CN109171694A - A kind of diabetic condition appraisal procedure and system based on pulse signal - Google Patents
A kind of diabetic condition appraisal procedure and system based on pulse signal Download PDFInfo
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- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
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- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7271—Specific aspects of physiological measurement analysis
- A61B5/7275—Determining trends in physiological measurement data; Predicting development of a medical condition based on physiological measurements, e.g. determining a risk factor
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Abstract
The invention discloses a kind of diabetic condition appraisal procedure and system based on pulse signal by obtaining pulse signal, and the characteristic index of the corresponding pulse signal of acquisition, and obtain the characteristic index of pulse signal and the pattern function of diabetic condition corresponding relationship；By obtaining pulse signal, calculating and obtaining diabetic condition assessment result by the pattern function according to the characteristic index of pulse signal.System also available multiple pulse signals, obtain multiple diabetic condition assessment results, these results are recorded and analyzed, and diabetic condition development trend assessment result are obtained, for the daily state of illness monitoring of diabetic and control.Compared with prior art, the present invention can assess diabetic condition and development trend by non-invasive methods, and user experience is good, at low cost, easy to operate, realize control progression of the disease convenient for diabetic, even delay the target of progression of the disease.
Description
Technical field
The present invention relates to diabetic condition appraisal procedures, and in particular to a kind of diabetic condition assessment based on pulse signal
Method and system.
Background technique
Diabetes be it is a kind of can disable, lethal chronic metabolic disease, state of an illness weight and risk assessment are glycosurias
The problem that patient and its household extremely pay close attention to.Diabetes are closely related with life style, at present unless being in a bad way,
Most time patient is in community and family, therefore the control of diabetes largely relies on patient's self-management.It is fixed to remove
Phase admission examination glycosylated hemoglobin, hepatic and renal function, the retina extent of damage, weight, blood pressure, heart condition, by monitoring hand
Section understands the physical condition of oneself, tentatively progress self-assessment, so that timely seeking medical attention, is diabetic's self-management
Important link.
In the prior art, the daily health control of diabetic depends on self detecting blood sugar.Pass through the blood to itself
Sugar is monitored, and is only assessed the blood sugar regulation ability of itself, when the adjusting of discovery blood glucose can not pass through drug at home
When control, it is hospitalized for treatment in time.But in addition to blood glucose is high outer, many diabetics also and meanwhile complicated hypertension, hyperlipidemia,
A variety of cardiovascular risk factors such as hyperuricemia, these risk factors are more, and the risk of diabetic complication is higher.Because
Diabetes can cause the multiple organ injuries such as the heart, brain, kidney, eye, nerve, limbs, and the various chronic complicating diseases of diabetes are to lead to sugar
The main reason for urine patient disables and is dead.
Summary of the invention
The present invention solves the technical problem of the assessments of current diabetic condition mainly to use blood glucose self monitoring method, should
Method detection parameters are single, invasive, poor user experience, at high cost.
In order to solve the above technical problems, the present invention proposes a kind of diabetic condition appraisal procedure based on pulse signal, packet
It includes: obtaining pulse signal；According to the pulse signal, corresponding diabetic condition assessment result is obtained.
On the other hand, the present invention also proposes a kind of diabetic condition assessment system based on pulse signal, comprising: pulse letter
Number acquisition device, for acquiring the pulse signal of person to be detected；Processor, for executing method as described above.
On the other hand, the present invention also proposes a kind of computer readable storage medium, including program, and described program can be located
Device is managed to execute to realize method as described above.
A kind of diabetic condition appraisal procedure and system based on pulse signal that the present invention uses, compared with prior art,
Can be with noninvasively estimating diabetic condition and development trend, user experience is good, at low cost, easy to operate, realizes convenient for diabetic
Progression of the disease is controlled, the target of progression of the disease is even delayed.
Detailed description of the invention
Fig. 1 is a kind of diabetic condition assessment system schematic diagram based on pulse signal；
Fig. 2 is a kind of diabetic condition appraisal procedure flow chart based on pulse signal；
Fig. 3 is a kind of characteristic index of pulse signal and the pattern function method for building up process of diabetic condition corresponding relationship
Figure.
