Low-Cost Short –Range Wireless Optical FSK Modem for Swimmers Feed.docx

Low-Cost Short –Range Wireless Optical FSK Modem for
Swimmers Feedback
Rabee M. Hagem1, David V. Thiel1,2*, Steven G. O’Keefe1
Thomas Fickenscher3
Andrew Wixted1,2
3Chair, High-Frequency Engineering, Helmut Schmidt
1Centre for Wireless Monitoring and Applications
University
2Centre for Excellence in Applied Sports Research
University of the Federal Armed Forces
Queensland Academy of Sport
Hamburg, Germany
Griffith University
Abstract—This paper reports 3 axis accelerometer datatransfer
over a one meter underwater path at 10 cm depth using a 2400
bps optical wireless frequency shift keying (FSK) at very low
frequency (VLF). The modulation frequencies used were 10 and
12 KHz. The prototype modem was designed and implemented
for real time feedback for swimmers in the pool. The optical
transmitter included an accelerometer unit with a
microcontroller, the modulator and a detector circuit based on
an integrated detector preamplifier (IDP). The cost of the
components for the optical transmitter and receiver was less
than AU$25. Range experiments were performed in air and
underwater, with and without bubbles. The received data was
error free for 1.3 m in air and for more than 1.1 m underwater

without bubbles. The underwater range decreased to 70 cm with
bubbles. The availability of the link between the wrist and head
of a swimmer was approximately 50% and varied with the
position of the wrist. This enables stroke rate data to be
presented to the swimmer via a goggle mounted display.
I. INTRODUCTION
The evaluation of swimmers can be performed wirelessly using
a small portable accelerometer/gyroscope unit with data
capture. Post processing allows interpretation of the swimming
data [1]. No previous work has been reported for optical real
time swimmer feedback. In training and longer swim events,
feedback to the swimmer using sensors can improve training
and performance by pre-setting the stroke rate and lap times and
providing the swimmer with visual information about their
current performance. The challenge is to achieve sufficient
communication distance underwater between the sensor unit and
a display unit mounted on the goggles.
II. LITERATURE REVIEW
Wireless communications between motion sensors placed on
various parts of the body of a swimmer can be used to provide
real time feedback through a heads-up display on the swimmer’s
goggles. A wrist-mounted accelerometer can provide data such
as stroke rate and lap time which can be used to improve
compliance with swimming strategies and training regimes. The
communications system between the wrist and the head must
achieve a maximum distance of
approximately 1 m. Radio frequency suffers from severe
attenuation in water and the antenna size is relatively large.
Acoustic communications has the disadvantages of relative low
speed and multipath problems. An optical wireless link can

provide a relatively high speed data rate with low attenuation in
the visible part of the spectrum. In particular green light has the
minimum attenuation through clear, still water [2]. The design
goals of the optical system in this paper were low cost, short
range and a low data rate. FSK with a VLF carrier frequency at
10 and 12 KHz were designed and implemented.
High power consumption and cost were reported in most optical
wireless communications systems reported in the literature.
Anguita et al [3] developed a point to point optical wireless
transceiver system based on using a blue LED as transmitter and
a photodiode as a receiver. A single board node was used in an
underwater wireless sensor network (UWSN) for
communications between the sensor nodes. Two Spartan-3
boards were used. A transmission distance of 1.8 m was
achieved with a data rate of 100 kbps.
Vasilescu et al [4] presented system hardware and software for
underwater wireless sensor networks using a mixture of optical
and acoustic communications to monitor coral reefs and
fisheries. The cost of an optical communication board was about
$50 per node while the acoustic modem was about $3000 per
node. For the optical node, the transmitter was Luxeon 5 LXHL-
PM02 with 532 nm green LED with about 700 mW radiated
power while consuming 6 W of the input power. The receiver
was a high speed PIN photodiode PDB -C156 with 8 mm2
surface area. The range achieved for the optical system was
about 2.2 m point to point with a cone of 30 degree with data
rate of 320 kbps and 8 m with a lens to concentrate the light
beam.
Lu et al [5] designed and implemented an underwater optical
wireless communication system with a range of between 5 to 10
m. Inexpensive components were used for the implementation of
the communication system with complex detection algorithms
including signal detection and clock synchronization. The cost

of this system was below
$ 15. The LED was the RL5-G13008 Super-Green LED with a
520 nm wavelength and the maximum operation power was 12
mW. The photodiode was a Silonex SLD-70 BG2A with a
maximum sensitivity at wavelength 550 nm and a sensitivity
spectral range from 400 nm to 700 nm. In addition, a BG filter
for infrared rejection was included with the photodiode. The
radiation beam half angle for the LED and the photodiode were
45 and 60 degrees respectively. The experimental results
showed that for 7 m, the detection probability was 100% while
at 10 m this reduced to 80%. The data rate was restricted by the
digital signal processing (DSP) board and was approximately
310 bps.
Schill et al [6] designed a small size optical communication
transceiver for a swarm of submersible robots. The combination
of the IrDA physical layer with a 3 W high power green and
blue LED in the visible spectrum was introduced. The
transmitter was a Luxeon III Emitter and the receiver was a
SLD-70BG2A which is sensitive to the wavelength range 400-
700 nm. The IRDA chip MCP2120 which includes encoder and
decoder was used at the transmitter and the receiver, while a
MAX3120 chip was used for amplification and filtering. The
communications was point to point and the cost of the
transmitter was about AU$45 per unit. An air and underwater
experiment was performed to assess the viability of the link at
different wavelengths of optical radiation. The maximum range
achieved in air with the cyan emitter was 2.02 m followed by
blue 1.71 m and green with 1.49 m. In water the range was
reduced to 1.7 m.
The optical system presented in this paper will be used to give
real time feedback to a swimmer about swim performance data
including stroke rate and lap times.
III. SYSTEM DESIGN

An underwater optical communications link budget is dependent
on the range, the attenuation through the water, the orientation
and directivity of the transmitter, the orientation and directivity
of the optical detectors, the transmitted power, the receiver
sensitivity and the effect of the ambient light in the pool [2].
The optical transmitter was a superflux green LED (λ = 520 nm)
with a +35o divergence angle and a 9500 mcd light intensity
which is equivalent to a radiated power of 1.5 mW [2]. XR-2206
was used as the FSK modulator at the transmitter. The optical
detector (transimpedance amplifier with a pin photodetector)
had a 0.3AW-1 responsivity at λ = 520 nm, and provides an
output voltage proportional to the incident optical power. XR-
2211 was used as a phase locked loop (PLL) and FSK
demodulator at the receiver. The receiver optical filter was the
cokin P004 centered on 510 nm in order to reduce the effect of
the ambient light [2]. The wireless sensor used to generate the
acceleration data was the nCore 2.0 designed by Davey et al [1].
Some hardware and software modification for this sensor were
required in order to connect it to the optical system.
The FSK optical link with a 3 axis accelerometer running at 50
samples per second was designed and tested in the pool. In
water without bubbles, the distance achieved was greater than
1.1 m and in bubbled water this distance decreased to 70 cm.
This range is sufficient for communications between the wrist
and the head of a swimmer allowing an optical display of the
processed data using a multi-colored LED mounted in the
goggles. Fig. 1 shows the block diagram for the transmitter and
fig. 2 shows the block diagram of the receiver.

Figure 1. Block diagram of FSK optical transmitter.
Figure 2. Block diagram of FSK receiver circuit. The RGB LED
is attached to the swimmer goggles.
IV. FREESTYLE SWIM CYCLE
Typically the stroke patterns for the freestyle swim stroke are
described in terms of six phases. Fig. 3 shows a side view for
these phases as determined by the position of the hand. The first
phase from 1-2 is the entry and stretch, the second is 2-3 phase
called downsweep to catch. The third phase 3 is called catch
and from 3-4 this is called the insweep. The next phase is the
upsweep from 4-5. The phase between positions 5-6 is called
the release and exit [7].

