CN116173412A - Defibrillation equipment control method and device based on rhythm recognition and defibrillation equipment - Google Patents
Defibrillation equipment control method and device based on rhythm recognition and defibrillation equipment Download PDFInfo
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- A61N1/00—Electrotherapy; Circuits therefor
- A61N1/18—Applying electric currents by contact electrodes
- A61N1/32—Applying electric currents by contact electrodes alternating or intermittent currents
- A61N1/38—Applying electric currents by contact electrodes alternating or intermittent currents for producing shock effects
- A61N1/39—Heart defibrillators
- A61N1/3904—External heart defibrillators [EHD]
- A61N1/39044—External heart defibrillators [EHD] in combination with cardiopulmonary resuscitation [CPR] therapy
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Abstract
The invention discloses a defibrillation equipment control method and device based on rhythm recognition, and the defibrillation equipment, wherein the method comprises the following steps: acquiring a signal to be analyzed according to a target sampling rate obtained after the initial sampling rate downsampling; determining an amplitude mean value and an amplitude probability according to a smooth signal obtained by denoising and smoothing the signal to be analyzed; and performing CPR operation when the amplitude mean value and the amplitude probability meet the beat stopping rhythm condition, otherwise, performing defibrillation operation when the waveform complexity parameter and the waveform amplitude parameter meet the first defibrillation condition or the heart rate parameter and the QRS wave width meet the second defibrillation condition after converting the smooth signal into the standard signal. According to the technical scheme of the embodiment, the emergency situation can be rapidly judged based on the signals with shorter duration, rapid response of stopping the pulse is realized based on the stopping pulse rhythm, the defibrillatable scene to be shocked urgently is identified based on the first defibrillation condition and the second defibrillation condition, and the response efficiency of the defibrillation equipment is improved, so that the treatment efficiency of the defibrillation equipment is improved.
Description
Technical Field
The application relates to the technical field of medical equipment, in particular to a defibrillation equipment control method and device based on rhythm recognition and defibrillation equipment.
Background
Ventricular Fibrillation (VF) is considered to be a common type of arrhythmia that causes Sudden Cardiac Death (SCD), and when ventricular fibrillation occurs, the heart is in chaotic condition with contractions of the heart muscle, and loses pumping function, resulting in sudden cardiac arrest that in turn threatens the life of the patient. Defibrillation devices are important devices for dealing with ventricular fibrillation, and common defibrillation devices perform a rhythm analysis after being precharged by starting up and then perform electric shock or cardiopulmonary resuscitation (Card io Pu lmonary Resuscitat ion, CPR) according to the result of the rhythm analysis. However, in order to distinguish between a defibrillatable rhythm and a non-defibrillatable rhythm, defibrillation devices typically require collecting two signals at analysis intervals for a rhythm analysis that is time consuming and does not provide a fast response to an emergency such as a stop-beat or coarse ventricular fibrillation.
Disclosure of Invention
The embodiment of the application provides a defibrillation equipment control method and device based on rhythm recognition, and defibrillation equipment, which can at least ensure that the scheme of the application can complete the analysis of the rhythm through shorter analysis time and improve the response efficiency of the defibrillation equipment.
In a first aspect, an embodiment of the present application provides a defibrillation device control method based on rhythm recognition, applied to a defibrillation device, where the method includes:
determining a target sampling rate according to a preset initial sampling rate and a downsampling coefficient, and collecting a signal to be analyzed according to the target sampling rate;
denoising and smoothing the signal to be analyzed to obtain a smooth signal, and searching the smooth signal to determine an amplitude average value and an amplitude probability;
when the amplitude mean value and the amplitude probability meet a preset beat stopping rhythm condition, controlling the defibrillation equipment to execute CPR operation;
when the amplitude mean value and the amplitude probability do not meet the beat rhythm condition, converting the smooth signal into a dimensionless standard signal, and determining a waveform complexity parameter, a waveform amplitude parameter, a heart rate parameter and a QRS wave width of the standard signal;
and when the waveform complexity parameter and the waveform amplitude parameter meet a preset first defibrillation condition, or the heart rate parameter and the QRS wave width meet a second defibrillation condition, controlling the defibrillation equipment to execute defibrillation operation.
