CN104274907A - Defibrillation success probability predicting method and defibrillation instrument - Google Patents
Defibrillation success probability predicting method and defibrillation instrument Download PDFInfo
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Abstract
The invention discloses a defibrillation success probability predicting method, and relates to the technical field of electric defibrillation. The method includes the steps of obtaining electrocardio signals of a patient through a defibrillation electrode, conducting digitalized collection after amplifying and filtering are conducted, mapping collected one-dimensional electrocardio data to a two-dimensional plane after delaying the one-dimensional electrocardio data by a certain period of time, calculating phase space scale parameters through the morphology and distribution of a two-dimensional mapping scatter diagram, establishing a multi-parameter predicting function model through a mathematical modeling method, and calculating the index for predicting the defibrillation success, wherein the phase space scale parameters include the scatter data distribution width and the scatter data distribution uniform degree. The method has the advantages that the duration for collecting and analyzing signals is short, and therefore the treatment of a ventricular fibrillation patient can not be influenced; the phase space scale is calculated in real time, the defibrillation success probability is evaluated, and guidance advises are provided for medical staff so that the medical staff can know whether to immediately conduct defibrillation or not; the precision of the defibrillation success probability predicting method is higher than that of an existing defibrillation success probability predicting method.
Description
Technical field
The present invention relates to a kind of electric defibrillation technical field, particularly a kind of method predicting the defibrillation probability of success.
Background technology
Electric defibrillation is an important link in cardio-pulmonary resuscitation (CPR) process, and it refers to a certain amount of rush of current heart thus ventricular fibrillation is stopped.The success or not direct relation of electric defibrillation the survival of ventricular fibrillation patient, is treatment ventricular fibrillation effective method the most.Whether research shows, occurs the electrocardiosignal of ventricular fibrillation patient, grasp patient heart condition that can be real-time by analyzing, and successfully can make electric defibrillation this moment and effectively to judge and prediction.The prediction of this defibrillation usefulness can greatly reduce unnecessary electric defibrillation, just carries out defibrillation, reduce the damage of electric current to patient's cardiac muscle when only having some index when electrocardiosignal to reach expection threshold value.
At present, the successful algorithm of prediction electric defibrillation emerges in an endless stream, and its method mainly realizes the prediction of defibrillation usefulness based on amplitude, frequency and amplitude-frequency analysis.But the accuracy rate of most of algorithm predicts is high not enough, the signal length required for analysis is longer, and these all can affect the treatment of the patient that to quiver to room.
Therefore, need explore a kind of accurately simple, and the method for the prediction defibrillation probability of success of short-time analysis can be realized, to overcome now methodical deficiency.
Summary of the invention
In view of this, the technical problem to be solved in the present invention is to provide a kind of method predicting the defibrillation probability of success, and short-time analysis, effective judgement and prediction carry out the successful probability of electric defibrillation to patient.
The present invention is solved the problems of the technologies described above by following technological means:
The invention provides a kind of method predicting the defibrillation probability of success, specifically comprise the following steps:
Step one: gather ecg signal data;
Step 2: the electrocardiogram (ECG) data figure choosing 0.1s ~ 10s from the electrocardiosignal of described collection is analyzed, and the described signal chosen is carried out time delay, described in the signal chosen be abscissa, the signal after time delay is that vertical coordinate draws two-dimentional scatterplot;
Step 3: analyze described two-dimentional scatterplot, obtains the peak width Width of loose point data distribution and evaluates the standard B of loose point data distributing homogeneity;
Step 4: by the peak width Width of described loose point data distribution and the standard B founding mathematical models evaluating loose point data distributing homogeneity, calculate phase space yardstick PSS;
Step 5: according to described phase space yardstick PSS, obtains the successful probability of prediction defibrillation.
Further, the concrete analysis process of step 3 described above is:
Described two-dimentional scatterplot is analyzed, calculate the distance d of each loose point to straight line x=y, find distance d, the sample point making distance be less than d accounts for 95% of all data points, and be boundary with 1.5d, get rid of the exceptional data point that distance value is greater than 1.5d, the distance maximum in calculated line x=y two side data is also added the peak width obtaining the distribution of loose point data: Width=max
up+ max
down, wherein, Width is the peak width of loose point data distribution, max
upfor a distance straight line x=y is fallen apart apart from numerical value farthest in top, max
downfor a distance straight line x=y is fallen apart apart from numerical value farthest in bottom;
Be that standard does demarcation line with Width/2, calculate the data point sum N that demarcation line is upper and lower, the difference of counting up and down using demarcation line is as the standard B:B=|N evaluating loose point data distributing homogeneity
up-N
down|, wherein, N
uprepresent the data point sum on top, demarcation line, N
downrepresent the data point sum of bottom, demarcation line.