6
2 1
5
3
Figure 3. Side view of the phases of the stroke in freestyle
swimming.
V. EXPERIMENTAL DESIGN AND RESULTS
A number of range measurements were undertaken in order to
characterize the optical link before attaching the circuit to a
swimmer. The first experiment was conducted in air and the
distance achieved was greater than 1.3 m. The second
experiment was conducted in still water (i.e. clear water without
bubbles) with the transmitter and receiver both located 10 cm
below the water surface. The effect of total internal reflection
on the propagation path was clearly evident in the results. This
experiment achieved a link distance greater than 1.1 m. Fig. 4
shows the circuit and calibrated support frame at the side of a
swimming pool.

Figure 4. The experimental measurement system showing the
rigid mounting frame in a swimming pool used for range
measurements.
Range measurements in water with intense aeration were
conducted in a jet spa. This bubbled water experiment revealed
that the range decreased to 70 cm [2]. In this case the effect of
total internal reflection from the water surface is not significant
as the water surface is highly perturbed. This range is sufficient
for communications between the wrist and the head of a
swimmer. It was thought that the bubble density created by a
swimmer would be much less than that observed in the spa and
so the attenuation along the propagation path would be smaller.
The underwater observation of a freestyle swimmer shows
bubble formation, but the bubble density and bubble size
distribution is very dependent on the speed and style of the
swimmer.
The FSK VLF optical circuit was tested on a swimmer in air and
in water to check the availability of optical link in different
positions for the swimmer’s hand. The swimmer was asked to
lie face -down on the side of a bench and move his head and
arms in a manner which resembled freestyle swimming
(sometimes referred to as dry-land swimming). Fig. 5 shows the
y-axis of the acceleration data sent and received in real time in
air from the optical transmitter attached to a swimmers hand to
the optical receiver attached to his/her head. The acceleration
data was recorded in the wrist mounted device and also in the

head mounted device. The two recordings were matched to
deduce the periods of link failure. This is plotted as zero in the
dashed (red) line in Figure 5. The acceleration data clearly
shows the variation in acceleration due to the stroke cycle. This
characteristic variation in the acceleration can be used to
determine the time between successive strokes.
The percentage of time when the data was received was
calculated to be approximately 50% for this dry-land swimming
situation. Table 1 shows the percentage of received data for
different positions of the stroke in air.

Figure 5. Real time transmitted (continuous line/blue) and
received acceleration data (dashed line/red) from the wrist for
dry-land freestyle swimming. The propagation path was totally
air. The acceleration is relative to the earth’s gravitational
acceleration (g’s).
TABLE 1.Percentage of data received for different stroke
positions given in Fig. 3.
Positions
Definition
Percentage of
data received
1-2
Entry and
100%
stretch
2-3
Downsweep to
100%
catch

3
Catch
0%
3-4
Insweep
0%
4-5
Upsweep
0%
5-6
Release and
100%
exit
A recreational swimmer was asked to swim freestyle in the
pool. Fig. 6 shows the real time transmitted and received data
for one acceleration axis on the wrist. The location of the
transmitter on the wrist and the receiver on the head can be seen
in Figure 7. The stroke characteristics are clearly evident but
with more variability between strokes when compared to dry-
land swimming. The optical path is broken more frequently

when compared to the dry-land swimming. This is thought to be
the result of the effect of the roughness of the
water surface and the possibility that at some times the
transmitter and receiver are on opposite sides of the water
surface. The overall result however was that the reliability of
the communications link during freestyle swimming in the pool
was approximately 50%.
Figure 6. Real time transmitted (continuous line/blue) and
received acceleration data (dashed line/red) during freestyle
swimming in a swimming pool. The acceleration is normalized
to the earth’s gravitational acceleration (g’s).

Receiver
Transmitter
& sensor
Figure 7. Optical link trial in the swimming pool showing the
swimmer wearing the transmitter and the receiver circuits.
VI. CONCLUSIONS
A low cost, short range optical wireless communications system
using a green LED transmitter and IDP was designed and
implemented based on FSK modulation with VLF carrier signal
at 10 and 12 KHz. The optical link was tested and the stroke
phases for freestyle swimming were investigated in order to
check the percentage of received data for different arm
positions. The results showed that the link was error free for
approximately 50% of the time.
The prototype system described can be improved through a

reduction in the size of both the transmitter and the receiver.
Future work will be directed towards the design of the goggles
feedback system in order to give a real time feedback to a
swimmer. An investigation of the communications from a
swimmer to pool side is important to allow interactions from the
coach to the swimmer. The deployment of more than one
movement sensor located in different places on the body (eg
wrist, sacrum and ankle etc) requires a network of sensors. This
will give additional information about the swimmer
coordination, movement and speed. The optical link is suitable
for a body-centric wireless sensor network.
ACKNOWLEDGMENTS
This work was conducted as part of Rabee Hagem’s Ph.D.
program. He is supported by the MHED scholarship granted by
Iraqi government. The authors also wish to thank the
Queensland Academy of Sport for the facilities provided for the
various experiments, and Dr. Daniel A. James for helping
during these tests. This work has been supported by a research
grant from the Australian Research Council. This research was
conducted under Griffith University Ethics Protocol number
ENG 05 10 HREC.
REFERENCES
N. Davey, D. James, A. Wixted, Y. Ohgi, "A low cost self
contained platform for human motion analysis," in The Impact
of Technology onSport II, F. K. Fuss, et al., Eds., London:
Taylor & Francis, 2008, pp.101-111.
R. Hagem, D. Thiel, S. O'Keefe, T. Fickenscher, "The effect of
air bubbles on an underwater optical communications system for
wireless sensor network applications", Microwave & Optical
Tech. Letters.submitted, 2011.
D. Anguita, D. Brizzolara, G. Parodi "Building an Underwater
Wireless Sensor Network Based on Optical: Communication:

Research Challenges and Current Results," in Sensor
Technologies andApplications, 2009. SENSORCOMM '09.
Third International Conference on Sensor Technologies and
Applications, 2009, pp. 476-479.
I. Vasilescu, K. Kotay, D. Rus, M. Dunbabin, P. Corke "Data
collection, storage and retrieval with an underwater sensor
network," presented at the Proceedings of the 3rd ACM
international conferenceon embedded networked sensor systems,
San Diego, California, USA,2005.
F. Lu, S. Lee, J. Mounzer, C. Schurgers "Low-cost medium-
range optical underwater modem: short paper," presented at the
Proceedingsof the Fourth ACM International Workshop on
UnderWater Networks,Berkeley, California, 2009.
[6] F. Schill, U. Zimmer, J. Trumpf "Visible Spectrum Optical
Communication and Distance Sensing for Underwater
Applications,"
Proc. Australasian Conf. Robotics & Automation, 2004.
E. W. Maglischo, Swimming fastest, Human Kinetics:
Champaign, IL, 2003.
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YOUR ASSIGNMENT
YOUR FINAL SUBMISSION:
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TEMPLATE. You cannot use any other template.
ALL Matlab Code that implements your program.