According to some embodiments of the present invention, the denoising and smoothing the signal to be analyzed to obtain a smoothed signal includes:
Filtering the signal to be analyzed according to a preset Butterworth band-stop filter to obtain a filtered signal;
denoising the filtered signal to obtain a denoised signal, and smoothing the denoised signal according to the signal amplitude of the denoised signal, a preset smoothing window length and a preset window sliding step length to obtain a smoothed signal;
wherein the smoothing process is obtained by the following formula:
wherein AS i To smooth the signal amplitude of the signal, N is the signal length of the denoising signal, N is the window sliding step length, A i WS is the smooth window length, which is the signal amplitude of the denoising signal and satisfies N>WS, i is a natural number.
According to some embodiments of the invention, the searching the smoothed signal to determine the amplitude mean and the amplitude probability includes:
performing first-order differential calculation on each sampling point of the smooth signal to obtain a first-order differential output matrix;
determining the sampling point corresponding to a value smaller than minus one in the first-order differential output matrix as an alternative peak value point, and determining the sampling point corresponding to a value larger than one in the first-order differential output matrix as an alternative valley value point;
Determining a plurality of effective peak points from a plurality of alternative peak points, and obtaining a peak amplitude matrix according to the plurality of effective peak points, wherein the effective peak points are adjacent alternative peak points with the largest value among the plurality of alternative peak points with the interval larger than a preset peak interval threshold;
determining a plurality of effective valley points from a plurality of candidate valley points, and obtaining a valley amplitude matrix according to the plurality of effective valley points, wherein the effective valley points are adjacent candidate valley points with the smallest value in the plurality of candidate valley points with intervals larger than a preset valley interval threshold;
determining a waveform amplitude matrix according to the difference value of the peak amplitude matrix and the trough amplitude matrix, and determining the average value of the waveform amplitude matrix as the amplitude average value;
and determining the ratio of the number of elements with the value smaller than a first amplitude threshold value in the waveform amplitude matrix to the total number of elements of the waveform amplitude matrix as the amplitude probability.
According to some embodiments of the invention, the converting the smoothed signal into a dimensionless standard signal includes:
dividing the smoothed signal into a plurality of data windows according to the window sliding step length;
Determining a window amplitude mean value of the data window, and normalizing the window amplitude mean value to obtain the standard signal;
the window amplitude mean value is obtained through the following formula:
the window amplitude mean value is normalized by the following formula:
According to some embodiments of the invention, the waveform amplitude parameter includes a peak amplitude variance and a standard signal waveform amplitude, and the first defibrillation condition includes:
the waveform complexity parameter is larger than a preset waveform complexity low threshold value and smaller than a preset waveform complexity high threshold value;
the peak amplitude variance is smaller than or equal to a preset variance threshold;
the standard signal waveform amplitude is greater than a preset second amplitude threshold.
According to some embodiments of the invention, the heart rate parameter and the QSR wave width are determined by:
acquiring two adjacent effective valley points and the effective peak point, and taking the effective valley point as an R wave when the effective valley point is larger than the product of a first screening coefficient and the effective peak point and smaller than the product of a second screening coefficient and the effective peak point, otherwise, taking the effective peak point as the R wave;
Determining the R wave quantity of the R waves, the R wave amplitude of each R wave and the R wave position information, and determining the heart rate parameter according to the R wave amplitude, the R wave position information and the R wave number;
establishing a QRS wave start-stop window based on the R wave position information as a center, determining a QRS wave starting point forwards according to a preset space threshold, determining a QRS wave end point backwards, and determining the QRS wave width according to the QRS wave starting point and the QRS wave end point;
wherein the heart rate parameter is calculated by the following formula:
wherein the QRS complex width is obtained by the following formula:
intervalT j ＝Qend j -Qstart j ,j＝(1,2,…,count)，
interval j ＝sort(intervalT j )，
wherein, interval T j For the distance between the QRS wave starting point and the QRS wave ending point, sort () is arranged according to the order of the numerical value, interval j For the data set obtained by the sort () arrangement, interval is the QRS wave width.