Specific embodiment
Below by specific embodiment combination attached drawing, invention is further described in detail.Wherein different embodiments
Middle similar component uses associated similar element numbers.In the following embodiments, many datail descriptions be in order to
The application is better understood.However, those skilled in the art can recognize without lifting an eyebrow, part of feature
It is dispensed, or can be substituted by other elements, material, method in varied situations.In some cases, this Shen
Please it is relevant it is some operation there is no in the description show or describe, this is the core in order to avoid the application by mistake
More descriptions are flooded, and to those skilled in the art, these relevant operations, which are described in detail, not to be necessary, they
Relevant operation can be completely understood according to the general technology knowledge of description and this field in specification.
It is formed respectively in addition, feature described in this description, operation or feature can combine in any suitable way
Kind embodiment.Meanwhile each step in method description or movement can also can be aobvious and easy according to those skilled in the art institute
The mode carry out sequence exchange or adjustment seen.Therefore, the various sequences in the description and the appended drawings are intended merely to clearly describe a certain
A embodiment is not meant to be necessary sequence, and wherein some sequentially must comply with unless otherwise indicated.
It is herein component institute serialization number itself, such as " first ", " second " etc., is only used for distinguishing described object,
Without any sequence or art-recognized meanings.And " connection ", " connection " described in the application, unless otherwise instructed, include directly and
It is indirectly connected with (connection).
The embodiment of the present invention one: please referring to Fig. 1, and a kind of diabetic condition assessment system based on pulse signal includes:
Pulse signal acquisition device A00: for acquiring the pulse signal of person to be detected；
Processor A01: for the pulse signal according to acquisition, corresponding diabetic condition assessment result is obtained.Another party
Face, for processor A01 according to pulse signal, obtaining corresponding diabetic condition assessment result includes: to calculate arteries and veins according to pulse signal
The one or more features index of signal of fighting obtains corresponding diabetic condition assessment knot according to the characteristic index of pulse signal
Fruit.In addition, processor A01 can pre-establish the characteristic index of pulse signal and the model letter of diabetic condition corresponding relationship
Number, by the characteristic index input model function of pulse signal, obtains corresponding diabetic condition assessment result.Processor A10 is logical
After the physiological parameter for obtaining different state of an illness stage diabetics in advance, and acquire corresponding time point when the physiological parameter
Pulse signal before；Obtain the characteristic index of these pulse signals；By the characteristic index of these pulse signals and these arteries and veins
The corresponding physiological parameter of signal of fighting carries out machine learning, obtains the characteristic index and diabetic condition of pulse signal as input
The pattern function of corresponding relationship.Processor A10 can also be according to the pulse signal for obtaining multiple time points, when obtaining corresponding multiple
Between the diabetic condition assessment result put, these assessment results are recorded and are analyzed, for assessing diabetic condition development
Trend.
Wherein, processor A10 is based on pulse signal and obtains corresponding diabetic condition assessment result, is based primarily upon pulse letter
Pulse frequency (PR, Pulse Rate) signal sequence in number plethysmogram, the pulse frequency PR signal refer to that pulse signal volume is retouched
Remember the time interval between wave crest and wave crest adjacent in figure, PR signal sequence includes all PR signals in one section of pulse signal
Interval.
In one embodiment, processor A10 calculates characteristic index by pulse signal, comprising:
Frequency-domain analysis is carried out to any one section of pulse signal, available one or more frequency domain character index:
Area obtains under line of the freqArea sequence by calculating at least one frequency range of pulse signal frequency domain image, by setting
Different frequency ranges is set, obtains area under the corresponding line of each frequency range, area constitutes the freqArea sequence under these lines；
The frequency domain of usual pulse signal includes: ultralow frequency range: 0-0.04Hz, low-frequency range: 0.04-0.15Hz and high band: 0.15-
0.4Hz.FreqPercent sequence accounts for area under bus by calculating area under at least one frequency range line of pulse signal frequency domain image
Percentage obtain, by the way that different frequency range is arranged, obtain the corresponding percentage of each frequency range, these percentages constitute institute
The freqPercent sequence stated；Ratio sequence is by calculating below the mutual line of pulse signal frequency domain image different frequency range
Product ratio obtains, and by the way that different frequency ranges is arranged, obtains area ratio under the mutual line of every two frequency range, these ratio structures
At the ratio sequence.
