CN101461711A - Shockable rhythm recognition algorithm based on standard deviation of standard slope absolute value - Google Patents
Shockable rhythm recognition algorithm based on standard deviation of standard slope absolute value Download PDFInfo
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Abstract
一种基于标准化斜率绝对值标准差的可电击复律心律识别算法，适用于疾病的诊治仪器或装置，包括步骤：S1.对心电信号进行预处理；S2.对心电信号进行心脏停搏心律的识别：若为心脏停搏心律，则判为不可电击复律心律；若不是心脏停搏心律，则继续执行后续步骤S3，S4；S3.计算标准化斜率绝对值标准差；S4.根据标准化斜率绝对值标准差来辨别是否为不可电击复律心律或可电击复律心律。本发明提高了识别可电击复律心律的灵敏度和特异性，也简化了算法的计算复杂度，可应用于心电监护仪和自动体外除颤器等需要根据体表心电图识别可电击复律心律的仪器设备。
A shockable cardioversion heart rhythm recognition algorithm based on the standard deviation of the absolute value of the standardized slope, which is suitable for a disease diagnosis and treatment instrument or device, including steps: S1. Preprocessing the ECG signal; S2. Performing cardiac arrest on the ECG signal Identification of heart rhythm: if it is a cardiac arrest rhythm, it is judged as a non-shockable cardioversion rhythm; if it is not a cardiac arrest rhythm, continue to perform subsequent steps S3, S4; S3. Calculate the standard deviation of the absolute value of the standardized slope; S4. According to the standardized The standard deviation of the absolute value of the slope is used to distinguish whether it is a non-shockable rhythm or a shockable rhythm. The invention improves the sensitivity and specificity of identifying shockable heart rhythms, and also simplifies the calculation complexity of the algorithm, and can be applied to electrocardiographic monitors and automatic external defibrillators, etc., which need to identify shockable heart rhythms based on body surface electrocardiograms equipment.
Description
Technical field
The present invention relates to a kind of electrocardiosignal (ECG) recognition methods, but the particularly a kind of Electrical Cardioversion rhythm of the heart (Shockable Rhythm, ShR) recognizer of improving existing electrocardiogram monitor and automated external defibrillator performance.
Background technology
Sudden cardiac death (SCD) is meant the natural death of the unexpected generation that causes owing to the heart reason.The reason major part that causes sudden cardiac death is momentary dysfunction and the electrophysiological change that takes place on all kinds of cardiovascular pathological changes basis, and cause that malignant ventricular arrhythmia such as ventricular tachycardia (are called for short chamber speed, VT), ventricular fibrillation (is called for short the chamber and quivers, VF) etc.Electric defibrillation is the first-selected effective ways that stop most rapidity malignant ventricular arrhythmias.
1997, American Heart Association (AHA) has delivered a suggestion relevant with automated external defibrillator (AED) algorithm performance report " automated external defibrillator that is used for the public arena defibrillation: to illustrating and the performance of the arrhythmia analysis algorithm of report on (Circulation) magazine in circulation, comprise the suggestion of new waveform and raising safety " (" Automatic External Defibrillators forPublic Access Defibrillation:Recommendations for Specifying and ReportingArrhythmia Analysis Algorithm Performance, Incorporating New Waveforms, and Enhancing Safety. ").
This suggestion is divided into following three major types with the rhythm of the heart: but the Electrical Cardioversion rhythm of the heart (shockable rhythms, ShR), can not the Electrical Cardioversion rhythm of the heart (nonshockable rhythms, NShR) and the middle rhythm of the heart (Intermediate rhythms).
At present but the Electrical Cardioversion rhythm recognition algorithm of bibliographical information exists variety of issue, as since the chamber when quivering Electrocardiographic form can change a lot, but various algorithm based on ECG R wave identification is not suitable for the differentiation of the Electrical Cardioversion rhythm of the heart; Phase space rebuild (Phase Space ReconstructionAlgorithm, PSR) algorithm, signal comparison algorithm (Signal Comparison Algorithm, though SCA) wait very high specificity is arranged, sensitivity is very poor; And some are based on the algorithm computation complexity of various conversion and analysis of complexity, to having relatively high expectations of hardware.So, but the differentiation algorithm of the existing Electrical Cardioversion rhythm of the heart still exists sensitivity and specificity not to take into account, or problem such as calculation of complex, for example, as typical example, also there are some such shortcomings in the HILB algorithm application in the instrument or device of the diagnosis and treatment of disease, the HILB algorithm has used method-Hilbert transform method of often using when analyzing nonlinear properties to make up phase space.Suppose that electrocardiosignal is x (t), obtain x after it is done Hilbert transform
H(t), if, use x with x (t) expression x axial coordinate
H(t) represent the y axial coordinate, just constructed the phase space of a two dimension.In such phase space, the track of chaotic signal can be more mixed and disorderly than the track of rule signal.People such as Anoton, Robert and Karl find that the trajectory of phase space of VF signal is more mixed and disorderly than the trajectory of phase space of SR (sinus rhythm) signal.So they suppose that the VF signal is a chaos, and the SR signal is a rule.They are divided into the grid of 40 identical sizes of 40 x with the phase space that builds, and the grid of the trajectory of phase space process of statistics electrocardiosignal is counted.Because the SR signal is a rule, the VF signal is a chaos, so compare with the trajectory of phase space of SR signal, the trajectory of phase space of VF signal can pass through more grid.