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copy your matlab .m files to that directory copy your data to
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ASSIGNMENT
1004ENG Computing & Programming with Matlab 2014 S1
Assignment
This assignment requires some programming and plotting
activities. The assignment requires some understanding of the
discrete maths implementation of integration and differentiation

(which will be explained)
SCENARIO:
Your assignment is based around data collected from some kind
of sensor measuring 3D displacement or velocity or
acceleration. You are required to convert from one of these
kinematic types to the other types eg: if you are given
displacement, then you would be converting to velocity AND
acceleration. If you were given velocity then you would be
converting to both acceleration AND displacement. If you were
given acceleration then you would be converting to both
velocity AND displacement
BACKGROUND MATH / PHYSICS
The position vector, r (or s), the velocity vector, v, and the
acceleration vector, a are expressed using rectangular
coordinates in the following way:

How are these related :
If r or v or a are described by functions then each is either the
integral or the differentiation of another, as below, calculating v
from the derivative of r and a from the derivative of v.
Conversely, as below, v is calculated as the integral of a, r is
calculated as the integral of v.
BUT: in sensor based data, these are not continuous functions
but discrete samples and the maths iscompletely simplified.
vi=
(ri−ri−1)

=(ri −ri−1)∗ samplerate
t
In the above, the average velocity at a point in time, is the
change in position ( r ) divided by
the change in time (
t ). The change in time is simply the inverse of the samplerate
(eg 1/samplerate). Using matlab, if the displacement samples
are loaded in a vector, then to generate the velocity the vector is
subtracted from a one sample shifted copy of itself and the
resultant
matlab vector multiplied by the samplerate (eg t =
1/samplerate and dividing by t is the
same as multiplying by samplerate.
Eg: for a samplerate of 10 samples / sec
r=[0.15, 0.3, 0.45, 0.61, 0.77, 0.94, 1.1 ] (metres)
then we assume for the moment that r0 is zero and get:
v=[0.15-0, 0.3-0.15, 0.45-0.3, 0.61-0.45, 0.77-0.61, 0.94-0.77,
1.1-0.94]*samplerate
v=[1.5, 1.5, 1.5, 1.6, 1.6, 1.7, 1.6]

BUT: subtracting zero from the first sample can cause the first
velocity (or acceleration) calculation to be anomalous. It is
better to generate the differences between each pair of samples
and the resultant data set will be one sample shorter than the
source data.
To calculate the integral requires the summing of successive
samples and multiplying by t (or
divide by the samplerate)
i
i
∑ vn
ri=∑(vn
t )=
1
samplerate
1
for example, if the velocity vector was:

v=[ 1.5, 1.5, 1.5, 1.6, 1.6, 1.7, 1.6 ]
then
r=[1.5, 3.0, 4.5, 6.1, 7.7, 9.4, 11 ] /samplerate.
Each of you will receive an individual assignment in the form of
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load X42
ASSIGNMENT
ASSIGNMENT =
data: [3x4321 double] samplerate: 100
TimeSeriesIn: 'rows' units: 'm/s^2'
currentData: 'acceleration' requiredData: 'velocity'
requiredUnits: 'm/s'
>>
>> ASSIGNMENT.data(:,1:6)
ans =

-0.0010
-0.0020
-0.0029
-0.0039
-0.0048
-0.0056
0.0049
0.0099
0.0151
0.0203
0.0257
0.0312
-0.0646
-0.1292
-0.1938
-0.2584
-0.3230
-0.3876
>>
In the above example, the data is in rows and represents
acceleration. The student receiving this assignment is required
to convert the data from acceleration to velocity AND to
displacement..
(Note: in the above example, the variable
ASSIGNMENT.currentData tells us that the data represents
acceleration and is in m/s2.)
The important descriptors of the data are below.
data: [3x4321 double] samplerate: 100

TimeSeriesIn: 'rows' units: 'm/s^2'
currentData: 'acceleration'
Some students will also have instructions describing the X,Y &
Z channels such as 'length', 'height', 'width'. In this case, these
descriptors should be used in the appropriate places eg a 3D
plot would include all 3 descriptors, one on each axis eg: height
(m).
Ignore the fields “requiredData” and “requiredUnits”
Your final units should be metres (m) for displacement, metres-
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Your report WILL include a flowchart and a structure chart
describing your program.
Your results will includeCheck-sum of the 3 channels of

original data. ((3 checksums) (sum of each channel data))
Mean of each channel for each of the three steps (displacement,
velocity, acceleration)
Mean of the magnitude of the data for each of the three steps.
Your results will include the first three figures listed below and
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Figures your program must produce.
A figure with 3 sub-plots representing the 3 channels of original
data. A figure with a 3D plot of the original data.
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(vector length eg (sqrt(x^2+y^2+z^2)
(1st Processing Step eg velocity)(depends on your specific
question)
A figure with 3 sub-plots representing the 3 channels of
processed data. A figure with a 3D plot of the processed data.
A figure with one plot with the magnitude of the processed data.
(2nd Processing Step eg acceleration)(depends on your specific
question) A figure with 3 sub-plots representing the 3 channels
of processed data. A figure with a 3D plot of the processed data.
Each Graph MUST HAVE the axis labelled with the name and
units (if no labels have been given, label the channels 'X', 'Y',
'Z'). The figure must be titled. Graphs need grid lines AND 3D
plots need to have a 1:1:1 aspect ratio. (use “help” to
understand this)
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built-in functions where possible except:

You must write your own function to produce the graphs (eg the
graphing code only occurs once in a separate function m-file,
not three times in your program.
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(and/or differentiation) (eg the integration code is in a separate
function m-file, not in your main program. These functions must
use looping to perform their calculations.
For one type of graph of your choosing, write programming to
add a special grid line marking some special value (such as a
minimum value or a maximum value or mean value (something
of significance)).
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code using a command similar to one used in Lab 2. eg: print(‘-
dpng’,’q2a.png’);
Exporting your graphs will simplify importing them into your
word processor..
Use the above list as a checklist.Make sure you include ALL the
required information and outputs.
ASSIGNMENT CODING
The assignment will cover many areas of Matlab coding.
There will be a requirement to:
load data
inspect the data
process the data
display the data
save the results

This will involve the following coding:
for loops
matrix manipulation
use of statistical tools
plotting (2D and 3D)
use of built in functions
use of your own functions
NOTE WELL:
In your programming you cannot use built in differentiation or
integration functions but must make your own functions and
perform the differentiation and / or integration using looping
code.
Programming Hints:
To aid you in your programming here are a few summary points.
You will need a function that plots data.
It will plot a figure with three subplots .
It will plot a figure that represents a 3D representation of data.
It will plot a 3D magnitude.
The figures will all be labelled and titled.
It will add additional useful information to a figure of your
choice.
It will save the figures to disk so you can import them to your
word processor.
Since your graphing function will be plotting data for three
different types of input (displacement, velocity and
acceleration) it not only needs to accept input data but also a
text message of the data type.
You will need either one or two other functions; written by you,
that do integration of a set ofdata or differentiation of data. If
you receive velocity information you will require both
functions, if you receive displacement or acceleration data, you

will only require one of the two functions (which function
depends on your data).
Your main program will call your functions to convert your data
to the other two forms of the dataand to plot the three figures
associated with each of the three forms.
Because of the above, you will create 3 or 4 (or more if you
wish) matlab “m” files.
Errors:
If any of your graphs are a straight line or two straight line
segments then you have made a mistake. and confused a row for
a column or visa-versa. Do not forget to include the check-sum
and mean values. Make sure you can tick off every item in the
checklist.
Marking:
On the previous page is a check list. For every item you don't
supply, you lose marks.
If you don't supply the four page report with sensible text
correctly formatted, spell-checked and grammar checked you
lose marks.
If you copy code or text from another student you get NO
marks.
If you purchase your assignment from the internet, another
student or any other source you get NO marks.