Linear analysis is carried out to the pPRx sequence of pulse signal to obtain one or more linear characteristic indexs, and/or
Nonlinear analysis is carried out, to obtain one or more nonlinear characteristic indexs.The wherein pPRx sequence of any one section of pulse signal
Column are calculated in the following manner: the difference for calculating adjacent pulse rate signal interphase in this section of pulse signal is greater than threshold value x milliseconds
It is corresponding to obtain each threshold value x by the way that different threshold value x is arranged for the ratio of the quantity of quantity and whole pulse rate signal interphases
Ratio, these ratios constitute the pPRx sequence.In the present embodiment, which is expressed as a percentage, as shown in formula (1):
Linear analysis, and/or nonlinear analysis, and/or frequency-domain analysis are carried out according to the pPRx sequence of the pulse signal,
Available one or more features index.
For example, the characteristic index that linear analysis obtains may include: the mark of mean value meanPR, the pPRx sequence of pPRx sequence
The root mean square RMSSD of adjacent pPRx difference in standard deviation SDAPR and the pPRx sequence of quasi- difference SDPR, pPRx serial mean.
Nonlinear analysis is carried out to the pPRx sequence of every section of pulse signal, using Entropy Analysis Method, it may be assumed that according to existing skill
Art, for the stochastic variable collection A of probability-distribution function p (x), shown in the definition of entropy such as formula (2):
H (A)=- ∑ pA(x)logpA(x) (2)
The characteristic index that can be obtained includes:
(1) pPRx sequence histogram distributed intelligence entropy SdhIt is the numeric distribution comentropy to pPRx sequence；
(2) pPRx sequence power composes histogram distributed intelligence entropy SphIt is to carry out discrete Fourier transform to pPRx sequence to obtain function
Rate spectrum, then calculates its comentropy according to the numeric distribution of power spectrum sequence；
(3) pPRx sequence power composes full frequency band distributed intelligence entropy SpfIt is to carry out discrete Fourier transform to pPRx sequence to obtain
Power spectrum, in full frequency band [fs/N,fs/ 2] (sample frequency of signal is fs, sampling number N) and i-1 branch f of interior insertion1,
f2..., fm-1, full frequency band is divided into i frequency sub-band.Using the sum of power density in each frequency range as the power of the frequency range
Density then obtains m power density.This i power density is normalized to obtain the Probability p of each frequency range appearancei, then ∑ipi=
1, shown in corresponding power spectrum full frequency band entropy such as formula (3):
Nonlinear analysis is carried out to the pPRx sequence of every section of pulse signal, can also be calculated using following four kinds of fractal dimensions
The available following characteristic index of analysis method:
(1) structure function method calculates resulting fractal dimension Dsf, wherein structure function method refers to for given sequence z
(x), defining increment variance is structure function, relationship are as follows:
For several scales τ, corresponding S (τ) is calculated to the discrete value of sequence z (x), then draws logS (τ)-
The function curve of log τ carries out linear fit in non-scaling section, obtains slope, then correspond to fractal dimension DsfWith the conversion of slope
Shown in relationship such as formula (5):
(2) correlation function algorithm calculates resulting fractal dimension Dcf, wherein correlation function algorithm refers to for given sequence z
(x), correlation function C (τ) is defined as shown in formula (6):
C (τ)=AVE (z (x+ τ) * z (x)), τ=1,2,3 ..., N-1 (6)
Wherein, AVE () indicates average, and τ indicates two o'clock distance.Correlation function is power type at this time, since there is no feature
Length is then distributed as a point shape, there is C (τ) α τ-α.At this moment, the function curve for drawing logC (τ)-log τ carries out line in non-scaling section
Property fitting, obtain slope, then correspond to fractal dimension DcfShown in transforming relationship such as formula (7) with slope:
Dcf=2- α (7)
(3) variate-difference method calculates resulting fractal dimension Dvm, wherein the rectangle frame that variate-difference method is τ with width is end to end to incite somebody to action
Fractal curve covers, and the difference of the maximum value and minimum value that enable i-th of frame inner curve is H (i), the as height of rectangle.It will
The height and width of all rectangles are multiplied to obtain gross area S (τ).The size for changing τ, obtains a series of S (τ).As shown in formula (8):
The function curve for drawing logN (τ)-log τ carries out linear fit in non-scaling section and obtains slope, then correspondence divides shape
Dimension DvmShown in transforming relationship such as formula (7) with slope.
