Journal of Software Engineering and Applications, 2012, 5, 836-840 Published Online October 2012 (
Design and Application of Software for Generating
Simulated Signal Data
Longcong Chen1, Gaiqin Liu2, Bin Gao1, Ping Chen1, Shixiong Deng1, Xingliang Xiong1*
1Laboratory of Forensic Medicine and Biomedical Information, Chongqing Medical University, Chongqing, China; 2School of Opto-
electronic Information, Chongqing University of Technolog y, Chongqing, China.
Email: *
Received August 10th, 2012; revised September 12th, 2012; accepted September 24th, 2012
Simulated signal, produced by digital to analog converter, is important and necessary in many fields, such as electronic
experiment, equipment debugging and maintenance, especially, in medical area. In this paper, the design and applica-
tion of an effective software which may be used to generate simulated signal data by special wave picture obtained by
scanner or drawing software are presented. First, we introduce how to realize producing needed data that meet the g iv en
conditions including amplitude, samples and resolution by this software. Second, the method and steps of getting the
stimulated signal data from wave figure file is given. Third, an example of application about this software to generate
simulated physiolo gical signal data is shown. Then , the data are put into use and by digital to analog converter, an idea
stimulated signal is produced. Therefore, with full confidence, we could draw a conclusion that it is very convenient and
effective to get needed data for digital to analog conversion to generate all kinds simulated signal with a novel method.
Keywords: Digital to Analog Converter; Wave Picture; Simulated Signal
1. Introduction
In many fields, which include electronic experiment and
testing, equipment debugging and maintenance, medical
teaching, many special stimulated signals are often nee-
ded. Take in medical equipment debugging as an exam-
ple, the all kinds of normal and abnormal physiologic
stimulated signals, such as electrocardiosignal, electro-
encephalosignal, pulse wave signal, are often applied to
test whether or not the medical equipment work properly.
As is known to all, all sorts of stimulated signals are
often achieved by using digital-to-analog converter (DAC)
which needs the corresponding signal digital data. With
DAC, Lee, W. T., Vasan, B. K., etc. got demanded sig-
nals [1-4], and Dajun Tian acquired ECG simulated sig-
nals [5], and Quan Zhao gained General Radar RF Signal
[6,7]. Moreover, the digital data is acqu ired through ana-
log to digital converter (ADC) or graph paper. For thro-
ugh the ADC, we must have corresponding original sig-
nal source as its input, while if not, we can get nothing
about the digital data o f stimulated sign al. With this way,
we must get original signal and face the problem—how
and where to get it. As a result, it is not convenient and
the resolution and samples of signals, which are limited
by ADC, are fixed. For through the coordinate paper,
getting digital data is inefficient by hand. if only a few
signals, this method is possible, but if there are a few
dozen signals and each needs hundreds of samples or
more, the workload is too big to complete and the effi-
ciency is too low.
On the whole, the two ways to obtain simulated signal
data (SSD) are not very efficient and convenient. To
overcome the disadvantage, we designed this software,
which can be used conveniently and easily, to generate
automatically SSD with deferent samples, resolution and
2. Methods
2.1. Procedure of Getting Digital Data
The procedure of getting needed digital data, which in-
clude four steps, is shown in Figure 1. The function of
every step is introduced below.
1) The first step is obtaining gray images, which must
include wave pattern and can be gained by scanning from
book and paper, or by drawing software such as Photo-
shop, MSPaint, Coredraw, CAD an d so on.
2) Digital image processing, the second step, is aimed
at only keeping the needed wave pattern and wiping out
other unexpected area and dots in picture, which, without
double, can be erased manually by drawing software.
*Corresponding a uthor.
Copyright © 2012 SciRes. JSEA
Design and Application of Software for Generating Simulated Signal Data 837
Obt ainin g gray
Digita l image
Converting image
to signal data
Figure 1. The procedure of getting digital data.
3) Converting image to signal data is the third step and
its goal is changing wave pattern to digital data for gen-
erating corresponding stimulated signal.
4) The last step, the fourth step, is data processing in
order to meet user’s conditions, such as amplitude, sam-
ples and so on, and save needed digital data to files.