Inertial sensor orientation for cricket bowling monitoring.
Abstract— Inertial sensors are a potential method of
measuringthe elbow angle during cricket bowling, currently an
indicator of illegal bowling. To detect the elbow angle it was
necessary to orient sensors relative to the elbow axis. An elbow
orientation exercise was developed and the sensor orientation
relative to the elbow axis calculated for upper-arm, forearm and
wrist mounted sensors for different muscle loading and wrist
rotation. Inertial rate-gyroscope outputs were compared for
sensors before and after adjustment for elbow-axis orientation.
This output was compared to the results obtained from a Vicon
motion capture analysis system.
Adjusting the sensor orientation based on the output from the
orientation exercise improved the correlation between outputs
of the upper-arm and forearm sensors but also indicated that the
sensors were susceptible to muscle loading and wrist rotation
effects that will need to be accounted for in any sensor based
illegal bowling detection system.
INTRODUCTION
Cricket bowlers suspected of bowling with an illegal action are
assessed in technology intensive motion capture laboratories.
This is an expensive process and generally limited to players at
the elite level. Low cost inertial sensors have the potential to
detect illegal bowling in situ, which would make bowling
assessment available to developing players and provide
opportunity for remediation. Illegal bowling involves the
extension (“straightening”) of the elbow in excess of 15 degrees
during the bowling action. There are potentially multiple ways
to detect illegal bowling using inertial sensors but the required
accuracy is likely to be influenced by numerous factors
including an individual’s bowling action and arm morphology.

We have shown that for a legal delivery featuring the hand
upward at the arm horizontal position and where the hand
continues to face forward during the delivery arc, the output of
inertial rate-gyroscopes mounted on the forearm and upper-arm
tracked together [1]. The outputs of accelerometers also tracked
proportionally. For an illegal delivery where the elbow starts
flexed and straightens as the arm comes forward there is a
distinct divergence in the gyroscope outputs as well as a phase
shift in accelerometer outputs.
Other deliveries start with the arm back but with the wrist or
arm rotated and the hand facing downward. Some deliveries
have internal and external rotation of the arm as the shoulder
rotates. Some bowlers, due to their anthropometry, cannot fully
straighten their elbow and can use an upper-arm internal
rotation to gain speed at the wrist [2]. Some bowlers deliver the
ball with the back of their arm facing the batsman, using a wrist
rotation or wrist extension to direct the ball forward. Illegal
bowling actions tend to occur at different points in the delivery.
As described above, fast bowlers may start the bowling action
with the elbow flexed; any type of bowler may experience a
flex-extend action as the arm approaches vertical, or, for slower
bowlers bowling with the back of the arm facing the batsman (a
“doosra”), elbow extension can be used through ball release [3].
Further complications arise because the elbow joint is not a
simple hinge joint. Some bowlers have elbows that can bend
sideways (abduction and adduction) or backwards
(hyperextension).
There are numerous issues related to detecting illegal bowling
with inertial sensors. These include identifying the critical time
points of arm horizontal and ball release during bowling action
[4], confirming that sensor outputs match the existing standard
of motion capture, calibrating the sensors to the arm,
identifying the most appropriate arm position for sensors and

understanding how the sensor orientation is affected by the
changes in muscle tension and wrist position.
This paper reports on a simple elbow axis alignment technique
and the effect of wrist rotation and muscle tension on the sensor
alignment. A sensor to elbow axis alignment factor was applied
to upper -arm and forearm mounted gyroscopes and the output
of these sensors compared for known good and illegal
deliveries. Analysis of elbow angle is ongoing work and will
not be addressed in this paper.
METHOD
Sensors were developed using the highest specification devices
available at the time. The sensors included a ± 100g
accelerometer (Analog Devices ADXL190) aligned to capture
the arm’s centrifugal acceleration. Orthogonal to this was a dual
axis ± 18g accelerometer (Analog Devices ADXL321). Also
included were 3 axes of ± 2000 deg/s rate gyroscopes
This work is funded by the International Cricket Council (ICC)
and the Marylebone Cricket Club (MCC) with funding
administered by Cricket Australia.
(Inversense IDG650). The 100g accelerometer was a relatively
large device (12x10x3 mm) and the direction of sensing
required the chip to be mounted orthogonal to the arm’s surface.
This subsequently affected the packaging size (Fig.1). A Hall
Effect device was used to capture external magnetic pulses
which were used for synchronization of the sensors. Data were
logged to an on-board 2G Byte flash memory for later
downloading. A lithium polymer battery capable of sustaining
continuous operation for 40 minutes was included.
Y channel, labeled ‘Pitch’ in this diagram. Misalignment of the
sensor relative to the axis of rotation would result in signals on
the other channels. For example, if the sensor had some roll

applied, the orientation exercise would generate signal on both
the pitch and yaw axes. By analyzing the signal on all three
channels, the alignment of the sensor to the elbow axis could be
extracted.
Figure 1. Wrist sensor mounted on motion capture marker
cluster. The cluster base was attached with double sided tape
and then secured with tape. The sensor was similarly attached
and secured. The sensor package size was due to the verticaly
mounted sensor board (hidden by tape).
The sensor tests were performed in conjunction with existing
3D motion capture bowler testing procedures where 11 bowlers
performed a mixture of their bowling actions with a total of 24
deliveries each. Sensors were located on the back of the wrist
and the back of the forearm and upper -arm, either side of the
elbow (Fig.2a). The sensor on the wrist was attached to a
motion-capture cluster of markers (Fig.1) allowing direct

comparison between the outputs of the sensor and the motion
capture system. Sensors either side of the elbow axis were
attached with double sided tape but then held on firmly using
medical tape around the arm segment. The sensors and the
motion capture system were run at 200Hz sampling.
An elbow axis calibration procedure was performed where the
upper arm was held still and the elbow repeatedly flexed and
extended (Fig.2a). For two bowlers this was performed with the
wrist in three different orientations, with the hand supinated
(palm up), with the hand vertical and with the hand pronated
(palm down) (Fig.2b). The set of three flex and extend exercises
was repeated with the bowlers holding a 5kg weight. The
resultant data were processed to extract the angles of the sensor
relative to the elbow axis of rotation for each combination of
weight and wrist rotation. The upper-arm sensor was also
calibrated to the elbow axis with a single set of flex-extend
repetitions. These were performed with the forearm held firmly
in position and the upper-body rocking back and forth to create
the flex-extend motion.
Assuming an arrangement sensor location relative to axis of
rotation such shown in Fig.3, the arm flex-extend exercise,
where one arm segment is fixed, created a fixed axis of rotation
for the sensor on the moving segment. For a triaxial gyroscope
this arrangement would result in signal only on the

Figure 2. (a) Upper-arm and forearm sensor mounting with
effect of flex and extend exercise illustrated. (b) Arm, looking
from below, with hand moving from supinated to pronated
position. The solid line was drawn on with a ruler, the dashed
line represents an estimate of the arm centre line. In
(a) the sensors were physically closer to the elbow point than
illustrated.
Initially the above method was trialed on a wooden arm with
sensors arranged at different orientations. The extracted angles
were compared with angles obtained from analysis of the
photographs of the sensors in-situ. Pitch angle cannot be
resolved in the absence of other misalignments because the
orientation calibration routine only generates signal on the pitch
axis.
PROCESSING
Sensor Calibration
Accelerometers were calibrated used the six point stationary
orientation method [5]. Gyroscopes were calibrated by rotating
them a fixed number of times on a turntable and then scaling the
result so the integrated angle matched the angle of rotation.
This was performed for each axis.