In order to reduce amount of calculation, also need signal is done down-sampled.
The detailed process of HILB algorithm is as follows:
1. down-sampled with 50Hz to signal.
2. the Hilbert transform of electrocardiosignal x (t) is x
H(t), make up the phase space of 40 x, 40 lattice, calculate (x (t), x
H(t)) shared lattice are counted visited boxes in constructed phase space.
3. definition
And to get threshold value be d0,
If d〉d0, then be judged to VF;
If d＜=d0 then is judged to SR.
Summary of the invention:
As mentioned above, but for electrocardiogram monitor and automated external defibrillator provide the Electrical Cardioversion rhythm recognition algorithm of discriminant accuracy height and fast operation, be technical problem to be solved by this invention.For this reason, but the object of the present invention is to provide a kind of discern accurately, calculate simple, can satisfy application requirements, based on the Electrical Cardioversion rhythm recognition algorithm of standard slope absolute value standard deviation, but to improve the existing performance that needs to use the instrument and equipment of Electrical Cardioversion rhythm of the heart recognition methods.
Technical scheme of the present invention is as follows:
But the Electrical Cardioversion rhythm recognition algorithm of a kind of standard slope absolute value standard deviation that proposes according to the present invention comprises that step is as follows:
At first, electrocardiosignal is carried out the identification of the asystole rhythm of the heart:
If the asystole rhythm of the heart then is judged to NShR;
If not the asystole rhythm of the heart, then carry out the step of back.
Normalized slope absolute value standard deviation;
Differentiate NShR and ShR according to standard slope absolute value standard deviation,
Discrimination standard is:
If standard slope absolute value standard deviation 〉=threshold value, then be judged to NShR;
If standard slope absolute value standard deviation＜threshold value then is judged to ShR.
The detailed process of the above-mentioned identification asystole rhythm of the heart is:
Amplitude is judged to the asystole rhythm of the heart less than the electrocardiosignal of 80uV.
The detailed process of aforementioned calculation standard slope absolute value standard deviation is:
At first, one section electrocardiogram (ECG) data is divided into segment by identical interval, each segment is called a grizzly bar (bar), and each interval is called grill width (barwidth);
Then, calculate the absolute value (slope) of the difference of last interior sampling point of each grizzly bar and first sampling point, i.e. slope
i=abs (signal
i(barwidth)-signal
i(i)), slope wherein
iThe slope absolute value of representing i grizzly bar, signal
iRepresent the sampling point sequence in i the grizzly bar;
Then, calculate the standard deviation (slope_std) of all slope absolute values;
At last, to the slope_std standardization, promptly slope_std/mean (slope) obtains standard slope absolute value standard deviation (slope_stdnor).
Owing to adopted above technical scheme, but improved the sensitivity and the specificity of the identification Electrical Cardioversion rhythm of the heart.Also simplified the computation complexity of algorithm in addition.The present invention can be applicable to electrocardiogram monitor and automated external defibrillator (AED) but etc. need be according to the instrument and equipment of the surface electrocardiogram identification Electrical Cardioversion rhythm of the heart.
Description of drawings:
Fig. 1 is main process figure of the present invention.
Fig. 2 is the flow chart of " S1 pretreatment " step among the main process figure of the present invention.
Fig. 3 is the flow chart of " S3 normalized slope absolute value standard deviation " step among the main process figure of the present invention.
The specific embodiment:
The invention will be further described below by specific embodiment.
Present embodiment is that the present invention is at personal computer (PC) and matrix experiment chamber (MatrixLaboratory, Matlab) a kind of possible realization on the platform, and on the test data set that constitutes by three standard databases of the arrhythmia data base of Massachusetts Polytechnics (MITDB), the ventricular arrhythmia data base of Ke Laideng university (CUDB), the malignant ventricular arrhythmia data base of Massachusetts Polytechnics (VFDB), test and compare.The present embodiment concrete steps are as follows:
1. electrocardiosignal is carried out pretreatment:
A) moving average filter on one 5 rank of use, high-frequency noises such as filtering spread noise and myoelectricity noise;
B) use the high pass filter of a cut-off frequency, suppress baseline drift as 1Hz;
C) use the Butterworth low pass filter of a cut-off frequency, further the irrelevant radio-frequency component of filtering as 30Hz.