According to some embodiments of the invention, the second defibrillation condition comprises:
the heart rate parameter is greater than a preset first heart rate threshold, and the QRS wave width is greater than a preset QRS wave width threshold;
The heart rate parameter is greater than a preset second heart rate threshold, wherein the second heart rate threshold is greater than the first heart rate threshold.
In a second aspect, embodiments of the present application provide a defibrillation device control apparatus based on rhythm recognition, comprising at least one control processor and a memory for communicatively coupling with the at least one control processor; the memory stores instructions executable by the at least one control processor to enable the at least one control processor to perform the rhythm-recognition-based defibrillation device control method of the first aspect.
In a third aspect, embodiments of the present application provide a defibrillation device, including the defibrillation device control apparatus based on rhythm recognition according to the second aspect.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium storing computer-executable instructions for performing the method for controlling a defibrillation device based on rhythm recognition according to the first aspect.
The application has at least the following beneficial effects: determining a target sampling rate according to a preset initial sampling rate and a downsampling coefficient, and collecting a signal to be analyzed according to the target sampling rate; denoising and smoothing the signal to be analyzed to obtain a smooth signal, and searching the smooth signal to determine an amplitude average value and an amplitude probability; when the amplitude mean value and the amplitude probability meet a preset beat stopping rhythm condition, controlling the defibrillation equipment to execute CPR operation; when the amplitude mean value and the amplitude probability do not meet the beat rhythm condition, converting the smooth signal into a dimensionless standard signal, and determining a waveform complexity parameter, a waveform amplitude parameter, a heart rate parameter and a QRS wave width of the standard signal; and when the waveform complexity parameter and the waveform amplitude parameter meet a preset first defibrillation condition, or the heart rate parameter and the QRS wave width meet a second defibrillation condition, controlling the defibrillation equipment to execute defibrillation operation. According to the technical scheme of the embodiment, the emergency situation can be rapidly judged based on the signals with shorter duration, rapid response of stopping the pulse is realized based on the stopping pulse rhythm, the defibrillatable scene to be shocked urgently is identified based on the first defibrillation condition and the second defibrillation condition, and the response efficiency of the defibrillation equipment is improved, so that the treatment efficiency of the defibrillation equipment is improved.
Drawings
Fig. 1 is a flowchart of a method for controlling a defibrillation device based on rhythm recognition according to an embodiment of the present application;
fig. 2 is a flowchart illustrating signal preprocessing according to another embodiment of the present application;
FIG. 3 is a flowchart of searching for a smooth signal according to another embodiment of the present application;
FIG. 4 is a general flow chart of performing a beat detection according to another embodiment of the present application;
FIG. 5 is a flow chart of signal normalization according to another embodiment of the present application;
fig. 6 is a flowchart for determining a heart rate parameter and QRS wave width according to another embodiment of the present application;
fig. 7 is a graph comparing QRS wave recognition results according to another embodiment of the present application with effects of the prior art;
fig. 8 is a general control flow diagram of a defibrillation device according to another embodiment of the present application;
fig. 9 is a block diagram of a defibrillation device control apparatus based on rhythm recognition according to another embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
In some embodiments, although functional block division is performed in a system diagram, logical order is shown in a flowchart, in some cases, steps shown or described may be performed in a different order than block division in a system, or in a flowchart. The terms first, second and the like in the description and in the claims and in the above-described figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order.
In order to at least solve the above problems, the present application discloses a defibrillation equipment control method, a device and a defibrillation equipment based on rhythm recognition, wherein, by the defibrillation equipment control method based on rhythm recognition, a target sampling rate is determined according to a preset initial sampling rate and a downsampling coefficient, and a signal to be analyzed is acquired according to the target sampling rate; denoising and smoothing the signal to be analyzed to obtain a smooth signal, and searching the smooth signal to determine an amplitude average value and an amplitude probability; when the amplitude mean value and the amplitude probability meet a preset beat stopping rhythm condition, controlling the defibrillation equipment to execute CPR operation; when the amplitude mean value and the amplitude probability do not meet the beat rhythm condition, converting the smooth signal into a dimensionless standard signal, and determining a waveform complexity parameter, a waveform amplitude parameter, a heart rate parameter and a QRS wave width of the standard signal; and when the waveform complexity parameter and the waveform amplitude parameter meet a preset first defibrillation condition, or the heart rate parameter and the QRS wave width meet a second defibrillation condition, controlling the defibrillation equipment to execute defibrillation operation. According to the technical scheme of the embodiment, the emergency situation can be rapidly judged based on the signals with shorter duration, rapid response of stopping the pulse is realized based on the stopping pulse rhythm, the defibrillatable scene to be shocked urgently is identified based on the first defibrillation condition and the second defibrillation condition, and the response efficiency of the defibrillation equipment is improved, so that the treatment efficiency of the defibrillation equipment is improved.