Figure 3. Axes of gyroscope sensor relative to axis of rotation
(elbow joint). For a pure hinge joint only the Y (pitch) axis
should detect rotation.
B. Sensor Orientation
Rapid flexing and extending of the elbow with the upper arm
held stationary generated signals on the wrist and forearm
gyroscopes and accelerometers. For the purpose of this
processing it was assumed that the elbow was a one degree of
freedom hinge joint.
The processing for angle extraction involved two steps. The
first step generated estimated angles of sensor pitch, roll and
yaw from the magnitude of the signal on each channel. This
estimate was then used with an iterative process to optimize the
sensor orientation angles.
Initially an envelope detector using a Hilbert transform was
used to estimate the signal magnitudes for the angle extraction.
A simplified method of only calculating the angle when the
signal exceeded some threshold appeared to give a better
starting point. Angles were calculated using the arc-tan trig
function where the signal on two channels was used to estimate
the angle of the third. This process is outlined below:
Find samples where the signal on any channel exceeds the
threshold.

Calculate the pitch, roll and yaw angle for each sample from
above using the arc-tan trig function.
Average the results for each angle.
The approximate angles from the above process were then used
as the starting position of an iterative process to find the angles
that produced maximum RMS signal on the pitch axis and the
minimum RMS signal on the yaw and roll axes of the
gyroscopes. This process was repeated for the six combinations
of wrist position and weight for the forearm and wrist sensors.
The process was also used to calculate the orientation angle of
the upper-arm sensor.
IV. RESULTS
Two aspects of the results were considered: (1) the effect of
adjusting sensor output by the orientation angles on the
relationship of the forearm and upper-arm sensors, and (2), the
effect of muscle tension and wrist rotation on the sensor
orientation.
A. Comparison of gyroscope outputs
Unadjusted gyroscope outputs from the forearm and upper-arm
sensors sometimes showed poor correspondence even for legal
bowling actions (Fig.4a). After orientation calibration
adjustment the signals became more correlated at the critical
points of the bowling action. Fig.4 and Fig.5 show the pitch
axis of the forearm and upper-arm gyroscopes for a legal and an
illegal delivery as defined by the motion capture analysis.
Although elbow angle was not entirely dependent on this axis, it
was a good indicator of bowling techniques where the forearm
and upper-arm were moving together.
B. Effect of muscle tension and wrist rotation on sensor
orientation

Orientation angle results for the forearm and wrist sensors of
two bowlers are reported in tables 1 to 4. An example of the
gyroscope signal before and after orientation adjustment
appears in Fig.6. As was expected for the wrist sensor, the
main orientation changes were recorded on the roll axis. As the
wrist pronated the attached sensor went with it. The amount of
roll at the wrist (Tables 2 & 4) indicated less flexibility than
was anticipated, with one bowler only producing 91 to 93
degrees of forearm pronation at the wrist and the other 104-107
degrees.
Figure 4. Gyroscope sensor “pitch” axis signal for a typical
legal bowling action before (a) and after (b) adjustment of
orientation angle.

Figure 5. Gyroscope sensor “pitch” axis signal for an illegal
bowling action before (a) and after (b) adjustment of orientation
angle.
TABLE I.
BOWLER 1 – FOREARM SENSOR

Position
Supinated
Vertical
Pronated
Load
Yaw
Pitch
Roll
Yaw
Pitch
Roll
Yaw
Pitch
Roll
No_weight
0
0
0
3
-1

6
12
0
-22
Weight
1
-8
4
4
-4
-3
12
11
-21
For all tables, the supinated, no weight condition is the
reference or zero value.
TABLE II.
BOWLER 1 – WRIST SENSOR

Position
Supinated
Vertical
Pronated
Load
Yaw
Pitch
Roll
Yaw
Pitch
Roll
Yaw
Pitch
Roll
No_weight
0
0
0

-6
-16
-49
-14
-33
-104
Weight
0
-6
0
-7
-14
-52
-10
-44
-107
TABLE III.
BOWLER 2 – FOREARM SENSOR

Position
Supinated
Vertical
Pronated
Load
Yaw
Pitch
Roll
Yaw
Pitch
Roll
Yaw
Pitch
Roll
No_weight
0
0
0
2

-8
-6
6
-15
-14
Weight
0
-8
2
1
-9
-6
6
3
-15
TABLE IV.
BOWLER 2 – WRIST SENSOR
Position

Supinated
Vertical
Pronated
Load
Yaw
Pitch
Roll
Yaw
Pitch
Roll
Yaw
Pitch
Roll
No_weight
0
0
0
-4
-19
-59
1
4
-93
Weight

-1
-4
-2
-2
-16
-56
2
-1
-91
Figure 6. (a) The raw wrist sensor gyroscope signal and (b) the

rotated signal for the flex-extend exercise for the unloaded
supinated hand.
For the forearm sensor mounted at the elbow there was
substantial movement of the sensor. Both muscle tension and
wrist rotation affected the sensor orientation. Muscle tension
predominately affected the pitch of the sensor and wrist rotation
predominately affected the roll and yaw of the sensor. The
amount of the roll, as a percentage of wrist rotation, increased
with increasing wrist rotation.
For some bowlers during bowling, the recorded rotation rates
exceeded the specification for the gyroscopes. This applied to
any sensor location. Recorded acceleration for the wrist sensor
for some bowlers exceeded the 18g specification of the
transverse accelerometer axes.
DISCUSSION
While adjusting for sensor orientation improved the alignment
of signals in Fig.4, it did not bring both sensors into complete
alignment through the critical period. Inspection of the other
channels of the gyroscope indicated wrist rotation occurred and
from the results above relating to wrist rotation, the forearm
sensor was most probably changing orientation through the
bowling action. While some types of bowling deliveries could
potentially be monitored now, simply turning the wrist changed
the relationship of the sensors to each other and therefore
affected the ability to interpret the output. Using rigid-body
common-mode-rejection based models for angle extraction
requires that the sensor is firmly attached to its segment and
that there is only one degree of freedom. Sensors
mounted on the arm moved about on all three axes therefore a
movement detection and compensation algorithm would need to
be developed.

The flex-extend exercise took the elbow through approximately
135 degrees and would have generated some dynamic
morphology related sensor orientation changes. A smaller range
of movement generated insufficient signal to extract any angles
reliably. The changes would have contributed to error in the
extracted orientation angle and were probably a source of some
of the noise in Fig.6b (rotated signal). The flex-extend process
could also explain the limited range of measured roll at the
wrist (Tables 2&4) as a fully flexed elbow limits forearm
pronation and a fully extended elbow limits forearm supination
[6]. The flex-extend exercise would result in these limits
applying concurrently.
During these trials, the sensors were taped on the arm and it
could be assumed that the taping made the sensor respond, at
least in part, to movements of the arm cross section at that
point. In the future it is expected that smaller, lower profile
sensors would be used for in-situ monitoring which will require
thorough investigation of the best methods to attach them to
minimize soft tissue artifact.
VI. CONCLUSIONS
Some form of elbow-axis to sensor orientation calibration
process was necessary and this exercise appeared beneficial.
Sensor mounting location, muscle loading and longitudinal
rotation of the forearm all influenced the data generated from
the inertial sensors during functional movements and the cricket
bowling action. Work is ongoing to minimize the effect of these
factors to allow inertial sensors to be used as a bowling training
aid and illegal action assessment tool. Work is also ongoing to
understand which aspects of the movement are individual or
generic so on-field monitoring with inertial sensors is effective
in cricket.
REFERENCES