Further, described phase space yardstick PSS:
PSS=K*Width-Y*B, wherein, K is loose some width weight coefficient, and Y is the weight coefficient of uniformity coefficient, and Width is the peak width of loose point data distribution, and B is the standard evaluating loose point data distributing homogeneity.
Further, described phase space yardstick PSS:
PSS=10*Width-0.0004*B, wherein, Width is the peak width of loose point data distribution, and B is the standard evaluating loose point data distributing homogeneity.
Further, when described phase space yardstick PSS value is more than or equal to 0.45, defibrillation success, when described phase space yardstick PSS value is less than 0.45, defibrillation failure.
The present invention provides a kind of defibrillator in addition, comprises ecg signal acquiring module, for gathering patient's electrocardiogram (ECG) data; Electrocardiosignal time delay module, for choosing the described electrocardiogram (ECG) data of 0.1s ~ 10s and carrying out time delay to described electrocardiogram (ECG) data; Electrocardiogram (ECG) data processing module, for carrying out two-dimentional Scatter plot to the electrocardiogram (ECG) data after described time delay, the described electrocardiogram (ECG) data chosen is abscissa, signal after time delay is that vertical coordinate draws two-dimentional scatterplot, obtain the peak width Width of loose point data distribution and evaluate the standard B of loose point data distributing homogeneity, the standard B of the peak width Width loose point data distributed and the loose point data distributing homogeneity of evaluation carries out mathematical modeling, calculates phase space yardstick PSS; Output module, for exporting prompting suggestion according to the value of described phase space yardstick PSS, described ecg signal acquiring module, electrocardiosignal time delay module, electrocardiogram (ECG) data processing module are connected in turn with output module.
Further, the processing procedure of described electrocardiogram (ECG) data processing module is: analyze described two-dimentional scatterplot, calculate the distance d of each loose point to straight line x=y, find distance d, the sample point making distance be less than d accounts for 95% of all data points, and be boundary with 1.5d, get rid of the exceptional data point that distance value is greater than 1.5d, the distance maximum in calculated line x=y two side data is also added the peak width Width:Width=max obtaining the distribution of loose point data
up+ max
down, wherein, Width is the peak width of loose point data distribution, max
upfor a distance straight line x=y is fallen apart apart from numerical value farthest in top, max
downfor a distance straight line x=y is fallen apart apart from numerical value farthest in bottom;
Be that standard does demarcation line with Width/2, calculate the data point sum N that demarcation line is upper and lower, the difference of counting up and down using demarcation line is as the standard B:B=|N evaluating loose point data distributing homogeneity
up-N
down|, wherein, N
uprepresent the data point sum on top, demarcation line, N
downrepresent the data point sum of bottom, demarcation line;
Further, described electrocardiogram (ECG) data processing module calculates the formula of phase space yardstick PSS: PSS=K*Width-Y*B, wherein, K is loose some width weight coefficient, Y is the weight coefficient of uniformity coefficient, and Width is the width that loose point data is scattered, and B is the standard evaluating loose point data distributing homogeneity;
Further, described electrocardiogram (ECG) data processing module calculates the formula of phase space yardstick PSS: PSS=10*Width-0.0004*B, and wherein, Width is the peak width of loose point data distribution, and B is the standard evaluating loose point data distributing homogeneity;
Further, when the value of the described phase space yardstick PSS calculated is more than or equal to 0.45, described output module exports prompting advise defibrillation, and when described phase space yardstick PSS value is less than 0.45, described output module exports suggestion and continues pressing.
