical
frequency
Amplitude Where on brain
Alpha
Quiet, resting,
eyes closed
8-13Hz 2-100V Originate in
occipital lobe
Beta Mental activity;
alert to external
stimulus
13-22Hz 5-10V Parietal, frontal
lobes
THE 10-20 SYSTEM FOR EEG PLACEMENT
Data collection needs to be done carefully if good results are to be obtained; EEG signals
are much smaller than ECG signals. A method called the 10-20 system has been
developed for placement of electrodes on the scalp. The 10 and 20 refer to the percent
distances between the electrodes in proportion to the size of the head.
Fig C.2: electrode placement
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EXERCISE C1: PROCESSING AND EXAMINATION OF PRE-
STORED DATA
Start Matlab, Make sure you are in directory MATLAB/Mfiles. Load the files:
eyesopen_b18 and eyesclosed_b18 (ask a demonstrator if you don’t know how to).
These have been taken with electrodes across the occipital area of the brain (O1-Cz) with
sampling frequency fs=256Hz.
C1.1 EXAMINING THE DATA
Plot the first 128 samples of each file:
plot(eyesopen(1:128)); figure; plot(eyesclosed(1:128))
Find the spectrum through taking the FFT of each:
feopen=fft(eyesopen); feclosed=fft(eyesclosed);
Plot the spectrum up to 100Hz (note that fs=256Hz) using a routine plotf that picks out
the region from 0 to fmax Hz:
fmax=100;
plotf(feopen,fs,fmax); figure; plotf(feclosed,fs,fmax)
See Lab record., Exercise C.1.1
C.1.2 FILTERING – EYESCLOSED DATA
Although you may just see a spike at 10Hz in the eyesclosed file (corresponding to alpha
wave production) both signals are heavily contaminated by (simulated) 50Hz mains
signal and other artefacts. In this section you will use low pass filters to reduce this
effect. You also use the function detrend to remove any d.c. level.
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You are provided with the Matlab function lpfilter which implements a low pass
Butterworth filter with cut off frequency fc. Set the cut off frequency to 30Hz.
Experiment with different low pass filters on the eyesclosed signal. For example:
aclosed2=lpfilter(detrend(eyesclosed),2,fs,30); % second order filter
aclosed4=lpfilter(detrend(eyesclosed),4,fs,30); % 4th order
aclosed6=lpfilter(detrend(eyesclosed),6,fs,30); % 6th order
Plot the results of the filters
close all % closes all figures so far – up to you!
figure
subplot(3,1,1); plot(aclosed2(1:128))
subplot(3,1,2); plot(aclosed4(1:128));
subplot(3,1,3) ; plot(aclosed6(1:128));
and their spectra:
figure
subplot(3,1,1); plotf(fft(aclosed2),fs,100);
subplot(3,1,2) ; plotf(fft(aclosed4),fs,100);
subplot(3,1,3) ; plotf(fft(aclosed6),fs,100);
Print out the two sets of graphs and label each graph.
See Lab record., Exercise C.1.2
C.1.3 EYES OPEN DATA
There is no obvious structure in the eyesopen spectrum. It needs more rigorous filtering
to see any spectral information.
Use the 6th order low pass filter, and plot the result:
aopen6=lpfilter(detrend(eyesopen),6,fs,30); plotf(fft(aopen6),fs,100)
See Lab record., Exercise C.1.3
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EXERCISE C2: COLLECTING YOUR OWN DATA
See Fig C2. To collect EEG data you will place electrodes in positions FPz (centre
forehead), FP1 (left forehead), O1 (see diagram – about 10% above the inion, the
occipital bone) and A2 (mastoid on opposite side to FP1). Talk to a demonstrator and/or
watch the video EEG to see how to place the electrodes. Connect them to the bioamp
inputs as below.
Channel 1: O1-A2
Channel 2: FP1-A2
Earth: FPz
(connect a jumper lead
between the connectors for
A2)
Now run LabChart Powerlab software to display and acquire signals. If the experiments
gallery box pops up; close it.
Set up the channel parameters
i. Set sampling frequency to 200Hz (top right button).
ii. Determine a suitable time scale for the horizontal axis on the screen – probably
you want a ratio of about 5:1 to display a few cycles.
iii. Determine a suitable vertical scale for each channel so the whole trace is
displayed (click the channel number to the right of the display; select input
amplifier)
iv. Check the filters for each channel (button by ‘Low pass’ below). Add a bandpass
filter with low cut off frequency 1 Hz and high cut off frequency 20 Hz.