(4) mean square root method calculates resulting fractal dimension Drms, wherein mean square root method with width be τ rectangle frame it is end to end
Fractal curve is covered, the difference of the maximum value and minimum value that enable i-th of frame inner curve is H (i), the as height of rectangle
Degree.Calculate the root-mean-square value S (τ) of these rectangular elevations.The size for changing τ, obtains a series of S (τ).Draw logS (τ)-
The function curve of log τ carries out linear fit in non-scaling section and obtains slope, then corresponds to fractal dimension DrmsWith the conversion of slope
Shown in relationship such as formula (7).
Pulse signal characteristic index for carrying out diabetic condition assessment result is above-mentioned frequency-domain analysis, and/or linear,
And/or one in the obtained characteristic index of nonlinear analysis, multiple, or wherein several set, it is also possible to except this
Embodiment enumerate except the obtained individual features index of existing analysis method.
Input unit A02: being connected with processor signal, for receiving the input information of user.
Shell A03: the shell is enclosed accommodating chamber, and processor A01 and input unit A02 are at least partly contained in
In the accommodating chamber of shell A03, the shell A03 is equipped with a display area.
Display device A04: it is connected with display area and processor A01 signal, and according to input unit A02 and processor
The instruction of A01 shows diabetic condition and/or diabetic condition trend evaluation result.
Memory A05: being connected with processor A01 signal, for storing program, diabetic condition assessment result and diabetes
State of an illness trend evaluation result.
In one embodiment, there is a diabetes B in one diabetic 65 years old, and 8.5 mmoles of fasting blood-glucose/liter, it is early postprandial
2 hours 14.2 mmoles of blood glucose/liter, glycosylated hemoglobin (HbA1c) 8.5%；Body mass index 29 (being normal lower than 24), abdomen type fertilizer
It is fat, blood pressure be 165/100 millimetres of mercury (high blood pressure), triacylglycerol be 4.8 mmoles/liter, low density lipoprotein-cholesterol is
(LDL-C) 4.5 mmoles/liter, highdensity lipoprotein-cholesterol be (HDL-C) 0.85 mmoles/liter (disorders of lipid metabolism), blood uric acid
For 580 mmoles/liter (hyperuricemia), eyeground is normal, (increases within twenty-four-hour urine microalbumin quantification of 210 milligrams/24 hours
It is high), liver function is normal, normal ECG.The diabetic condition assessment result of this Patient Global is diabetes B and early stage sugar
Sick nephrosis is urinated, while with the high-risk situation of cardiovascular disease.Specifically in the present embodiment, patient can be acquired by pulse signal
Device A00 acquires pulse signal in different time, by A01 processor and A05 memory, completes the diabetes at corresponding time point
Condition assessment result and record are received by input unit A02 and are suffered to carry out the trend evaluation of diabetes mellitus's progression of the disease
Person's instruction accurately obtains resulting glycosuria by the way that the display area on shell A03 is convenient under the support of display device A04
Sick condition assessment is as a result, and corresponding diabetic condition development trend assessment result.The result can be used for diabetic
Carry out self health control, comprising: discuss individuation diabetic condition control target fully with doctor；Day is looked back jointly with doctor
Normal diabetic condition monitoring and trend result；The day diabetes state of an illness is explained and exchanged together with doctor；According to diabetic condition
Actively change daily life behavior with physician feedback, to realize control diabetic condition development, even delays progression of the disease
Target.
In the present embodiment, processor A10 uses the diabetic condition assessment side shown in Fig. 2 based on pulse signal
Method, this method is at low cost, safe and effective, specifically includes B00 step~B10 step, is specifically described below:
B00: the pulse signal of multiple periods is obtained.
B10: according to the pulse signal, corresponding diabetic condition assessment result is obtained.
In one embodiment, step B10 includes: according to pulse signal, and the one or more features for calculating pulse signal refer to
Mark, according to the characteristic index of pulse signal, obtains corresponding diabetic condition assessment result.Wherein, the feature of pulse signal refers to
The calculation method of mark and diabetic condition assessment result is as described above.