Embodiments of the present application are further described below with reference to the accompanying drawings.
Referring to fig. 1, fig. 1 is a flowchart of a method for controlling a defibrillation device based on rhythm recognition according to an embodiment of the present application, including, but not limited to, the following steps:
step S110, determining a target sampling rate according to a preset initial sampling rate and a downsampling coefficient, and collecting a signal to be analyzed according to the target sampling rate;
step S120, denoising and smoothing the signal to be analyzed to obtain a smooth signal, and searching the smooth signal to determine an amplitude average value and an amplitude probability;
step S130, when the amplitude mean value and the amplitude probability meet the preset beat stopping rhythm condition, controlling the defibrillation equipment to execute CPR operation;
step S140, when the amplitude mean value and the amplitude probability do not meet the beat rhythm condition, converting the smooth signal into a dimensionless standard signal, and determining the waveform complexity parameter, the waveform amplitude parameter, the heart rate parameter and the QRS wave width of the standard signal;
step S150, when the waveform complexity parameter and the waveform amplitude parameter meet the preset first defibrillation condition, or the heart rate parameter and the QRS wave width meet the second defibrillation condition, the defibrillation equipment is controlled to execute defibrillation operation.
It should be noted that, the initial sampling rate is the preset sampling rate of the defibrillation device, and the target sampling rate is obtained by downsampling the front-end signal to obtain the signal to be analyzed, so that the rhythm recognition can be performed by using the signal to be analyzed with a shorter length, thereby improving the response efficiency of the defibrillation device. For example, the initial sampling rate is S1000 Hz, and in this embodiment, the sampling rate is reduced to R250 Hz, and the original signal at the front end is decimated from S/R points, so as to reduce the length of the signal to be analyzed.
It should be noted that, because the beat rhythm is lower in the data amplitude level, it is easy to be disturbed, and after the signal to be analyzed is obtained, the embodiment can firstly perform denoising and smoothing processing on the signal to be analyzed, so as to reduce the interference of noise on beat rhythm recognition.
In this embodiment, in order to identify the beat rhythm, the wave searching is performed on the smooth signal, so that the peak amplitude matrix formed by the peak points of the smooth signal and the valley peak amplitude matrix formed by the valley peak points of the smooth signal can be determined, the amplitude mean value and the amplitude probability of the smooth signal can be calculated through the peak amplitude matrix and the valley peak amplitude matrix, and the simple data comparison is performed through the amplitude mean value and the amplitude probability and the set beat rhythm condition, so that whether the beat occurs can be determined, the CPR operation is performed after the beat is judged, the beat scene is responded quickly, and the treatment efficiency is improved. It will be appreciated that the pacing rhythm condition may be set according to actual requirements, for example, when the average amplitude value is greater than a certain value and the probability of amplitude is greater than a certain probability value, and those skilled in the art may set a specific comparison value according to actual requirements, which is not limited herein.
It should be noted that, when it is determined that no asystole occurs according to the smoothed signal, it may be further determined whether a defibrillation scene such as coarse ventricular fibrillation or rapid pulse-free ventricular rate occurs, and in order to reduce the influence of individual differences on the calculation of relevant parameters, the embodiment performs dimensionless normalization processing on the smoothed signal to obtain a standard signal due to the large differences in the amplitudes of the cardiac electrical signals of different individuals.