Note down your settings: See Lab record., Exercise C2
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EXERCISE C3: ARTEFACTS
You have already seen some causes of distortion in the signal. Because they are so small,
EEG signals are especially prone to artefact. Note the effects on the signal when the
subject does the following movements:
C.3.1 Blinking. The subject should do three quick blinks in succession.
C.3.2 Eye movement. (Electro-ocular effect) Eye movements cause a potential between
the cornea and the retina which you may be able to observe from the electrodes. The
subject should move their eyes rapidly from side to side, and up and down keeping their
head still.
C.3.3 Muscular movement. The subject should clench their teeth on and off
C.3.4 Deep breathing: The subject should breathe deeply and regularly. To see any
breathing effect you need to change the filter to a low pass filter with cut off 20Hz.
See Lab record., Exercise C3
EXERCISE C4.1: EYES CLOSED: ALPHA ACTIVITY
Give the subject a rest. He/she should relax and try to go to sleep (but must not actually
drop off!). Set the filter back to band pass, cutoff 20Hz and 1Hz.
Some tips:
close eyes, relax
lotus-type hand position (cross fingers, thumbs and small finger touching)
nobody behind the subject
lower head if necessary
concentrate on breathing
The other in the group should monitor the screen and subject. You should see a small
periodic pattern on the screen when the subject is producing alpha waves. Most people
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can produce alpha waves like this but a few just aren’t very good at it doing it on
demand!
Observe the signals in chart mode. Select a portion and find the spectrum. Alpha waves
normally give a clear peak around 10-12 Hz in this exercise. Alpha waves are the resting
state of the brain.
EXERCISE C4.2: IF TIME PERMITS: BETA ACTIVITY
If time permits you may want to see if you can observe changes beta activity. This is
harder: beta activity is the normal mode of the brain when you are awake. Try one of the
following to stimulate his intellectual activity:
Ask the subject to perform mental arithmetic tasks
Give a sequence of letters and ask him to count how many are repeated two letters on
(e.g. OIDRTRSCS – the second R and second S should be counted
In each case take a trace of the signal before and during the exercise and see if oyu cna
see any differences (beta waves are in the region 13-30Hz)
See Lab record. Exercise C.4
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For MSc BME1: LONG WRITEUP
An excellent write up need not be more than 6 pages (excluding printouts and the work in
the lab) as follows (the length of each section is provided as a guideline). In any case it
must not be more than 8 pages long. It should not include Appendices – you need to
decide which results to include in the main text (you will hand in your lab sheet at the
same time). Do not copy information from the sheet; summarise in your own words.
We are looking for
an understanding of how the ECG and EEG signals (in time and spectrum) depend on the
underlying physiology. You need not discuss EMG signals.
an understanding of the issues involved in collecting, processing and interpreting data
a description of signal artefacts (electrical and physiological)
Introduction: short description of how you can use ECG and EEG measurements to
monitor heart activity and brain waves, and the aim of the lab
Approx 0.5 pages
Methods. Practical issues on placement of electrodes, data monitoring (including
requirements from amplifiers, filter settings. Do not just repeat the lab sheet; use your
own words
Approx 1 pages
Results
For ECG: results and discussion of signals and spectra, relating them to physiology.
Effects of artefacts and movement (exercises B1.4,5), results from Einthoven’s triangle
(A1.4 and A1.5)
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For EEG: results and discussion of signals and spectra, relating them to physiology. The
effect of artefacts (eg blinking)
For both: discussion and results on the effects of filtering
Approx 3-4 pages
Sources of error
Approx 0.5-1 page
Discussion –Relate results and conclusions to the aims of the experiment. How useful is
this technique performed outside a clinic (eg for home monitoring)?
Approx 0.5-1page
References (see below)
The long write up should be handed in to the faculty office by the end of term. Include
the completed Lab record with your lab results.
References (should be in Engineering department library):
You should be able to complete the write up largely from notes and the handout for this
lab. For further information you may like to look at some of the following:
Physiology notes
Webster: Medical Instrumentation: Application and Design Sections on ECG (4.6),
EEG(4.8). Parts of chapter 5 on electrodes
From Biomedical Engineering Handbook (Vol 1):
- Principles of Electrocardiography, E.J. Berbari
- Principles of Electroencephalography, J.D. Bronzino
- Biomedical Signal Analysis, Banu Onaral, Section Editor
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Introduction, B. Onaral
Biomedical Signals: Origin and Dynamic Characteristics;
Frequency-Domain Analysis, A. Cohen