CN109350022A - For predicting that arrhythmia cordis risk surface electrocardiogram processing system occurs for multipole individual - Google Patents
For predicting that arrhythmia cordis risk surface electrocardiogram processing system occurs for multipole individual Download PDFInfo
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- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- 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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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- 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
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
- A61B5/0245—Detecting, measuring or recording pulse rate or heart rate by using sensing means generating electric signals, i.e. ECG signals
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- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
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- A—HUMAN NECESSITIES
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- A61B5/74—Details of notification to user or communication with user or patient ; user input means
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Abstract
The invention belongs to electrocardiogram processing technology fields, it discloses one kind and is used to predict that arrhythmia cordis risk surface electrocardiogram processing system to occur for multipole individual, it is described for predicting that multipole individual generation arrhythmia cordis risk surface electrocardiogram processing system includes: electrocardio-data collection module, parameter configuration module, operation input module, central control module, heart rate discrimination module, data analysis module, alarm module, print module, display module.The present invention preferably supports user to carry out self health control by heart rate discrimination module, and the differentiation process calculation amount of this method is smaller, and algorithm complexity is low, high-efficient;Meanwhile secondary analysis accurately can be carried out by the ecg wave form to unstable quality by data analysis module, analysis precision can be improved at times, reduces the workload of operator, while improving the working efficiency of operator.
Description
Technical field
The invention belongs to electrocardiogram processing technology fields, more particularly to one kind is for predicting that arrhythmia cordis occurs for multipole individual
Risk surface electrocardiogram processing system.
Background technique
Electrocardiogram (ECG or EKG) is to record electricity caused by heart each cardiac cycle from body surface using electrocardiograph
The technology of activity change figure.Myocardial cell membrane is semi-permeable membrane, when quiescent condition, arranges the positively charged sun of certain amount outside film
Ion, the negatively charged anion of the identical quantity of the interior arrangement of film, film volta potential are higher than in film, referred to as polarized state.Quiescent condition
Under, since each position cardiac muscle cell of heart is all in polarized state, without potential difference, the potential curve that galvo-recorder is traced is flat
Directly, the as equipotential line of surface electrocardiogram.In the stimulation by some strength, permeability of cell membrane changes cardiac muscle cell
Become, poured in film in a large amount of cation short time, becomes film inner potential just by negative, this process is known as depolarization.To whole heart
For, potential change of the cardiac muscle cell from the internal membrane of heart into external membrane of heart sequence process of depolarization, the current potential traced by galvo-recorder
Curve is known as wave of depolarization, i.e., the P wave in atrium and the QRS wave of ventricle on surface electrocardiogram.After the completion of cell depolarization, cell membrane is arranged again
A large amount of cations out make film inner potential be restored to original polarized state by just becoming negative, this process from the external membrane of heart to the internal membrane of heart into
Row, referred to as multipole.Potential change in same cardiac muscle cell's process of repolarization traces out referred to as repolarization wave by galvo-recorder.By
Relatively slow in process of repolarization, repolarization wave is low compared with wave of depolarization.The repolarization wave in atrium is low and is embedded in the wave of depolarization of ventricle, body surface
Electrocardiogram is not easy to recognize.The repolarization wave of ventricle shows as T wave on surface electrocardiogram.After entire cardiac muscle cell's whole multipole, then
Secondary recovery polarized state, without potential difference between each position cardiac muscle cell, equipotential line is recorded in surface electrocardiogram.However, existing
Ecg signal acquiring equipment is not readily portable greatly, and needs wearing in continuous 24 hours that can just obtain complete assessment report, limits
The daily action of patient, while diagnosis needs the participation of doctor, is difficult to realize daily cardiomotility situation and rhythm abnormality
Self-monitoring, diagnosis and management;Meanwhile environment, position and state locating for the subject be when changing, in electrocardiogram
Intensity, the frequency of various interference signals can also change at any time, lead to the consistency reduction of ECG signal and waveform quality
Decline causes the workload of operator's follow-up editor, modification wrong report, failing to report phenomenon to influence the precision of software analysis result
Increase, working efficiency reduces.