2.2. Processing Algorithm
The processing algorithm is essential and necessary for
us to obtain digital data of simulated signal from an im-
age that include needed wave pattern. The algorithm ge-
nerally consists of the following five steps:
2.2.1. Linear Spatial Filtering
Spatial filtering includes linear and non linear ones [7]. In
this software, only averaging linear spatial filter, which is
simply the average of pixels contained in the neighbor-
hood of the filter mask, has been designed. By replacing
the value of every pixel in an image by the average of the
gray levels in the neighborhood defined by the filter mask ,
this process results in an image with reduced “sharp”
transitions in gray levels. Because random noise typically
consists of sharp transitions in gray levels, the obvious
result of this filtering is noise reduction, blur edges and
reduce irrelevant detail in an image. We designed three
kinds of averaging filter masks, and two of which are 3 ×
3 (Figure 2(a)) and 5 × 5 (Figure 2(b)). The third is n ×
n, whose value may be set by input dialogue box.
The basic goal of linear spatial filtering is wiping out
noise and reducing irrelevant detail in an image.
2.2.2. Image Binarization
The binarization process involves using a threshold op-
eration. Pixels with grey level below the predetermined
threshold are assigned a value of “1”, which is of maxi-
mum brightness and whose display is pure white in im-
age, while all others were designated a value of “0”,
whose display is pure black. The essential purpose of this
procedure is to erase some pixels which are not needed.
The threshold, whose default value is three hundred, may
be set by input dialog ue b ox .
2.2.3. Morphonological Binary Image Processing
The basic operations of morphonological binary image
processing have dilation, erosion, opening and closing.
Dilation expands an image and can bridge certain gaps,
while erosion shrinks it and can eliminate irrelevant de-
tail or isolated small area. Opening generally smoothes
the contour of an object, breaks narrow isthmuses, and
eliminates thin protrusions. Closing also tends to smooth
sections of contours but, as opposed to opening, it gener-
ally fuses narrow breaks and long thin gulfs, eliminates
small holes, and fills gaps in contour. In this software we
designed those four basic operations to be use, and user
can choice anyone if image processing is necessary. For
each operation, there are three kinds of algorithms, which
are small disk (Figure 3(a)), large disk (Figure 3(b)) and
rectangle (Figure 3(b)), and whose structuring elements
are respectively shown in Figure 3.
Our primary aim of morphonological binary image pro-
cessing is that only the needed wave pattern can be kept
while other unexpected area and dots must be wiped out
in picture by those operations. Certainly, we can erase
manually to meet this purpo se by drawing software.
2.2.4. Conversion of Changing Wave Patt er n t o
Digital Data
In an image of including wave pattern, X axis is th e equ-
ivalent of time axis in signal waveform, which corresp-
onds to the sampling sequence in digital signal, and Y
axis is the size of the equivalent of digital signal. There-
fore, we can easily obtained corresponding digital data of
(a) (b)
Figure 2. The averaging filter mask: (a) Shows 3 × 3 aver-
aging filter mask; (b) Shows 5 × 5 averaging filter mask.
(a) (b) (c)
Figure 3. The basic operations of morphonological binary
image processing: (a) Shows structuring element of small
disk; (b) Shows structuring element of large disk; (c) Shows
structuring element of rectangle.
Copyright © 2012 SciRes. JSEA
Design and Application of Software for Generating Simulated Signal Data
each sample by regarding each column as one sample,
and the average position of black pixels in each column
as one value of corresponding sample or column in digi-
tal signal. In the actual conversion, taking into account
the graphics that may be scanning, we can obtain three
data for every column in an image: the top one which is
the minimum coordinate value of Y axis of black pixels
in the column; the bottom one which is the maximum
coordinate value of Y axis of black pixels in the column;
the average one which is the average of the top and the
bottom of each column. Moreover, we looked upon the
average value of each column as the digital data of cor-
responding column or sample. In addition, because the
coordinate value of Y axis gradually enlarge from top to
bottom in an image while the valu e of digital data in sig-
nal waveform lessen little by little from top to bottom,
value of the real digital data should equal to the subtrac-
tion of height of the image and the value of the digital
data. The equation can be defined as
DHM (1)
where D presents the real digital data, H is the height of
the image and M presents the value of the digital data.
To each column, we can get real digital data, th erefo re,
a group of digital data sequences (DDS), which may be
presented by D [n] and in which n means the total num-
ber of data, can be obtained from the whole image.
2.2.5. Di gital Da ta Processing
The DDS, which are produced directly through wave
pattern image often can’t meet given conditions; there-
fore, it is necessary for the digital filtering and changing
to stimulate signal data. In this software, we design an
average digital filter, and it’s equation is:
DkDk l
where k presents the order of digital data in sequences, m
is the number of averaging data, which can set by input
dialogue box. By this processing, the total number of the
data (TMD) is equal to n-m, the unexpected sharp transi-
tions can be reduced or eliminated, and an ideal wave
pattern digital data may be obtained.