Wixted AJ, Spratford W, Davis M, Portus M, James DA, 2010,
Wearable sensors for onfield near real-time detection of illegal
bowling actions, in Proc Conference of Science, Medicine &
Coaching in Cricket, Ed Portus M. pub. Cricket Australia.
Melbourne, Australia, 165-168
Marshall R, Ferdinands R, 2003,The Effect of a Flexed Elbow
on Bowling Speed in Cricket,Sports Biomechanics,2:1,65—71
Chin A, Elliott B, Alderson J, Lloyd D, Foster D, The off-break
and "doosra": kinematic variations of elite and sub-elite bowlers
in creating ball spin in cricket bowling, Sports Biomech. 2009
Sep;8(3):187-98.
Wixted AJ, Portus M, James DA, Spratford W, Davis M, 2010,
Towards a wearable cricket bowling sensor. Proceedings:
Eleventh International Symposium on the 3D Analysis of
Human Movement, San Francisco, USA July 2010
Lai A, James DA, Hayes JP, Harvey EC, Semi-automatic
calibration technique using six inertial frames of reference, In:
Abbott D, Eshraghian K, Musca C, Pavlidis D, Weste N, editors.
Microelectronics: Design, Technology, and Packaging; Proc.
SPIE, 2004, Vol. 5274:531-542
Shaaban H, Pereira C, Williams R, Lees VC, 2008, The effect of
elbow position on the range of supination and pronation of the
forearm. J.Hand Surgery 33E:1:3–8
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dot to separate compound units, e.g., “A·m2.”
Helpful Hints
Figures and Tables
Because IEEE will do the final formatting of your paper, you do
not need to position figures and tables at the top and bottom of
each column. In fact, all figures, figure captions, and tables can
be at the end of the paper. Large figures and tables may span
both columns. Place figure captions below the figures; place

table titles above the tables. If your figure has two parts,
include the labels “(a)” and “(b)” as part of the artwork. Please
verify that the figures and tables you mention in the text
actually exist. Please do not include captions as part of the
figures. Do not put captions in “text boxes” linked to the
figures. Do not put borders around the outside of your figures.
Use the abbreviation “Fig.” even at the beginning of a sentence.
Do not abbreviate “Table.” Tables are numbered with Roman
numerals.
Color printing of figures is available, but is billed to the
authors. Include a note with your final paper indicating that you
request and will pay for color printing. Do not use color unless
it is necessary for the proper interpretation of your figures. If
you want reprints of your color article, the reprint order should
be submitted promptly. There is an additional charge for color
reprints. Please note that many IEEE journals now allow an
author to publish color figures on Xplore and black and white
figures in print. Contact your society representative for specific
requirements.
Figure axis labels are often a source of confusion. Use words
rather than symbols. As an example, write the quantity
“Magnetization,” or “Magnetization M,” not just “M.” Put units
in parentheses. Do not label axes only with units. As in Fig. 1,
for example, write “Magnetization (A/m)” or “Magnetization
(Am1),” not just “A/m.” Do not label axes with a ratio of
quantities and units. For example, write “Temperature (K),” not
“Temperature/K.”
Multipliers can be especially confusing. Write “Magnetization
(kA/m)” or “Magnetization (103 A/m).” Do not write
“Magnetization (A/m) 1000” because the reader would not
know whether the top axis label in Fig. 1 meant 16000 A/m or
0.016 A/m. Figure labels should be legible, approximately 8 to
12 point type.

References
Number citations consecutively in square brackets [1]. The
sentence punctuation follows the brackets [2]. Multiple
references [2], [3] are each numbered with separate brackets
[1]–[3]. When citing a section in a book, please give the
relevant page numbers [2]. In sentences, refer simply to the
reference number, as in [3]. Do not use “Ref. [3]” or “reference
[3]” except at the beginning of a sentence: “Reference [3]
shows ... .” Please do not use automatic endnotes in Word,
rather, type the reference list at the end of the paper using the
“References” style.
Number footnotes separately in superscripts (Insert |
Footnote).[footnoteRef:2] Place the actual footnote at the
bottom of the column in which it is cited; do not put footnotes
in the reference list (endnotes). Use letters for table footnotes
(see Table I). [2: It is recommended that footnotes be avoided
(except for the unnumbered footnote with the receipt date on the
first page). Instead, try to integrate the footnote information
into the text.]
Please note that the references at the end of this document are
in the preferred referencing style. Give all authors’ names; do
not use “et al.” unless there are six authors or more. Use a space
after authors’ initials. Papers that have not been published
should be cited as “unpublished” [4]. Papers that have been
accepted for publication, but not yet specified for an issue
should be cited as “to be published” [5]. Papers that have been
submitted for publication should be cited as “submitted for
publication” [6]. Please give affiliations and addresses for
private communications [7].
Capitalize only the first word in a paper title, except for proper
nouns and element symbols. For papers published in translation
journals, please give the English citation first, followed by the
original foreign-language citation [8].

Abbreviations and Acronyms
Define abbreviations and acronyms the first time they are used
in the text, even after they have already been defined in the
abstract. Abbreviations such as IEEE, SI, ac, and dc do not have
to be defined. Abbreviations that incorporate periods should not
have spaces: write “C.N.R.S.,” not “C. N. R. S.” Do not use
abbreviations in the title unless they are unavoidable (for
example, “IEEE” in the title of this article).
Equations
Number equations consecutively with equation numbers in
parentheses flush with the right margin, as in (1). First use the
equation editor to create the equation. Then select the
“Equation” markup style. Press the tab key and write the
equation number in parentheses. To make your equations more
compact, you may use the solidus ( / ), the exp function, or
appropriate exponents. Use parentheses to avoid ambiguities in
denominators. Punctuate equations when they are part of a
sentence, as in
(1)
Be sure that the symbols in your equation have been defined
before the equation appears or immediately following. Italicize
symbols (T might refer to temperature, but T is the unit tesla).
Refer to “(1),” not “Eq. (1)” or “equation (1),” except at the
beginning of a sentence: “Equation (1) is ... .”
Other Recommendations
Use one space after periods and colons. Hyphenate complex
modifiers: “zero-field-cooled magnetization.” Avoid dangling
participles, such as, “Using (1), the potential was calculated.”
[It is not clear who or what used (1).] Write instead, “The

potential was calculated by using (1),” or “Using (1), we
calculated the potential.”
Use a zero before decimal points: “0.25,” not “.25.” Use “cm3,”
not “cc.” Indicate sample dimensions as “0.1 cm 0.2 cm,” not
“0.1 0.2 cm2.” The abbreviation for “seconds” is “s,” not
“sec.” Do not mix complete spellings and abbreviations of
units: use “Wb/m2” or “webers per square meter,” not
“webers/m2.” When expressing a range of values, write “7 to 9”
or “7-9,” not “7~9.”
A parenthetical statement at the end of a sentence is punctuated
outside of the closing parenthesis (like this). (A parenthetical
sentence is punctuated within the parentheses.) In American
English, periods and commas are within quotation marks, like
“this period.” Other punctuation is “outside”! Avoid
contractions; for example, write “do not” instead of “don’t.”
The serial comma is preferred: “A, B, and C” instead of “A, B
and C.”
If you wish, you may write in the first person singular or plural
and use the active voice (“I observed that ...” or “We observed
that ...” instead of “It was observed that ...”). Remember to
check spelling. If your native language is not English, please
get a native English-speaking colleague to carefully proofread
your paper.Some Common Mistakes
The word “data” is plural, not singular. The subscript for the
permeability of vacuum µ0 is zero, not a lowercase letter “o.”
The term for residual magnetization is “remanence”; the
adjective is “remanent”; do not write “remnance” or “remnant.”
Use the word “micrometer” instead of “micron.” A graph within
a graph is an “inset,” not an “insert.” The word “alternatively”
is preferred to the word “alternately” (unless you really mean
something that alternates). Use the word “whereas” instead of
“while” (unless you are referring to simultaneous events). Do
not use the word “essentially” to mean “approximately” or
“effectively.” Do not use the word “issue” as a euphemism for
“problem.” When compositions are not specified, separate
chemical symbols by en-dashes; for example, “NiMn” indicates