In one embodiment, step B10 is obtaining corresponding diabetic condition assessment according to the characteristic index of pulse signal
When as a result, the characteristic index of pulse signal and the pattern function of diabetic condition corresponding relationship can be pre-established, pulse is believed
Number characteristic index input model function, obtain corresponding diabetic condition assessment result.For example, B10 step can pass through machine
Study, it is shown referring to figure 3. to establish the characteristic index of pulse signal and the pattern function of diabetic condition corresponding relationship.
As shown in figure 3, B10 step establishes above-mentioned pattern function, it may include B11~B13 step, be specifically described below.
B11: obtaining the physiological parameter of different state of an illness stage diabetics in advance, and when acquiring the physiological parameter pair
Pulse signal before the time point answered.Wherein, the physiological parameter for obtaining different state of an illness stage diabetics in advance, example
Such as: blood glucose value, body mass index, pressure value, cholesterol, blood uric acid, disease type, stage, complication quantity and severity；
The method that physiological parameter is obtained described in the step can use method commonly used in the prior art, precision is high, meanwhile,
The acquisition of corresponding each physiological parameter, corresponding pulse signal before needing to acquire physiological parameter time point, due to individual
Metabolic situation has differences, and pulse signal time span needed for each sampler is not identical, models effect with practical
Subject to, the present embodiment chooses the pulse signal of 1~30 minute different time length.
B12: the characteristic index of these pulse signals is obtained.
B13: using the characteristic index of these pulse signals and the corresponding physiological parameter of these pulse signals as input,
Machine learning is carried out, the characteristic index of pulse signal and the pattern function of diabetic condition corresponding relationship are obtained.
After obtaining the characteristic index of pulse signal and the pattern function of diabetic condition corresponding relationship according to above-mentioned steps, then
The pulse signal of person to be detected acquired in B00 step is inputted into the pattern function, diabetic condition assessment result can be obtained.
In one embodiment, same patient can also be obtained according to the above method to comment in the diabetic condition at multiple time points
Estimate as a result, charting and further analysis, the assessment result of acquisition diabetes mellitus's progression of the disease trend can be carried out.
It will be understood by those skilled in the art that all or part of function of various methods can pass through in above embodiment
The mode of hardware is realized, can also be realized by way of computer program.When function all or part of in above embodiment
When being realized by way of computer program, which be can be stored in a computer readable storage medium, and storage medium can
To include: read-only memory, random access memory, disk, CD, hard disk etc., it is above-mentioned to realize which is executed by computer
Function.For example, program is stored in the memory of equipment, when executing program in memory by processor, can be realized
State all or part of function.In addition, when function all or part of in above embodiment is realized by way of computer program
When, which also can store in storage mediums such as server, another computer, disk, CD, flash disk or mobile hard disks
In, through downloading or copying and saving into the memory of local device, or version updating is carried out to the system of local device, when logical
When crossing the program in processor execution memory, all or part of function in above embodiment can be realized.
Use above specific case is illustrated the present invention, is merely used to help understand the present invention, not to limit
The system present invention.For those skilled in the art, according to the thought of the present invention, can also make several simple
It deduces, deform or replaces.
Claims (10)
1. a kind of diabetic condition appraisal procedure based on pulse signal characterized by comprising
Obtain pulse signal；
According to the pulse signal, corresponding diabetic condition assessment result is obtained.
2. method as described in claim 1, which is characterized in that it is described according to pulse signal, it obtains corresponding diabetic condition and comments
Estimating result includes: that the one or more features index of pulse signal is calculated according to pulse signal, is referred to according to the feature of pulse signal
Mark, obtains corresponding diabetic condition assessment result.
3. method as claimed in claim 2 characterized by comprising pre-establish the characteristic index and diabetes of pulse signal
The characteristic index input model function of pulse signal is obtained corresponding diabetic condition by the pattern function of state of an illness corresponding relationship
Assessment result.