For meeting the user’s requirements, we apply the fol-
lowing two steps conversion:
1) Converting the number of DDS to the needed sam-
Because the number of DDS usually can’t meet user’s
demand, we must covert the number of that to meet the
need by the following algorithm. It is
1jiTMD NN 1 (3)
where NN is the number of needed data which are equal
to samples, it is the order of needed data, which can
change from 0 to NN – 1, TMD presents the total number
of the data obtained after digital filtering, j is a float
Then, if the value of j isn’t eq ual to an integer, we can
get an integer J, which meets inequality: J < j < J + 1.
We can get the value of TD [i] by using Lagrange’s
interpolation formula for four neighbor data, whose order
is J – 1, J, J + 1, J + 2. Lagrange’s interpolation formula
 
[] 11
TDij Jj Jj J
DJ jJ jJ jJ
DJ jJjJ jJ
DJ jJjJ jJ
  
if the value of J is equa l to an integerwe can get TD [i]
by the following equation:
TD iDj (5)
Finally, the number in sequence of TD [i] is equal to
2) Converting the DDS to the needed ones
The data of meeting g iven cond itions can b e gained by
the following equ ation:
Min 2
NDS i
where NDS [i] is DDS, Max is the maximum value in TD
[i] and Min is the minimum value in TD [i], r presents
the number of bits, A is the amplitude of needed data.
Through this digital data processing, we can get all
needed data, which meet user’s demand, and save to a
file for using.
3. Application
In order to show how to apply the software, we gave
examples of generating simulated physiological signal
data. The processing generally consists of the following
three steps:
1) By scanning from a book, we obtained a gray image
and saved to a file named avr_1.bmp.
2) The file was loaded to this software by using “Op en
Bitmap” in menu, and then we could see the wave pattern
shown in the main window and some unexpected small
areas, lines and dots (Figure 4(a)). By using some opera-
tions in order of spatial filter with 5 × 5 averaging filter
mask, image binarization, morphonological binary image
processing of erosion and opening, we got the image
shown in Figure 4(b). Finally, unexpected areas, lines,
dots were wiped out and only the needed wave pattern
was kept in an image. Of course, we can erase manually
Copyright © 2012 SciRes. JSEA
Design and Application of Software for Generating Simulated Signal Data
Copyright © 2012 SciRes. JSEA
unexpected part in an image by drawing software, such
as Photoshop, MSPaint and so on.
3) Through “Bitmap Data” in menu of the software,
changing wave pattern to digital da ta was completed, and
red curve presents waveform of data sequences (Figure
4(c)). After we choose resolution, data formation (in-
cluding C/C++ and ASM langue) and set the value of
amplitude (2000), samples (1000), resolution (12 bits),
the needed simulated signal data sequences could be ob-
tained by clicking “Needed Data” in menu. Finally we
had obtained the needed data sequences, whose wave-
form was shown in Figure 4(d), and saved correspond-
ing data to a file for DAC.
The last, we show the result (Figure 4(e)) of output
after DAC and low pass filter. There has little difference
between the wave pattern in image and the waveform of
output after DAC and low pass filter. Therefore, with full
confidence, we could draw a conclusion that it is very
convenient and effective to get needed data for digital to
analog conversion to generate all kinds of SSD.
Figure 4. An example for application of the software. (a) Shows a gray image of scanning from a paper; (b) Shows image after
digital image processing; (c) Shows red waveform of data sequences; (d) Shows red waveform of needed data sequences; (e)
Shows signal waveform by DAC and low pass filter.
Design and Application of Software for Generating Simulated Signal Data
4. Discussions and Conclusions
In this paper, the method of generating SSD by special
wave picture obtained by scanner or drawing software is
presented. At the same time, an example of application
about this software to generate simulated physiological
signal data has demonstrated that it is very convenient
and effective to get needed data for digital to analog
conversion to generate all kinds of SSD.
The presented methods can obtain SSD without the
corresponding original signal source, we believe that it
has a good potential for application for generating signal
data by DAC and filter, or for getting data from wave-
5. Acknowledgements
This work was supported by Department of Biomedicine
Engineering in Chongqing Medical University, and au-
thors would like to thank Dr. Fengpeng Jia at the First
Affiliated hospital of Chongqing Medical University for
his help in affording all kinds of physiological signal
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