the intermetallic compound Ni0.5Mn0.5 whereas “Ni–Mn”
indicates an alloy of some composition NixMn1-x.
Be aware of the different meanings of the homophones “affect”
(usually a verb) and “effect” (usually a noun), “complement”
and “compliment,” “discreet” and “discrete,” “principal” (e.g.,
“principal investigator”) and “principle” (e.g., “principle of
measurement”). Do not confuse “imply” and “infer.”
Prefixes such as “non,” “sub,” “micro,” “multi,” and “ultra” are
not independent words; they should be joined to the words they
modify, usually without a hyphen. There is no period after the
“et” in the Latin abbreviation “et al.” (it is also italicized). The
abbreviation “i.e.,” means “that is,” and the abbreviation “e.g.,”
means “for example” (these abbreviations are not italicized).
An excellent style manual and source of information for science
writers is [9]. A general IEEE style guide and an Information
for Authors are both available at
http://www.ieee.org/web/publications/authors/transjnl/index.ht
ml
Editorial Policy
Submission of a manuscript is not required for participation in a
conference. Do not submit a reworked version of a paper you
have submitted or published elsewhere. Do not publish
“preliminary” data or results. The submitting author is
responsible for obtaining agreement of all coauthors and any
consent required from sponsors before submitting a paper. IEEE
TRANSACTIONS and JOURNALS strongly discourage courtesy
authorship. It is the obligation of the authors to cite relevant
prior work.
The Transactions and Journals Department does not publish
conference records or proceedings. The TRANSACTIONS does
publish papers related to conferences that have been
recommended for publication on the basis of peer review. As a
matter of convenience and service to the technical community,
these topical papers are collected and published in one issue of
theTRANSACTIONS.
At least two reviews are required for every paper submitted. For

conference-related papers, the decision to accept or reject a
paper is made by the conference editors and publications
committee; the recommendations of the referees are advisory
only. Undecipherable English is a valid reason for rejection.
Authors of rejected papers may revise and resubmit them to the
TRANSACTIONS as regular papers, whereupon they will be
reviewed by two new referees.
Publication Principles
The contents of IEEE TRANSACTIONS and JOURNALS are
peer-reviewed and archival. The TRANSACTIONS publishes
scholarly articles of archival value as well as tutorial
expositions and critical reviews of classical subjects and topics
of current interest.
Authors should consider the following points:
1) Technical papers submitted for publication must advance the
state of knowledge and must cite relevant prior work.
2) The length of a submitted paper should be commensurate
with the importance, or appropriate to the complexity, of the
work. For example, an obvious extension of previously
published work might not be appropriate for publication or
might be adequately treated in just a few pages.
3) Authors must convince both peer reviewers and the editors of
the scientific and technical merit of a paper; the standards of
proof are higher when extraordinary or unexpected results are
reported.
4) Because replication is required for scientific progress, papers
submitted for publication must provide sufficient information to
allow readers to perform similar experiments or calculations
and use the reported results. Although not everything need be
disclosed, a paper must contain new, useable, and fully
described information. For example, a specimen’s chemical
composition need not be reported if the main purpose of a paper
is to introduce a new measurement technique. Authors should
expect to be challenged by reviewers if the results are not
supported by adequate data and critical details.
5) Papers that describe ongoing work or announce the latest

technical achievement, which are suitable for presentation at a
professional conference, may not be appropriate for publication
in a TRANSACTIONS or JOURNAL.
Conclusion
A conclusion section is not required. Although a conclusion
may review the main points of the paper, do not replicate the
abstract as the conclusion. A conclusion might elaborate on the
importance of the work or suggest applications and extensions.
Appendix
Appendixes, if needed, appear before the acknowledgment.
Acknowledgment
The preferred spelling of the word “acknowledgment” in
American English is without an “e” after the “g.” Use the
singular heading even if you have many acknowledgments.
Avoid expressions such as “One of us (S.B.A.) would like to
thank ... .” Instead, write “F. A. Author thanks ... .” Sponsor
and financial support acknowledgments are placed in the
unnumbered footnote on the first page, not here.
References
[1] G. O. Young, “Synthetic structure of industrial plastics
(Book style with paper title and editor),” in Plastics, 2nd
ed. vol. 3, J. Peters, Ed. New York: McGraw-Hill, 1964, pp.
15–64.
[2] W.-K. Chen, Linear Networks and Systems (Book style).
Belmont, CA: Wadsworth, 1993, pp. 123–135.
[3] H. Poor, An Introduction to Signal Detection and
Estimation. New York: Springer-Verlag, 1985, ch. 4.
[4] B. Smith, “An approach to graphs of linear forms
(Unpublished work style),” unpublished.
[5] E. H. Miller, “A note on reflector arrays (Periodical style—
Accepted for publication),” IEEE Trans. Antennas Propagat., to
be published.
[6] J. Wang, “Fundamentals of erbium-doped fiber amplifiers
arrays (Periodical style—Submitted for publication),” IEEE J.
Quantum Electron., submitted for publication.
[7] C. J. Kaufman, Rocky Mountain Research Lab., Boulder,

CO, private communication, May 1995.
[8] Y. Yorozu, M. Hirano, K. Oka, and Y. Tagawa, “Electron
spectroscopy studies on magneto-optical media and plastic
substrate interfaces (Translation Journals style),” IEEE Transl.
J. Magn.Jpn., vol. 2, Aug. 1987, pp. 740–741 [Dig. 9th Annu.
Conf. Magnetics Japan, 1982, p. 301].
[9] M. Young, The Techincal Writers Handbook. Mill Valley,
CA: University Science, 1989.
[10] J. U. Duncombe, “Infrared navigation—Part I: An
assessment of feasibility (Periodical style),” IEEE Trans.
Electron Devices, vol. ED-11, pp. 34–39, Jan. 1959.
[11] S. Chen, B. Mulgrew, and P. M. Grant, “A clustering
technique for digital communications channel equalization using
radial basis function networks,” IEEE Trans. Neural Networks,
vol. 4, pp. 570–578, Jul. 1993.
[12] R. W. Lucky, “Automatic equalization for digital
communication,” Bell Syst. Tech. J., vol. 44, no. 4, pp. 547–
588, Apr. 1965.
[13] S. P. Bingulac, “On the compatibility of adaptive
controllers (Published Conference Proceedings style),” in Proc.
4th Annu. Allerton Conf. Circuits and Systems Theory, New
York, 1994, pp. 8–16.
[14] G. R. Faulhaber, “Design of service systems with priority
reservation,” in Conf. Rec. 1995 IEEE Int. Conf.
Communications, pp. 3–8.
[15] W. D. Doyle, “Magnetization reversal in films with biaxial
anisotropy,” in 1987 Proc. INTERMAG Conf., pp. 2.2-1–2.2-6.
[16] G. W. Juette and L. E. Zeffanella, “Radio noise currents n
short sections on bundle conductors (Presented Conference
Paper style),” presented at the IEEE Summer power Meeting,
Dallas, TX, Jun. 22–27, 1990, Paper 90 SM 690-0 PWRS.
[17] J. G. Kreifeldt, “An analysis of surface-detected EMG as
an amplitude-modulated noise,” presented at the 1989 Int. Conf.
Medicine and Biological Engineering, Chicago, IL.
[18] J. Williams, “Narrow-band analyzer (Thesis or Dissertation
style),” Ph.D. dissertation, Dept. Elect. Eng., Harvard Univ.,