4. such as Claims 2 or 3 the method, which is characterized in that the characteristic index of pulse signal, comprising: to pulse signal into
Line frequency domain analysis to obtain one or more frequency domain characters, and/or carries out linear analysis to the pPRx sequence of pulse signal to obtain
To one or more linear characteristic indexs, and/or nonlinear analysis is carried out, is referred to obtaining one or more nonlinear features
Mark；Wherein the pPRx sequence of any one section of pulse signal is calculated in the following manner: calculating adjacent in this section of pulse signal
The ratio of the quantity of quantity of the difference of pulse rate signal interphase greater than threshold value x milliseconds and whole pulse rate signal interphases, by being arranged not
Same threshold value x, obtains the corresponding ratio of each threshold value x, these ratios constitute the pPRx sequence.
5. method as claimed in claim 4, which is characterized in that the characteristic index of pulse signal, further includes:
The frequency domain character that the frequency-domain analysis obtains includes freqArea sequence, freqPercent sequence and ratio sequence.Its
In, area obtains under line of the freqArea sequence by calculating at least one frequency range of pulse signal frequency domain image, by being arranged not
Same frequency range, obtains area under the corresponding line of each frequency range, area constitutes the freqArea sequence under these lines；
FreqPercent sequence accounts for the percentage of area under bus by calculating area under at least one frequency range line of pulse signal frequency domain image
Than obtaining, by the way that different frequency ranges is arranged, the corresponding percentage of each frequency range is obtained, these percentages constitute described
FreqPercent sequence；Ratio sequence is by calculating area ratio under the mutual line of pulse signal frequency domain image different frequency range
Value obtains, and by the way that different frequency ranges is arranged, obtains area ratio under the mutual line of every two frequency range, these ratios constitute
At least one of described ratio sequence；And/or
The characteristic index that the linear analysis obtains: the standard deviation SDPR, pPRx of mean value meanPR, the pPRx sequence of pPRx sequence
At least one of the root mean square RMSSD of adjacent pPRx difference in standard deviation SDAPR, the pPRx sequence of serial mean；And/or
The nonlinear characteristic index includes that the obtained characteristic index of Entropy Analysis Method, packet are carried out to the pPRx sequence
It includes: pPRx sequence histogram distributed intelligence entropy Sdh, pPRx sequence power compose histogram distributed intelligence entropy Sph, pPRx sequence power spectrum it is complete
Frequency range distributed intelligence entropy SpfAt least one of；And/or the nonlinear characteristic index includes that the pPRx sequence is divided
Shape dimension, which calculates, analyzes obtained characteristic index, comprising: structure function method calculates resulting fractal dimension Dsf, correlation function algorithm
Calculate resulting fractal dimension Dcf, variate-difference method calculate resulting fractal dimension Dvm, mean square root method calculate resulting fractal dimension
DrmsAt least one of.
6. method as claimed in claim 3, which is characterized in that the characteristic index for pre-establishing pulse signal and diabetes disease
The pattern function of feelings corresponding relationship, comprising:
The physiological parameter of different state of an illness stage diabetics is obtained in advance, and acquires the corresponding time when physiological parameter
Pulse signal before point；
Obtain the characteristic index of these pulse signals；
It inputs, carries out using the characteristic index of these pulse signals and the corresponding physiological parameter of these pulse signals as feature
Machine learning obtains the characteristic index of pulse signal and the pattern function of diabetic condition corresponding relationship.
7. method as described in claim 1 characterized by comprising obtain the pulse signal at multiple time points, can obtain pair
The diabetic condition assessment result for answering multiple time points is recorded and is analyzed to these assessment results, can be used for assessing sugar
Urinate sick progression of the disease trend.
8. a kind of diabetic condition assessment system based on pulse signal characterized by comprising
Pulse signal acquisition device, for acquiring the pulse signal of person to be detected；
Processor, for executing such as method of any of claims 1-7.
9. system as claimed in claim 8, which is characterized in that further include:
Input unit is connected with processor signal, for receiving the input information of user；
Shell, the shell are enclosed accommodating chamber, and processor and input unit are at least partly contained in the accommodating chamber of shell
In, the shell is equipped with a display area；
Display device is connected with display area and processor signal, and according to the instruction of input unit and processor by diabetes
The state of an illness and/or diabetic condition trend evaluation result are sent to display area and are shown；
Memory is connected with processor signal, comments for storing program, diabetic condition assessment result and diabetic condition trend
Estimate result.
10. a kind of computer readable storage medium, which is characterized in that including program, described program can be executed by processor with
Realize such as method of any of claims 1-7.
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