In conclusion problem of the existing technology is:
Existing ecg signal acquiring equipment is not readily portable greatly, and wearing in continuous 24 hours is needed just completely to be commented
Estimate report, limit the daily action of patient, while diagnosis needs the participation of doctor, be difficult to realize daily cardiomotility situation with
And self-monitoring, diagnosis and the management of rhythm abnormality;Meanwhile environment, position and state locating for the subject be when changing,
Intensity, the frequency of various interference signals in electrocardiogram can also change at any time, the consistency of ECG signal is caused to reduce,
And waveform quality declines, to influence the precision of software analysis result, causes operator's follow-up editor, modification wrong report, fails to report now
The workload of elephant increases, and working efficiency reduces.
Alarm cannot carry out alert notice to the abnormal data of differentiation constantly in the prior art, reduce alarm velocity, make
Obtaining abnormal data cannot be found in time, reduce the operating accuracy and working efficiency of system;Printer cannot be quasi- in the prior art
Optimal solution is really obtained, electrocardiogram is subjected to printing to there is peak deviation, is unfavorable for obtaining accurate clearly electrocardiogram;It is existing
Have display in technology that cannot effectively avoid difference problem existing for the gray value of lamp point region and background area so that data by
The influence of contrast and brightness, display cannot quickly, clearly, accurately show electrocardiogram (ECG) data, electrocardiogram and the heart rate of acquisition
Abnormal data information.
Summary of the invention
In view of the problems of the existing technology, the present invention provides one kind for predicting that arrhythmia cordis wind occurs for multipole individual
Dangerous surface electrocardiogram processing system.
The invention is realized in this way a kind of for predicting that the body surface ecg of arrhythmia cordis risk occurs for early repolarization individual
Figure processing method, the surface electrocardiogram processing method for predicting early repolarization individual generation arrhythmia cordis risk include:
Step 1 is placed on human body different parts by electrode and is acquired electrocardiogram data information;Pass through electrocardiograph
Handle the initial parameter of electrocardiogram (ECG) data;It is input operation instruction by operating keyboard;
Step 2 carries out heart rate using electrocardiosignal of the data processor to acquisition and judges extremely;It is analyzed using data
Program is analyzed and processed the electrocardiogram (ECG) data of acquisition;
Step 3 carries out alert notice using abnormal data of the alarm moment to differentiation;Printer passes through ant group algorithm
Electrocardiogram is subjected to printing;
Step 4, it is different by using the electrocardiogram (ECG) data, electrocardiogram and heart rate of module-cascade constraint formula display display acquisition
Regular data information.
Further, alert notice is carried out using abnormal data of the alarm moment to differentiation, sampling instant is k alarm device
Input variable be u (k), state variable be x (k), output variable be y (k), then alarm is expressed as with abnormal data:
In formula, the output variable of input variable u (k) staff operating unit and detection input unit is constituted, and output becomes
Amount y (k) is the input variable of alarm.
Further, printer inquires optimal solution by ant group algorithm, electrocardiogram is carried out accurately printing, specifically
Steps are as follows:
If the position ant k is printout i, ant k selects next printout j to be added by following state transition probability
Print sequence:
In formula: allowedkAllow the printout of selection for ant k;
α is information heuristic greedy method;
β is expected heuristic value;
τijFor path (i, j) remaining information content;
ηijFor the expected degree of path (i, j);
ηijIndicate the expected degree that i is adjacent with j in printout distributing order;
To reach printout difference in height target as small as possible in batch, by ηijIt is taken as printout i and printout j difference in height
The inverse of value;
After whole ants complete printout traversal, residual risk element is updated;T+1 circulation rear path (i,
J) information content on is calculated as follows:
τij(t+1)=(1- ρ) τij(t)+Δτij(t);
In formula: ρ is pheromones volatility coefficient, and value range is [0,1];
ΔτijIt (t) is the pheromones increment on path (i, j) in this circulation, Pheromone update uses ant week model
(Ant-CycleModel);
In formula: Q is constant, indicate ant recycle one week the total amount through release pheromone on path;
LkThe total length for walking path in this circulation by kth ant, when the number of iterations reaches setting greatest iteration
When number, algorithm stops, and history optimal solution is Optimum Solution.