Beneficial effect of the present invention: first the method obtains patient's electrocardiosignal by defibrillation electrode, after amplification filtering, carry out digital collection, afterwards the one dimension electrocardiogram (ECG) data collected is mapped on two dimensional surface after the time delay of certain hour, again by form and the distribution calculating phase space scale parameter of two-dimensional map scatterplot, comprise the width of loose point data distribution and the uniformity coefficient of loose point data distribution, finally by the method establishment multi-parameter prediction function model of mathematical modeling, the successful index of computational prediction defibrillation.The length of the method collection analysis signal is short, can not affect the treatment of the patient that to quiver to room, calculates the value of phase space yardstick in real time, evaluates the successful probability of defibrillation, for medical personnel provide the guiding opinion the need of defibrillation at once, to reach best defibrillation effect.The present invention is adopted to predict that the method accuracy rate of the successful likelihood ratio of the defibrillation existing prediction defibrillation probability of success is high.
Defibrillator of the present invention, carry out analyzing and processing to the electrocardiosignal gathering patient, calculate the value of phase space yardstick, output module exports advise defibrillation according to phase space yardstick or suggestion continues pressing, can at short notice for medical personnel offer suggestions, the treatment of patient that room quivered can not be affected.
Accompanying drawing explanation
Below in conjunction with drawings and Examples, the invention will be further described.
Fig. 1 is the workflow diagram that the present invention predicts the method for the defibrillation probability of success;
Fig. 2 is the two-dimentional scatterplot that the present invention predicts the method for the defibrillation probability of success;
Fig. 3 is that the present invention predicts the prediction defibrillation success of the method for the defibrillation probability of success and the schematic diagram of prediction defibrillation failure;
Fig. 4 is the structural representation of defibrillator of the present invention.
Detailed description of the invention
Below with reference to accompanying drawing, the present invention is described in detail, as shown in Figure 1:
The method of the prediction defibrillation probability of success of the present invention, comprises the following steps:
Step one: gather ecg signal data, obtained the electrocardiosignal of patient by defibrillation electrode, and carry out pretreatment by band filter, band filter frequency range is 2Hz ~ 48Hz.
Step 2: select the electrocardiogram (ECG) data image of 0.1s ~ 10s to analyze with rectangular window before defibrillation, after the signal chosen is carried out time delay τ, and using original signal as transverse axis coordinate, signal after time delay draws two-dimentional scatterplot as ordinate of orthogonal axes, one dimension electrocardiogram (ECG) data is mapped on two dimensional surface, wherein τ=3ms.
Step 3: as shown in Figure 2, two-dimentional scatterplot is analyzed, calculate the distance of each loose point to straight line x=y, find distance d, the sample point making distance be less than d accounts for 95% of all data points, and is boundary with 1.5d, distance value is greater than getting rid of a little of 1.5d, exclude point in Fig. 2 needs to get rid of, and what distance value was greater than 1.5d is a little exceptional data point.Distance maximum in calculated line x=y two side data is also added the peak width Width obtaining the distribution of loose point data, Width=max
up+ max
down, wherein, Width represents the peak width that loose point data distributes, max
upfor a distance straight line x=y is fallen apart apart from numerical value farthest in top, max
downfor a distance straight line x=y is fallen apart apart from numerical value farthest in bottom.Be that standard does demarcation line with Width/2, calculate the data point sum N that demarcation line is upper and lower, the difference of counting up and down using demarcation line is as the standard B:B=|N evaluating loose point data distributing homogeneity
up-N
down|, wherein N
uprepresent the data point sum on top, demarcation line, N
downrepresent the data point sum of bottom, demarcation line.
Step 4: comprehensive peak width Width and the DATA DISTRIBUTION uniformity coefficient B founding mathematical models analyzing loose point data distribution, calculates the phase space yardstick PSS for predicting defibrillation usefulness:
PSS＝K*Width–Y*B
Wherein, K is loose some width weight coefficient, and Y is the weight coefficient of uniformity coefficient.When sample rate is fixed as 300Hz, K value 10, Y changes adjustment according to analytical data length, when getting 0.5 second data analysis, and Y value 0.0004.
Obtain through a large amount of experiments: K value is fixed as 10, B value and is fixed as 0.0004, sample rate is not fixed, too much influence be there is no to the result calculated, that is:
PSS＝10*Width–0.0004*B。
Step 5: according to phase space yardstick PSS, obtains the successful probability of prediction defibrillation.As shown in Figure 3, a in () figure, data get 2s electrocardiosignal before defibrillation, PSS=0.48 is calculated according to above-mentioned steps, defibrillation success, b in () figure, data get 2s electrocardiosignal before defibrillation, PSS=0.41 is calculated, defibrillation failure, not advise defibrillation in practical operation according to above-mentioned steps.When PSS threshold value is set as 0.45, defibrillation sensitivity reaches 71.30%, and specificity reaches 71.57%.When PSS is more than or equal to 0.45, prediction defibrillation can have larger success rate, otherwise the probability being less than 0.45 defibrillation failure is very large, not advise defibrillation.PSS threshold value is set as that 0.45, PSS also can as the case may be and need to adjust by ordinary circumstance.