It should be noted that, according to the above description, the coarse ventricular fibrillation or the rapid heart rate pulse-free ventricular rate are two different scenarios that need to be shocked, in order to improve the identification efficiency of the defibrillation device, the embodiment sets a first defibrillation condition for the coarse ventricular fibrillation and a second defibrillation condition for the rapid heart rate pulse-free ventricular rate, because the embodiment reduces the signal length through downsampling, the defibrillation signal is generally in an irregular characteristic, and is embodied as a quasi-random signal on the waveform, and other non-defibrillation rhythms may have abnormal discharge of the heart, but basically have a certain periodicity, so in order to analyze the defibrillation signal and the non-defibrillation signal, the embodiment introduces waveform complexity to make an auxiliary judgment, and can rapidly distinguish the defibrillation rhythm from the non-defibrillation rhythm. The waveform complexity can be realized by adopting a common LZ algorithm, and the method for calculating the waveform complexity is not improved in the embodiment, and is not repeated here.
It is noted that the defibrillation signal and the defibrillation signal can be distinguished by the waveform complexity parameter, on the basis of which the ventricular fibrillation signal and the defibrillation ventricular rate can be distinguished by combining the waveform amplitude parameter of the standard signal, the waveform amplitude parameter can adopt waveform amplitude variance, and the waveform complexity parameter and the waveform amplitude parameter are compared with the first defibrillation condition, and when the waveform complexity parameter and the waveform amplitude parameter are satisfied, the occurrence of coarse ventricular fibrillation is determined and the defibrillation process is started. It can be understood that the first defibrillation condition may be a threshold condition corresponding to the waveform complexity parameter and the waveform amplitude parameter, and whether the condition is satisfied is rapidly determined by comparing the values, so as to improve the response efficiency of the defibrillation device.
It should be noted that, in this embodiment, the rhythm recognition is performed on the ventricular rate with the faster pulse-free rate under the second defibrillation condition, so as to control the defibrillation device to perform defibrillation. In order to accurately identify the defibrillatable ventricular rate, the present embodiment introduces a heart rate parameter and QRS wave width and a second defibrillation condition to make a determination, for example, sets a threshold value related to the heart rate parameter and QRS wave width as the second defibrillation condition, determines that a faster pulse-free ventricular rate of the heart rate occurs and initiates a defibrillation procedure when satisfied.
According to the embodiment, under the condition of downsampling the signal, the identification of the defibrillation scene can be realized on the basis of the shorter signal length through the waveform data of the standard signal and the preset first defibrillation condition and second defibrillation condition, the condition that a plurality of acquisition intervals are waited for rhythm identification in the prior art is not needed, corresponding judgment bases are set for scenes with higher emergency degree, the scenes with higher emergency degree such as asystole, coarse ventricular fibrillation or rapid pulse-free ventricular speed are rapidly determined through the rhythm identification, corresponding processing flows are started, the response efficiency of defibrillation equipment can be improved, and the treatment efficiency is improved.
In addition, referring to fig. 2, step S120 of the embodiment shown in fig. 1 further includes, but is not limited to, the following steps:
step S210, filtering a signal to be analyzed according to a preset Butterworth band-stop filter to obtain a filtered signal;
step S220, denoising the filtered signal to obtain a denoised signal, and smoothing the denoised signal according to the signal amplitude of the denoised signal, a preset smoothing window length and a preset window sliding step length to obtain a smoothed signal;
wherein the smoothing process is obtained by the following formula:
Wherein AS i To smooth the signal amplitude, N is the signal length of the denoising signal, N is the window sliding step length, A i For the signal amplitude of the denoising signal, WS is the smooth window length and satisfies N>WS, i is a natural number.
It should be noted that, in this embodiment, the sampling frequency after downsampling is 250Hz, and in order to eliminate the power frequency interference of 50Hz and 60Hz, a butterworth band-stop filter may be used to filter the interference. Because the main frequency component of the ventricular fibrillation is 3-5Hz, the 4-order 2-25Hz Butterworth filter is adopted to carry out filtering operation on the signals in the embodiment, and interference can be effectively filtered.