Another object of the present invention is to provide be used to predict that arrhythmia cordis occurs for early repolarization individual described in a kind of implementation
The surface electrocardiogram processing method of risk is used to predict that arrhythmia cordis risk surface electrocardiogram processing system to occur for multipole individual,
It is described to include: for predicting that arrhythmia cordis risk surface electrocardiogram processing system occurs for multipole individual
Electrocardio-data collection module, connect with central control module, for by electrode be placed on human body different parts into
Row acquisition electrocardiogram data information;
Parameter configuration module is connect with central control module, for configure electrocardiograph processing electrocardiogram (ECG) data it is initial
Parameter;
Operation input module, connect with central control module, for being input operation instruction by operating keyboard;
Central control module differentiates mould with electrocardio-data collection module, parameter configuration module, operation input module, heart rate
Block, data analysis module, alarm module, print module, display module connection are normal for controlling modules by single-chip microcontroller
Work;
Heart rate discrimination module, connect with central control module, for the electrocardiosignal by data processor to acquisition
Heart rate is carried out to judge extremely;
Data analysis module is connect with central control module, for the electrocardiogram (ECG) data by data analysis program to acquisition
It is analyzed and processed;
Alarm module is connect with central control module, logical for carrying out alarm by abnormal data of the alarm to differentiation
Know;
Print module is connect with central control module, for electrocardiogram to be carried out printing by printer;
Display module is connect with central control module, abnormal for electrocardiogram (ECG) data, the heart rate by display display acquisition
Data information.
Another object of the present invention is to provide a kind of applications for predicting that arrhythmia cordis risk occurs for early repolarization individual
Surface electrocardiogram processing method computer.
Advantages of the present invention and good effect are as follows: the present invention by heart rate discrimination module using arrhythmia cordis method of discrimination with
The prior art is compared, can the automatic discrimination rhythm of the heart whether have abnormal and specific types of arrhythmia, to preferably support
User carries out self health control, and the differentiation process calculation amount of this method is smaller, and algorithm complexity is low, high-efficient;Together
When, secondary analysis accurately can be carried out by the ecg wave form to unstable quality by data analysis module, can be improved at times
Analysis precision, reduces the workload of operator, while improving the working efficiency of operator.
The present invention carries out alert notice using abnormal data of the alarm moment to differentiation, alarm velocity is improved, so that different
Regular data is found in time, improves the operating accuracy and working efficiency of system;Printer of the present invention is accurately looked by ant group algorithm
Optimal solution is ask, electrocardiogram is subjected to accurately printing, obtains accurate clearly electrocardiogram;The present invention passes through module-cascade about
The display of beam formula shows electrocardiogram (ECG) data, electrocardiogram and heart rate abnormal data information, effectively avoids lamp point region and back
Difference problem existing for the gray value of scene area, so that data are not influenced by contrast and brightness, so that display is quickly, clearly
Electrocardiogram (ECG) data, electrocardiogram and the heart rate abnormal data information of clear, accurate display acquisition.
Detailed description of the invention
Fig. 1 is provided in an embodiment of the present invention for predicting that the body surface ecg of arrhythmia cordis risk occurs for early repolarization individual
Figure processing method flow chart.
Fig. 2 is provided in an embodiment of the present invention for predicting that the processing of arrhythmia cordis risk surface electrocardiogram occurs for multipole individual
System structure diagram;
In figure: 1, electrocardio-data collection module;2, parameter configuration module;3, operation input module;4, central control module;
5, heart rate discrimination module;6, data analysis module;7, alarm module;8, print module;9, display module.
Specific embodiment
In order to further understand the content, features and effects of the present invention, the following examples are hereby given, and cooperate attached drawing
Detailed description are as follows.