In order to prove that the present invention predicts that the successful method of defibrillation is better than additive method and has carried out contrast experiment, by analyzing 214 cardiac arrest patients' 416 defibrillation results with diverse ways, the successful probability of prediction defibrillation.The method adopted comprises method of the present invention (PSS), amplitude area spectrum (AMSA), signal integration (SIGINT), intermediate value slope (MS) and power spectrumanalysis (PSA).The parametric results that diverse ways obtains is compared, parameter relatively comprises: specificity Spe when area AUC, sensitivity S en are 85% under receiver operating characteristic curve, positive prediction rate PPV, negative predictive rate NPV and accuracy rate Accuracy, as shown in table 1.Wherein, predict that the successful probability key parameter of defibrillation is area AUC and accuracy rate Accuracy under receiver operating characteristic curve.Result shows, under the receiver operating characteristic curve adopting method of the present invention to obtain, area AUC and accuracy rate Accuracy is all higher than other several methods, so adopt method of the present invention to be better than other existing method.
| Method | AUC | Sen/Spe[％] | PPV/NPV[％] | Accuracy[％] |
| PSS | 0.802 | 84.26/56.86 | 40.81/91.10 | 64.01 |
| AMSA | 0.786 | 84.26/53.27 | 38.89/90.56 | 61.14 |
| SIGNINT | 0.772 | 84.26/54.90 | 39.74/90.81 | 62.56 |
| MS | 0.784 | 84.26/55.56 | 40.09/90.91 | 63.04 |
| PSA | 0.776 | 84.26/53.57 | 39.22/90.66 | 61.84 |
The parameter comparison sheet that table 1 method of the present invention and existing algorithm obtain
Method of the present invention can be built in defibrillator, analyzes the state of patient's electrocardiosignal.In During Cardiopulmonary Resuscitation, real-time calculating phase space scale parameter, evaluate carry out defibrillation this moment can successful probability, provide the guiding opinion the need of defibrillation at once, to reach the defibrillation effect of the best to first-aid personnel.
A kind of defibrillator, as shown in Figure 4, comprises ecg signal acquiring module, for gathering patient's electrocardiogram (ECG) data; Electrocardiosignal time delay module, for choosing the described electrocardiogram (ECG) data of 0.1s ~ 10s and carrying out time delay to described electrocardiogram (ECG) data; Electrocardiogram (ECG) data processing module, for carrying out two-dimentional Scatter plot to the electrocardiogram (ECG) data after described time delay, the described electrocardiogram (ECG) data chosen is abscissa, signal after time delay is that vertical coordinate draws two-dimentional scatterplot, obtain the peak width Width of loose point data distribution and evaluate the standard B of loose point data distributing homogeneity, the standard B of the peak width Width loose point data distributed and the loose point data distributing homogeneity of evaluation carries out mathematical modeling, calculates phase space yardstick PSS; Output module, for exporting prompting suggestion according to the value of described phase space yardstick PSS, described ecg signal acquiring module, electrocardiosignal time delay module, electrocardiogram (ECG) data processing module are connected in turn with output module.
Ecg signal acquiring module acquires ecg signal data, obtained the electrocardiosignal of patient by defibrillation electrode, and carry out pretreatment by band filter, band filter frequency range is 2Hz ~ 48Hz.
Electrocardiosignal time delay module be used for by ecg signal acquiring module acquires to electrocardiogram (ECG) data carry out time delay, detailed process is: select the electrocardiogram (ECG) data image of 0.1s ~ 10s to analyze with rectangular window before defibrillation, after the signal chosen is carried out time delay τ, and using original signal as transverse axis coordinate, signal after time delay draws two-dimentional scatterplot as ordinate of orthogonal axes, one dimension electrocardiogram (ECG) data is mapped on two dimensional surface, wherein τ=3ms.