It should be noted that, the filtering signal is further denoised and smoothed, so that high-frequency noise and low-frequency noise can be removed, and the interference of noise on subsequent recognition can be reduced. The smoothing processing performed in this embodiment may be obtained by the above formula, and the description thereof will not be repeated here.
In addition, referring to fig. 3, step S120 of the embodiment shown in fig. 1 further includes, but is not limited to, the following steps:
step S310, performing first-order differential calculation on each sampling point of the smooth signal to obtain a first-order differential output matrix;
step S320, determining a sampling point corresponding to a value smaller than minus one in the first-order differential output matrix as an alternative peak value point, and determining a sampling point corresponding to a value larger than one in the first-order differential output matrix as an alternative valley value point;
Step S330, determining a plurality of effective peak points from a plurality of alternative peak points, and obtaining a peak amplitude matrix according to the plurality of effective peak points, wherein the effective peak points are adjacent alternative peak points with the largest value among the plurality of alternative peak points with the interval larger than a preset peak interval threshold;
step S340, determining a plurality of effective valley points from a plurality of candidate valley points, and obtaining a valley amplitude matrix according to the plurality of effective valley points, wherein the effective valley points are adjacent candidate valley points with the smallest value in the plurality of candidate valley points with intervals larger than a preset valley interval threshold;
step S350, determining a waveform amplitude matrix according to the difference value of the peak amplitude matrix and the trough amplitude matrix, and determining the average value of the waveform amplitude matrix as an amplitude average value;
in step S360, a ratio of the number of elements in the waveform amplitude matrix having a value smaller than the first amplitude threshold to the total number of elements in the waveform amplitude matrix is determined as the amplitude probability.
It should be noted that, after the first-order differential calculation is performed on the sampling points, the data may be further symbolized to obtain a first-order differential output matrix, where the first-order differential output matrix uses D as an example, the sampling points satisfying D (n) < -1 are determined as alternative peak points, the sampling points satisfying D (n) >1 are determined as alternative valley points, and the sampling points satisfying-1.ltoreq.d (n). Ltoreq.1 are determined as non-alternative points to be discarded; after a plurality of alternative peak points and a plurality of alternative valley points are obtained, determining the intervals of a plurality of adjacent alternative peak points, when the intervals among the continuous plurality of alternative peak points are all larger than a peak interval threshold value, selecting the point with the maximum value as an effective peak point, otherwise, directly determining the effective peak point when no adjacent point with the interval larger than the peak interval threshold value exists for a certain alternative peak point; the determination method of the effective valley point is the same, except that the minimum value is selected, and the detailed description is not repeated here.
It should be noted that, the calculation of the smoothed signal waveform amplitude can be obtained by the following formula: waveAmp i ＝(peak i -Valley i ) Wherein, wave Amp i To smooth the signal waveform amplitude, peak i As the i-th effective peak point, valley i For the i-th effective valley point, the number of the effective peak points and the number of the effective valley points can be unified, that is, the number of the effective peak points and the number of the effective valley points are the same, and taking the number as count as an example, the calculation of the amplitude mean value can be obtained through the following expression:
wherein A is ave Is the average value of the amplitude.
After obtaining the waveform amplitude matrix, determining the ratio of the number wCount smaller than the first amplitude threshold to the total number count as the amplitude probability, i.e.
Wherein P is amp Is the amplitude probability.
By way of example, fig. 4 is a flowchart for controlling the defibrillation device based on the beat rhythm recognition in this embodiment, it can be seen from fig. 4 that the acquired signal to be processed has a larger amplitude range, the signal amplitude obtained after filtering and denoising is more concentrated, the noise of the waveform after smoothing is less, the effective peak point and the effective valley point in the waveform are determined after the filtering, the calculation of the amplitude mean value and the amplitude probability is performed, and the comparison is performed according to the amplitude mean value and the amplitude probability and the beat rhythm condition, so that the recognition of the beat rhythm is realized, and the defibrillation device is controlled to enter the CPR flow after the beat is detected, so that the response efficiency is improved.