Structure of the invention is explained in detail with reference to the accompanying drawing.
As shown in Figure 1, provided in an embodiment of the present invention for predicting that the body of arrhythmia cordis risk occurs for early repolarization individual
Table ECG treatment method, specifically includes the following steps:
S101: human body different parts are placed on by electrode and are acquired electrocardiogram data information;Pass through the place of electrocardiograph
Manage the initial parameter of electrocardiogram (ECG) data;It is input operation instruction by operating keyboard;
S102: heart rate is carried out using electrocardiosignal of the data processor to acquisition and is judged extremely;Journey is analyzed using data
The electrocardiogram (ECG) data of ordered pair acquisition is analyzed and processed;
S103: alert notice is carried out using abnormal data of the alarm moment to differentiation;Printer will by ant group algorithm
Electrocardiogram carries out printing;
S104: electrocardiogram (ECG) data, electrocardiogram and the heart rate by using module-cascade constraint formula display display acquisition are abnormal
Data information.
In step S103, provided in an embodiment of the present invention using abnormal data of the alarm moment to differentiation to carry out alarm logical
Know, improves alarm velocity so that abnormal data is found in time and improve the operating accuracy and working efficiency of system;Sampling instant
Input variable for k alarm device is u (k), and state variable is x (k), and output variable is y (k), then alarm and abnormal data
It is represented by
In formula, the output variable of input variable u (k) staff operating unit and detection input unit is constituted, and output becomes
Amount y (k) is the input variable of alarm.
In step S103, printer provided in an embodiment of the present invention accurately inquires optimal solution, by electrocardio by ant group algorithm
Figure carries out accurately printing, obtains accurate clearly electrocardiogram;Specific step is as follows:
If the position ant k is printout i, ant k selects next printout j to be added by following state transition probability
Print sequence:
In formula: allowedkAllow the printout of selection for ant k;
α is information heuristic greedy method;
β is expected heuristic value;
τijFor path (i, j) remaining information content;
ηijFor the expected degree of path (i, j);
ηijIndicate the expected degree that i is adjacent with j in printout distributing order;
To reach printout difference in height target as small as possible in batch, the present invention is by ηijIt is taken as printout i and printout j
The inverse of height difference;
Heuristic information is flooded to avoid residual risk element excessive, it, be to residual after whole ants complete printout traversal
Pheromones are stayed to be updated;Information content on t+1 circulation rear path (i, j) is calculated as follows:
τij(t+1)=(1- ρ) τij(t)+Δτij(t)
In formula: ρ is pheromones volatility coefficient, and value range is [0,1];
ΔτijIt (t) is the pheromones increment on path (i, j) in this circulation, Pheromone update uses ant week model
(Ant-CycleModel);
In formula: Q is constant, indicate ant recycle one week the total amount through release pheromone on path;
LkThe total length in path is walked in this circulation by kth ant, the present invention takes the objective function that it is problem
Value;When the number of iterations reaches setting maximum number of iterations, algorithm stops, and history optimal solution is Optimum Solution.
It is provided in an embodiment of the present invention that the display of formula is constrained to electrocardiogram (ECG) data, the heart by module-cascade in step S104
Electrograph and heart rate abnormal data information are shown, difference existing for the gray value of lamp point region and background area is effectively avoided to ask
Topic, so that data are not influenced by contrast and brightness, so that display quickly, clearly, accurately shows the electrocardio number of acquisition
According to, electrocardiogram and heart rate abnormal data information, specific algorithm are as follows:
The display screen for being W for pixel width, each of which unit module width are WMPixel, maximum cascade number MmaxIf WM
×Mmax< W, it is necessary to screen body transverse direction piecemeal, if screen body laterally divides DVFor block, DVFor positive integer, then every piece of width WFAre as follows:
Every piece of width is no more than M simultaneouslymaxThe total pixel width of a drive module, i.e. WF<WM·Mmax, it can thus be concluded that:
As shown in Fig. 2, the processing of arrhythmia cordis risk surface electrocardiogram occurs provided by the present invention for prediction multipole individual
System includes: electrocardio-data collection module 1, parameter configuration module 2, operation input module 3, central control module 4, heart rate differentiation
Module 5, data analysis module 6, alarm module 7, print module 8, display module 9.