2. electrocardiosignal is carried out the identification of the asystole rhythm of the heart:
If the amplitude of electrocardiosignal less than 80uV, is then thought the asystole rhythm of the heart, be judged to NShR;
Not the asystole rhythm of the heart if the amplitude of electrocardiosignal more than or equal to 80uV, is then thought, continue the step of back.
3. normalized slope absolute value standard deviation:
A) one section electrocardiogram (ECG) data is divided into segment by identical interval, each segment is called a grizzly bar (bar), and interval is called grill width (barwidth), and barwidth is taken as 16ms (when sample rate is 250Hz, corresponding to 4 sampled points);
B) calculate the absolute value (slope) of the difference of last sampling point in each grizzly bar and first sampling point, i.e. slope
i=abs (signal
i(barwidth)-signal
i(i)), slope wherein
iThe slope absolute value of representing i grizzly bar, signal
iRepresent the sampling point sequence in i the grizzly bar;
C) calculate the standard deviation (slope_std) of all slope absolute values;
D) to the slope_std standardization, promptly slope_std/mean (slope) obtains standard slope absolute value standard deviation (slope_stdnor).
4. differentiate NShR and ShR according to standard slope absolute value standard deviation:
Discrimination standard is:
If standard slope absolute value standard deviation 〉=threshold value T, then be judged to NShR;
If standard slope absolute value standard deviation＜threshold value T then is judged to ShR.
The software and hardware configuration that present embodiment uses is as follows:
-hardware: Dell is to 4 computers, dominant frequency 226GHz, 512,000,000 internal memories (Dell OPTIPLEXGX270, Pentium (R) 4 (2.26GHz) and 512 MB DDR SDRAM)
-software: MATLAB R13, " signal processing workbox " version 6.0 (＂ Signal ProcessingToolbox ＂ version 6.0)
Under following test condition, to present embodiment and prior art Hilbert (HILB) algorithm
[1] [2]Test and compare:
Test data set is all data of MITDB, CUDB, three standard databases of VFDB, is a segment (sample data) with 8s, and adjacent two segment zero-times differ 1s.
The goldstandard (Golden Standard) of rhythm of the heart classification:
A) the reference note that carries according to the data base (reference annotation) carries out rhythm of the heart classification to the data segment.
B) ShR: the rhythm of the heart (rhythm) class annotation information is labeled as the electrocardiogram (ECG) data of VF, VT,
NShR: other all rhythms of the heart;
C) containing the segment of mixing the rhythm of the heart does not use.
Test result such as following table:
Wherein, AUC is meant and receives operating characteristic curve (ROC) area down
[3] [4], be concentrated expression sensitivity and specific index.
By in the table as seen, the AUC of present embodiment (0.980) is greater than the AUC (0.965) of HILB algorithm, and remarkable on this difference statistical significance
。The classification performance that present embodiment is described is better than the HILB algorithm.And also be less than the HILB algorithm computation time of present embodiment.
If threshold value T is taken as 0.98, but in the present embodiment based on the sensitivity of the Electrical Cardioversion rhythm recognition algorithm of standard slope absolute value standard deviation be 92.0%, specificity is 95%, reaches the sensitivity 90% that AHA advises, the performance requirement of specificity 95%.
*List of references of the present invention
[1]DI?Robert?Tratnig.Reliability?of?New?Fibrillation?DetectionAlgorithms?for?Automated?External?Defibrillators[D].Dornbirn，Austria：Technische?Universit"at?Graz，2005.
[2]A.Amann，R.Tratnig，K.Unterkofler.A?new?ventricular?fibrillationdetection?algorithm?for?automated?external?defibrillators[J].Computers?inCardiology，2005：559-562.
[3] JP Marques work, Wu Yifei translates. pattern recognition---principle, method and application [M]. and publishing house of Tsing-Hua University, 2002:113-115.
[4] space passes China, Xu Yongyong. and non parametric method is estimated ROC area under curve [J]. Chinese health statistics, 1999,16 (4): 241-244.
[5]Richard?E.Kerber，Chair?MD，Lance?B.Becker，et?al.AutomaticExternal?Defibrillators?for?Public?Access?Defibrillation：Recommendationsfor?Specifying?and?Reporting?Arrhythmia?Analysis?Algorithm?Performance，Incorporating?New?Waveforms，and?Enhancing?Safety[J].Circulation，1997，95(6)：1677-1682.
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