The concrete processing procedure of ECG's data compression module: the two-dimentional scatterplot of the electrocardiogram (ECG) data after time delay is analyzed, calculate the distance of each loose point to straight line x=y, find distance d, the sample point making distance be less than d accounts for 95% of all data points, and be boundary with 1.5d, distance value is greater than getting rid of a little of 1.5d, what distance value was greater than 1.5d is a little exceptional data point.Distance maximum in calculated line x=y two side data is also added the peak width Width obtaining the distribution of loose point data, Width=max
up+ max
down, wherein, Width represents the peak width that loose point data distributes, max
upfor a distance straight line x=y is fallen apart apart from numerical value farthest in top, max
downfor a distance straight line x=y is fallen apart apart from numerical value farthest in bottom.Be that standard does demarcation line with Width/2, calculate the data point sum N that demarcation line is upper and lower, the difference of counting up and down using demarcation line is as the standard B:B=|N evaluating loose point data distributing homogeneity
up-N
down|, wherein N
uprepresent the data point sum on top, demarcation line, N
downrepresent the data point sum of bottom, demarcation line.Comprehensive analysis fall apart point data distribution peak width Width and DATA DISTRIBUTION uniformity coefficient B founding mathematical models, calculate the phase space yardstick PSS:PSS=K*Width – Y*B for predicting defibrillation usefulness, wherein, K is loose some width weight coefficient, and Y is the weight coefficient of uniformity coefficient.When sample rate is fixed as 300Hz, K value 10, Y changes adjustment according to analytical data length, when getting 0.5 second data analysis, and Y value 0.0004.Obtain through a large amount of experiments: K value is fixed as 10, B value and is fixed as 0.0004, sample rate is not fixed, too much influence is not had, that is: PSS=10*Width – 0.0004*B to the result calculated.
Output module, according to the value judgement output prompting of the phase space yardstick PSS that ECG's data compression resume module obtains, when phase space yardstick PSS is more than or equal to 0.45, the successful probability of prediction defibrillation is very large, output module exports prompting advise defibrillation, and when phase space yardstick PSS is less than 0.45, the likelihood ratio of prediction defibrillation failure is larger, not advise defibrillation, output module exports prompting and continues pressing.
What finally illustrate is, above embodiment is only in order to illustrate technical scheme of the present invention and unrestricted, although with reference to preferred embodiment to invention has been detailed description, those of ordinary skill in the art is to be understood that, can modify to technical scheme of the present invention or equivalent replacement, and not departing from aim and the scope of technical solution of the present invention, it all should be encompassed in the middle of right of the present invention.
Claims (10)
1. predict a method for the defibrillation probability of success, it is characterized in that: comprise the following steps:
Step one: gather ecg signal data;
Step 2: the electrocardiogram (ECG) data figure choosing 0.1s ~ 10s from the electrocardiosignal of described collection is analyzed, and the described signal chosen is carried out time delay, described in the signal chosen be abscissa, the signal after time delay is that vertical coordinate draws two-dimentional scatterplot;
Step 3: analyze described two-dimentional scatterplot, obtains the peak width Width of loose point data distribution and evaluates the standard B of loose point data distributing homogeneity;
Step 4: by the peak width Width of described loose point data distribution and the standard B founding mathematical models evaluating loose point data distributing homogeneity, calculate phase space yardstick PSS;
Step 5: according to described phase space yardstick PSS, obtains the successful probability of prediction defibrillation.
2. the method for claim 1, is characterized in that: the concrete analysis process of described step 3 is:
Described two-dimentional scatterplot is analyzed, calculate the distance d of each loose point to straight line x=y, find distance d, the sample point making distance be less than d accounts for 95% of all data points, and be boundary with 1.5d, get rid of the exceptional data point that distance value is greater than 1.5d, the distance maximum in calculated line x=y two side data is also added the peak width Width:Width=max obtaining the distribution of loose point data
up+ max
down, wherein, Width is the peak width of loose point data distribution, max
upfor a distance straight line x=y is fallen apart apart from numerical value farthest in top, max
downfor a distance straight line x=y is fallen apart apart from numerical value farthest in bottom;
Be that standard does demarcation line with Width/2, calculate the data point sum N that demarcation line is upper and lower, the difference of counting up and down using demarcation line is as the standard B:B=|N evaluating loose point data distributing homogeneity
up-N
down|, wherein, N
uprepresent the data point sum on top, demarcation line, N
downrepresent the data point sum of bottom, demarcation line.