Electrocardio-data collection module 1 is connect with central control module 4, for being placed on human body different parts by electrode
It is acquired electrocardiogram data information;
Parameter configuration module 2 is connect with central control module 4, for configure electrocardiograph processing electrocardiogram (ECG) data just
Beginning parameter;
Operation input module 3 is connect with central control module 4, for being input operation instruction by operating keyboard;
Central control module 4 is sentenced with electrocardio-data collection module 1, parameter configuration module 2, operation input module 3, heart rate
Other module 5, data analysis module 6, alarm module 7, print module 8, display module 9 connect, each for being controlled by single-chip microcontroller
A module works normally;
Heart rate discrimination module 5 is connect with central control module 4, for being believed by electrocardio of the data processor to acquisition
Number carry out heart rate extremely judge;
Data analysis module 6 is connect with central control module 4, for the electrocardio number by data analysis program to acquisition
According to being analyzed and processed;
Alarm module 7 is connect with central control module 4, for being alarmed by abnormal data of the alarm to differentiation
Notice;
Print module 8 is connect with central control module 4, for electrocardiogram to be carried out printing by printer;
Display module 9 is connect with central control module 4, different for electrocardiogram (ECG) data, the heart rate by display display acquisition
Regular data information.
5 method of discrimination of heart rate discrimination module provided by the invention is as follows:
Firstly, obtaining electrocardiosignal;
Then, the characteristic index of electrocardiosignal is calculated;
Finally, obtaining arrhythmia cordis according to the characteristic index of electrocardiosignal differentiates result.
Characteristic index provided by the invention according to electrocardiosignal obtains arrhythmia cordis and differentiates result, comprising: pre-establishes
The pattern function of the type corresponding relationship of the characteristic index and rhythm state of electrocardiosignal, wherein the type packet of the rhythm state
Include rhythm of the heart normal type and different types of arrhythmia cordis;The electrocardiosignal characteristic index input model function that will newly obtain, obtains
To the type of corresponding rhythm state, result is differentiated as arrhythmia cordis.
The model of the type corresponding relationship of the characteristic index provided by the invention for pre-establishing electrocardiosignal and rhythm state
Function, comprising:
The electrocardiosignal of the normal electrocardiosignal of the rhythm of the heart and different types of arrhythmia is obtained in advance;
Calculate the characteristic index of these electrocardiosignals;
Using the characteristic index of these electrocardiosignals as input, the type conduct of the corresponding rhythm state of these electrocardiosignals
Label, carries out machine learning, and training obtains the model letter of the characteristic index of electrocardiosignal and the type corresponding relationship of rhythm state
Number.
The characteristic index of electrocardiosignal provided by the invention, comprising: linear analysis is carried out to the pRRx sequence of electrocardiosignal
To obtain one or more linear characteristic indexs, and/or nonlinear analysis is carried out, to obtain one or more nonlinear spies
Levy index;Wherein the pRRx sequence of any one section of electrocardiosignal is calculated in the following manner: calculating in this section of electrocardiosignal
The ratio of the quantity of quantity of the difference of adjacent R R interphase greater than threshold value x milliseconds and whole RR interphase, passes through the different threshold of setting value
Value x, obtains the corresponding ratio of each threshold value x, these ratios constitute the pRRx sequence;
The characteristic index that the linear analysis obtains: the standard deviation SDRR of mean value AVRR, the pRRx sequence of pRRx sequence,
In pRRx sequence in root mean square rMSSD, pRRx sequence of adjacent pRRx difference in the standard deviation SDSD of adjacent pRRx difference extremely
Few one;
The nonlinear characteristic index includes carrying out the obtained characteristic index of Entropy Analysis Method to the pRRx sequence,
It include: pRRx sequence histogram distributed intelligence entropy Sdh, pRRx sequence power spectrum histogram distributed intelligence entropy Sph, pRRx sequence power spectrum
At least one of full frequency band distributed intelligence entropy Spf.
