Design and Application of Software for Generating Simulated Signal Data

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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:

1

0

1m

l

DkDk l

m

(2)

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-

ples

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

value.

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

is

112

6

[] 11

2112

2211

6

DJ

TDij Jj Jj J

DJ jJ jJ jJ

DJ jJjJ jJ

DJ jJjJ jJ

2

(4)

if the value of J is equa l to an integer，we can get TD [i]

by the following equation:

TD iDj (5)

Finally, the number in sequence of TD [i] is equal to

samples.

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

MaxMin2

r

TD iA

NDS i

2

(6)

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

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