3. method as claimed in claim 1 or 2, is characterized in that: described phase space yardstick PSS:
PSS=K*Width-Y*B, wherein, K is loose some width weight coefficient, and Y is the weight coefficient of uniformity coefficient, and Width is the peak width of loose point data distribution, and B is the standard evaluating loose point data distributing homogeneity.
4. method as claimed in claim 3, is characterized in that: described phase space yardstick PSS:
PSS=10*Width-0.0004*B, wherein, Width is the peak width of loose point data distribution, and B is the standard evaluating loose point data distributing homogeneity.
5. method as claimed in claim 4, is characterized in that: when described phase space yardstick PSS value is more than or equal to 0.45, defibrillation success, when described phase space yardstick PSS value is less than 0.45, and defibrillation failure.
6. a defibrillator, is characterized in that: comprise ecg signal acquiring module, for gathering patient's electrocardiogram (ECG) data; Electrocardiosignal time delay module, for choosing the described electrocardiogram (ECG) data of 0.1s ~ 10s and carrying out time delay to described electrocardiogram (ECG) data; Electrocardiogram (ECG) data processing module, for carrying out two-dimentional Scatter plot to the electrocardiogram (ECG) data after described time delay, the described electrocardiogram (ECG) data chosen is abscissa, signal after time delay is that vertical coordinate draws two-dimentional scatterplot, obtain the peak width Width of loose point data distribution and evaluate the standard B of loose point data distributing homogeneity, the standard B of the peak width Width loose point data distributed and the loose point data distributing homogeneity of evaluation carries out mathematical modeling, calculates phase space yardstick PSS; Output module, for exporting prompting suggestion according to the value of described phase space yardstick PSS, described ecg signal acquiring module, electrocardiosignal time delay module, electrocardiogram (ECG) data processing module are connected in turn with output module.
7. defibrillator as claimed in claim 6, it is characterized in that: the processing procedure of described electrocardiogram (ECG) data processing module is: described two-dimentional scatterplot is analyzed, calculate the distance d of each loose point to straight line x=y, find distance d, the sample point making distance be less than d accounts for 95% of all data points, and be boundary with 1.5d, get rid of the exceptional data point that distance value is greater than 1.5d, the distance maximum in calculated line x=y two side data is also added the peak width Width:Width=max obtaining the distribution of loose point data
up+ max
down, wherein, Width is the peak width of loose point data distribution, max
upfor a distance straight line x=y is fallen apart apart from numerical value farthest in top, max
downfor a distance straight line x=y is fallen apart apart from numerical value farthest in bottom;
Be that standard does demarcation line with Width/2, calculate the data point sum N that demarcation line is upper and lower, the difference of counting up and down using demarcation line is as the standard B:B=|N evaluating loose point data distributing homogeneity
up-N
down|, wherein, N
uprepresent the data point sum on top, demarcation line, N
downrepresent the data point sum of bottom, demarcation line.
8. defibrillator as claimed in claim 6, it is characterized in that: described electrocardiogram (ECG) data processing module calculates the formula of phase space yardstick PSS: PSS=K*Width-Y*B, wherein, K is loose some width weight coefficient, Y is the weight coefficient of uniformity coefficient, Width is the peak width of loose point data distribution, and B is the standard evaluating loose point data distributing homogeneity.
9. defibrillator as claimed in claim 8, it is characterized in that: described electrocardiogram (ECG) data processing module calculates the formula of phase space yardstick PSS: PSS=10*Width-0.0004*B, wherein, Width is the peak width of loose point data distribution, and B is the standard evaluating loose point data distributing homogeneity.
10. defibrillator as claimed in claim 9, it is characterized in that: when the value of described phase space yardstick PSS is more than or equal to 0.45, described output module exports prompting advise defibrillation, and when described phase space yardstick PSS value is less than 0.45, described output module exports suggestion and continues pressing.
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| CN112315485B (en) * | 2019-07-18 | 2023-06-23 | 查宇亮 | Quality capability quantitative evaluation method based on asymmetric cardiac cycle change |
| CN111803054A (en) * | 2020-06-12 | 2020-10-23 | 中国人民解放军陆军军医大学 | Method and instrument for evaluating ventricular fibrillation signal quality and defibrillation success rate in real time |
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