The nonlinear characteristic index includes that the pRRx sequence carries out the obtained feature of fractal dimension calculating analysis
Index, comprising: structure function method calculates resulting fractal dimension D sf, correlation function algorithm calculates resulting fractal dimension D cf, becomes
Poor method calculates resulting fractal dimension D vm, mean square root method calculates at least one of resulting fractal dimension D rms.
6 analysis method of data analysis module provided by the invention is as follows:
(1) by acquiring human body electrocardio diagram data with multiple leads, obtain and save the heart of the N hour of multiple lead acquisitions
Electromyographic data;
(2) it selects the smallest lead of interference as analysis lead from the multiple lead, and the analysis is led
The ECG data of connection acquisition is analyzed, and ecg wave form and the report of electrocardiogram form in N hours is obtained;
(3) ecg wave form obtained from the ECG data analysis of the analysis lead acquisition is checked, finds wave
The undesirable ecg wave form of form quality amount and corresponding period;
(4) described in corresponding electrocardiogram form report of the ECG data acquired with other leads in the period is replaced
The undesirable electrocardiogram form report of waveform quality, to obtain the electrocardiogram form report that analysis precision is improved.
ECG data provided by the invention to the analysis lead acquisition is analyzed, and N hours electrocardiograms are obtained
Form report the step of include:
Using R wave recognizer, N hours of the ECG data is analyzed, obtains the corresponding heart of each heartbeat in N hours
Electrical waveform;
Clustering processing is carried out to obtained ecg wave form, obtains cluster shape waveform;
According to the waveform morphology of the cluster shape waveform, classify to ecg wave form, and determines ecg wave form classification;
To in N hours different classes of ecg wave form and heartbeat quantity count, form N hours electrocardiogram form reports
It accuses.
In cluster shape waveform provided by the invention, the similarity of waveform morphology is greater than or equal to default first similarity
The ecg wave form of threshold value is divided into same category;
Ecg wave form obtained from ECG data analysis to the analysis lead acquisition checks, finds waveform matter
The step of measuring undesirable ecg wave form and corresponding period include:
The waveform morphology of each ecg wave form is compared with the waveform morphology of default ecg wave form;
If similarity is less than default second similarity threshold, it is determined that the ecg wave form is that waveform quality is undesirable
Ecg wave form;
The undesirable ecg wave form of waveform quality in predetermined amount of time is counted;
If obtained statistical value is greater than preset quality statistical threshold, and the period is undesirable as waveform quality
The ecg wave form corresponding period.
When the invention works, it is carried out firstly, being placed on human body different parts using electrode by electrocardio-data collection module 1
Acquire electrocardiogram data information;The initial parameter of the processing electrocardiogram (ECG) data of electrocardiograph is configured by parameter configuration module 2;Pass through behaviour
Make input module 3 to be input operation instruction using operation keyboard;Secondly, central control module 4 passes through 5 benefit of heart rate discrimination module
Heart rate is carried out with electrocardiosignal of the data processor to acquisition to judge extremely;It is analyzed by data analysis module 6 using data
Program is analyzed and processed the electrocardiogram (ECG) data of acquisition;Then, utilize alarm to the abnormal data of differentiation by alarm module 7
Carry out alert notice;Electrocardiogram is subjected to printing using printer by print module 8;Finally, passing through 9 benefit of display module
With the electrocardiogram (ECG) data of display display acquisition, heart rate abnormal data information.
The above is only the preferred embodiments of the present invention, and is not intended to limit the present invention in any form,
Any simple modification made to the above embodiment according to the technical essence of the invention, equivalent variations and modification, belong to
In the range of technical solution of the present invention.