Cambridge, MA, 1993.
[19] N. Kawasaki, “Parametric study of thermal and chemical
nonequilibrium nozzle flow,” M.S. thesis, Dept. Electron. Eng.,
Osaka Univ., Osaka, Japan, 1993.
[20] J. P. Wilkinson, “Nonlinear resonant circuit devices (Patent
style),” U.S. Patent 3 624 12, July 16, 1990.
[21] IEEE Criteria for Class IE Electric Systems (Standards
style), IEEE Standard 308, 1969.
[22] Letter Symbols for Quantities, ANSI Standard Y10.5-1968.
[23] R. E. Haskell and C. T. Case, “Transient signal propagation
in lossless isotropic plasmas (Report style),” USAF Cambridge
Res. Lab., Cambridge, MA Rep. ARCRL-66-234 (II), 1994, vol.
2.
[24] E. E. Reber, R. L. Michell, and C. J. Carter, “Oxygen
absorption in the Earth’s atmosphere,” Aerospace Corp., Los
Angeles, CA, Tech. Rep. TR-0200 (420-46)-3, Nov. 1988.
[25] (Handbook style) Transmission Systems for
Communications, 3rd ed., Western Electric Co., Winston-Salem,
NC, 1985, pp. 44–60.
[26] Motorola Semiconductor Data Manual, Motorola
Semiconductor Products Inc., Phoenix, AZ, 1989.
[27] (Basic Book/Monograph Online Sources) J. K. Author.
(year, month, day). Title (edition) [Type of medium]. Volume
(issue). Available: http://www.(URL)
[28] J. Jones. (1991, May 10). Networks (2nd ed.) [Online].
Available: http://www.atm.com
[29] (Journal Online Sources style) K. Author. (year, month).
Title. Journal [Type of medium]. Volume(issue), paging if
given. Available: http://www.(URL)
[30] R. J. Vidmar. (1992, August). On the use of atmospheric
plasmas as electromagnetic reflectors. IEEE Trans. Plasma Sci.
[Online]. 21(3). pp. 876–880. Available:
http://www.halcyon.com/pub/journals/21ps03-vidmar

First A. Author (M’76–SM’81–F’87) and the other authors may
include biographies at the end of regular papers. Biographies
are often not included in conference-related papers. This author
became a Member (M) of IEEE in 1976, a Senior Member (SM)
in 1981, and a Fellow (F) in 1987. The first paragraph may
contain a place and/or date of birth (list place, then date). Next,
the author’s educational background is listed. The degrees
should be listed with type of degree in what field, which
institution, city, state, and country, and year degree was earned.
The author’s major field of study should be lower-cased.
The second paragraph uses the pronoun of the person (he
or she) and not the author’s last name. It lists military and work
experience, including summer and fellowship jobs. Job titles are
capitalized. The current job must have a location; previous
positions may be listed without one. Information concerning
previous publications may be included. Try not to list more than
three books or published articles. The format for listing
publishers of a book within the biography is: title of book (city,
state: publisher name, year) similar to a reference. Current and
previous research interests end the paragraph.
The third paragraph begins with the author’s title and last
name (e.g., Dr. Smith, Prof. Jones, Mr. Kajor, Ms. Hunter). List
any memberships in professional societies other than the IEEE.
Finally, list any awards and work for IEEE committees and
publications. If a photograph is provided, the biography will be
indented around it. The photograph is placed at the top left of
the biography. Personal hobbies will be deleted from the
biography.
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Your REPORT
You must process the data as required and present your results
in a written document using the IEEE template on the portal*.
Your report should follow the IEEE format. There is a dummy
version of how your assignment might be put together and two
actual IEEE conference papers that you can use as models.
*You will download the template and edit it. Delete the existing
text as you write your own text. The template on the portal is a
Microsoft Word docx file with track-changes turned on. When
you submit your electronic file, it will be checked for the
changes and the author.

Your report will be four pages long. You will include a fifth
page with all 9 graphs listed below.
You Must Have (in your report):
Your report WILL include a flowchart and a structure chart
describing your program.
Your results will includeCheck-sum of the 3 channels of
original data. ((3 checksums) (sum of each channel data))
Mean of each channel for each of the three steps (displacement,
velocity, acceleration)
Mean of the magnitude of the data for each of the three steps.
Your results will include the first three figures listed below and
any additional figure of yourchoice. All the figures will appear
in your additional page.
Figures your program must produce.
A figure with 3 sub-plots representing the 3 channels of original
data. A figure with a 3D plot of the original data.
A figure with one plot with the magnitude of the original data.
(vector length eg (sqrt(x^2+y^2+z^2)
(1st Processing Step eg velocity)(depends on your specific
question)
A figure with 3 sub-plots representing the 3 channels of
processed data. A figure with a 3D plot of the processed data.
(2nd Processing Step eg acceleration)(depends on your specific
question) A figure with 3 sub-plots representing the 3 channels
of processed data. A figure with a 3D plot of the processed data.

Each Graph MUST HAVE the axis labelled with the name and
units (if no labels have been given, label the channels 'X', 'Y',
'Z'). The figure must be titled. Graphs need grid lines AND 3D
plots need to have a 1:1:1 aspect ratio. (use “help” to
understand this)
You must also provide your original matlab code. You must use
built-in functions where possible except:
You must write your own function to produce the graphs (eg the
graphing code only occurs once in a separate function m-file,
not three times in your program.
You must write your own function to do the numeric integration
(and/or differentiation) (eg the integration code is in a separate
function m-file, not in your main program. These functions must
use looping to perform their calculations.
For one type of graph of your choosing, write programming to
add a special grid line marking some special value (such as a
minimum value or a maximum value or mean value (something
of significance)).
You can export your graphs automatically from your matlab
code using a command similar to one used in Lab 2. eg: print(‘-
dpng’,’q2a.png’);
Exporting your graphs will simplify importing them into your
word processor..
Use the above list as a checklist.Make sure you include ALL the
required information and outputs.
ASSIGNMENT CODING

The assignment will cover many areas of Matlab coding.
There will be a requirement to:
load data
inspect the data
process the data
display the data
save the results
This will involve the following coding:
for loops
matrix manipulation
use of statistical tools
plotting (2D and 3D)
use of built in functions
use of your own functions
NOTE WELL:
In your programming you cannot use built in differentiation or
integration functions but must make your own functions and
perform the differentiation and / or integration using looping
code.
Programming Hints:
To aid you in your programming here are a few summary points.
You will need a function that plots data.
It will plot a figure with three subplots .
It will plot a figure that represents a 3D representation of data.
It will plot a 3D magnitude.
The figures will all be labelled and titled.
It will add additional useful information to a figure of your
choice.
It will save the figures to disk so you can import them to your

word processor.
Since your graphing function will be plotting data for three
different types of input (displacement, velocity and
acceleration) it not only needs to accept input data but also a
text message of the data type.
You will need either one or two other functions; written by you,
that do integration of a set ofdata or differentiation of data. If
you receive velocity information you will require both
functions, if you receive displacement or acceleration data, you
will only require one of the two functions (which function
depends on your data).
Your main program will call your functions to convert your data
to the other two forms of the dataand to plot the three figures
associated with each of the three forms.
Because of the above, you will create 3 or 4 (or more if you
wish) matlab “m” files.
Errors:
If any of your graphs are a straight line or two straight line
segments then you have made a mistake. and confused a row for
a column or visa-versa. Do not forget to include the check-sum
and mean values. Make sure you can tick off every item in the
checklist.
Marking:
On the previous page is a check list. For every item you don't
supply, you lose marks.
If you don't supply the four page report with sensible text

correctly formatted, spell-checked and grammar checked you
lose marks.
If you copy code or text from another student you get NO
marks.
If you purchase your assignment from the internet, another
student or any other source you get NO marks.

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