Claims (5)
1. a kind of for predicting that the surface electrocardiogram processing method of arrhythmia cordis risk occurs for early repolarization individual, feature exists
In the surface electrocardiogram processing method for predicting early repolarization individual generation arrhythmia cordis risk includes:
Step 1 is placed on human body different parts by electrode and is acquired electrocardiogram data information;Pass through the processing of electrocardiograph
The initial parameter of electrocardiogram (ECG) data;It is input operation instruction by operating keyboard;
Step 2 carries out heart rate using electrocardiosignal of the data processor to acquisition and judges extremely;Utilize data analysis program
The electrocardiogram (ECG) data of acquisition is analyzed and processed;
Step 3 carries out alert notice using abnormal data of the alarm moment to differentiation;Printer passes through ant group algorithm for the heart
Electrograph carries out printing;
Step 4, by using electrocardiogram (ECG) data, electrocardiogram and the heart rate exception number of module-cascade constraint formula display display acquisition
It is believed that breath.
2. as described in claim 1 for predicting that the surface electrocardiogram processing side of arrhythmia cordis risk occurs for early repolarization individual
Method, which is characterized in that carry out alert notice using abnormal data of the alarm moment to differentiation, sampling instant is k alarm device
Input variable be u (k), state variable be x (k), output variable be y (k), then alarm is expressed as with abnormal data:
In formula, the output variable of input variable u (k) staff operating unit and detection input unit is constituted, output variable y
(k) be alarm input variable.
3. as described in claim 1 for predicting that the surface electrocardiogram processing side of arrhythmia cordis risk occurs for early repolarization individual
Method, which is characterized in that printer inquires optimal solution by ant group algorithm, and electrocardiogram is carried out accurately printing, specific to walk
It is rapid as follows:
If the position ant k is printout i, ant k selects next printout j that printing is added by following state transition probability
Sequence:
In formula: allowedkAllow the printout of selection for ant k;
α is information heuristic greedy method;
β is expected heuristic value;
τijFor path (i, j) remaining information content;
ηijFor the expected degree of path (i, j);
ηijIndicate the expected degree that i is adjacent with j in printout distributing order;
To reach printout difference in height target as small as possible in batch, by ηijIt is taken as printout i and printout j height difference
It is reciprocal;
After whole ants complete printout traversal, residual risk element is updated;On t+1 circulation rear path (i, j)
Information content be calculated as follows:
τij(t+1)=(1- ρ) τij(t)+Δτij(t);
In formula: ρ is pheromones volatility coefficient, and value range is [0,1];
ΔτijIt (t) is the pheromones increment on path (i, j) in this circulation, Pheromone update uses ant week model (Ant-
CycleModel);
In formula: Q is constant, indicate ant recycle one week the total amount through release pheromone on path;
LkThe total length for walking path in this circulation by kth ant, when the number of iterations reaches setting maximum number of iterations
When, algorithm stops, and history optimal solution is Optimum Solution.
4. a kind of implement described in claim 1 for predicting that early repolarization individual occurs at the surface electrocardiogram of arrhythmia cordis risk
Reason method is used to predict that arrhythmia cordis risk surface electrocardiogram processing system to occur for multipole individual, which is characterized in that the use
Arrhythmia cordis risk surface electrocardiogram processing system, which occurs, in prediction multipole individual includes:
Electrocardio-data collection module, connect with central control module, is adopted for being placed on human body different parts by electrode
Collect electrocardiogram data information;
Parameter configuration module is connect with central control module, the initial parameter of the processing electrocardiogram (ECG) data for configuring electrocardiograph;
Operation input module, connect with central control module, for being input operation instruction by operating keyboard;
Central control module, with electrocardio-data collection module, parameter configuration module, operation input module, heart rate discrimination module, number
According to analysis module, alarm module, print module, display module connection, worked normally for controlling modules by single-chip microcontroller;
Heart rate discrimination module, connect with central control module, for being carried out by electrocardiosignal of the data processor to acquisition
Heart rate judges extremely;
Data analysis module is connect with central control module, for being carried out by electrocardiogram (ECG) data of the data analysis program to acquisition
Analysis processing;
Alarm module is connect with central control module, for carrying out alert notice by abnormal data of the alarm to differentiation;
Print module is connect with central control module, for electrocardiogram to be carried out printing by printer;
Display module is connect with central control module, for electrocardiogram (ECG) data, the heart rate abnormal data by display display acquisition
Information.
5. it is a kind of using claims 1 to 3 any one be for predict early repolarization individual occur arrhythmia cordis risk body
The computer of table ECG treatment method.
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Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113891677A (en) * | 2019-03-18 | 2022-01-04 | 心脏起搏器股份公司 | System and method for predicting atrial arrhythmias |
CN114469041A (en) * | 2022-01-30 | 2022-05-13 | 北京理工大学 | Heart rate change data characteristic analysis method in exercise process |
CN114469131A (en) * | 2021-12-13 | 2022-05-13 | 中国科学院深圳先进技术研究院 | Self-adaptive real-time electrocardiosignal quality evaluation method |
Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN2038369U (en) * | 1988-10-12 | 1989-05-31 | 珠海市八达技术会社 | Portable electro-cardio monitor |
CN1110121A (en) * | 1994-04-14 | 1995-10-18 | 王湘生 | Wearing type superminiature heart protecting system and method |
CN1187338A (en) * | 1997-01-10 | 1998-07-15 | 张昊 | Multifunctional dynamic heart monitoring warning system |
CN201537088U (en) * | 2009-11-26 | 2010-08-04 | 马慧彬 | Portable electrocardiograph |
CN101904250A (en) * | 2009-06-02 | 2010-12-08 | 中国农业机械化科学研究院 | Method and device for measuring feeding amount of combine harvester |
CN203107119U (en) * | 2013-01-21 | 2013-08-07 | 孙秋 | Electrocardiogram monitoring recording analyzer with intelligent control system |
CN103859721A (en) * | 2014-04-09 | 2014-06-18 | 江南大学 | Intelligent walking stick for tumbling remote monitoring and nursing |
CN105334514A (en) * | 2015-10-19 | 2016-02-17 | 上海无线电设备研究所 | Tramcar radar video compound early warning crashproof system and method |
-
2018
- 2018-11-28 CN CN201811438292.1A patent/CN109350022A/en active Pending
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN2038369U (en) * | 1988-10-12 | 1989-05-31 | 珠海市八达技术会社 | Portable electro-cardio monitor |
CN1110121A (en) * | 1994-04-14 | 1995-10-18 | 王湘生 | Wearing type superminiature heart protecting system and method |
CN1187338A (en) * | 1997-01-10 | 1998-07-15 | 张昊 | Multifunctional dynamic heart monitoring warning system |
CN101904250A (en) * | 2009-06-02 | 2010-12-08 | 中国农业机械化科学研究院 | Method and device for measuring feeding amount of combine harvester |
CN201537088U (en) * | 2009-11-26 | 2010-08-04 | 马慧彬 | Portable electrocardiograph |
CN203107119U (en) * | 2013-01-21 | 2013-08-07 | 孙秋 | Electrocardiogram monitoring recording analyzer with intelligent control system |
CN103859721A (en) * | 2014-04-09 | 2014-06-18 | 江南大学 | Intelligent walking stick for tumbling remote monitoring and nursing |
CN105334514A (en) * | 2015-10-19 | 2016-02-17 | 上海无线电设备研究所 | Tramcar radar video compound early warning crashproof system and method |
Non-Patent Citations (2)
Title |
---|
王宇等: ""LED显示屏实现高质量图像显示的扫描算法分析"", 《电子器件》 * |
郝南海: ""基于蚁群算法的3D打印批次规划"", 《制造技术与机床》 * |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113891677A (en) * | 2019-03-18 | 2022-01-04 | 心脏起搏器股份公司 | System and method for predicting atrial arrhythmias |
CN114469131A (en) * | 2021-12-13 | 2022-05-13 | 中国科学院深圳先进技术研究院 | Self-adaptive real-time electrocardiosignal quality evaluation method |
CN114469041A (en) * | 2022-01-30 | 2022-05-13 | 北京理工大学 | Heart rate change data characteristic analysis method in exercise process |
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