In addition, referring to fig. 5, in an embodiment, step S140 of the embodiment shown in fig. 1 further includes, but is not limited to, the following steps:
step S510, dividing the smooth signal into a plurality of data windows according to the window sliding step length;
step S520, determining a window amplitude mean value of the data window, and normalizing the window amplitude mean value to obtain a standard signal;
the window amplitude mean value is obtained by the following formula:
the window amplitude mean value is normalized by the following formula:
When the signal is normalized, taking the initial sampling rate as S and the length of a data analysis window as WL seconds as an example, the data storage mode in the analysis window adopts a queue-like mode to carry out sliding storage and analysis to obtain a plurality of data windows, wherein the window sliding step length is n seconds, the analysis time is t, and the window amplitude average value Amp of the waveform in the data windows is obtained avg The method can be obtained by the formula, and after the window amplitude mean value is obtained, the data in the window can be normalized by the formula 
And obtaining, thereby realizing the standardization of the signals.
Additionally, in an embodiment, the waveform amplitude parameter comprises a peak amplitude variance and a standard signal waveform amplitude, and the first defibrillation condition comprises:
the waveform complexity parameter is larger than a preset waveform complexity low threshold value and smaller than a preset waveform complexity high threshold value;
the peak amplitude variance is smaller than or equal to a preset variance threshold;
the standard signal waveform amplitude is greater than a preset second amplitude threshold.
Note that, the standard signal waveform amplitude can be calculated by the following formula,
wherein n is<WL, n is an integer, and the meaning of the remaining parameters may refer to the description of the above embodiments, and the description is not repeated here.
It should be noted that, the peak amplitude variance can be calculated by the following formula:
wherein ASD is peak amplitude variance, and account is the number of effective peak points.
Referring to fig. 8, the first defibrillation condition of the present embodiment will be described by way of a specific example, in which a waveform complexity is lzc, a waveform complexity low threshold is CL, a waveform complexity high threshold is CH, a standard signal waveform amplitude is AMP, a second amplitude threshold is TH1, a peak amplitude variance is ASD, and a variance threshold is SDJ.
Illustratively, when lzc < CL, determining that the rhythm recognition result is sinus rhythm or other non-defibrillatable rhythm, re-performing signal acquisition and judgment; when lzc is more than or equal to CL and lzc is more than or equal to CH, determining that the rhythm recognition result is noise, and carrying out signal acquisition and judgment again; when lzc is more than or equal to CL and lzc is less than or equal to CH and SD is less than or equal to SDJ, if AMP > TH1, determining that the rhythm recognition result is coarse ventricular fibrillation and executing a defibrillation process, and if AMP is less than or equal to TH1, determining that the rhythm recognition result is fine ventricular fibrillation, and carrying out signal acquisition and judgment again.
Additionally, in one embodiment, referring to FIG. 6, the heart rate parameter and QSR wave width are determined by:
step S610, two adjacent effective valley points and an effective peak point are obtained, wherein the effective valley point is larger than the product of the first screening coefficient and the effective peak point and smaller than the product of the second screening coefficient and the effective peak point, the effective valley point is taken as an R wave, and otherwise, the effective peak point is taken as the R wave;
step S620, determining the R wave quantity of R waves, the R wave amplitude of each R wave and the R wave position information, and determining heart rate parameters according to the R wave amplitude, the R wave position information and the R wave number;
step S630, establishing a QRS wave start-stop window based on the R wave position information as a center, determining a QRS wave start point forwards according to a preset space threshold, determining a QRS wave end point backwards, and determining a QRS wave width according to the QRS wave start point and the QRS wave end point;
Wherein the heart rate parameter is calculated by the following formula:
wherein the QRS complex width is obtained by the following formula:
intervalT j ＝Qend j -Qstart j ,j＝(1,2,…,count)，
interval j ＝sort(intervalT j )，
wherein, interval T j For the distance between the start point and the end point of the QRS wave, the sort () is arranged according to the order of the numerical value, interval j For the data set obtained by the sort () permutation, interval is QRS wave width.
It should be noted that, the defibrillation chamber speed may be generally determined by a heart rate parameter and a threshold value, based on which, in order to accurately identify the defibrillation chamber speed, the QRS wave width and the heart rate parameter need to be accurately calculated, the calculation formulas of the heart rate parameter and the QRS wave width may refer to the above description, and are not repeated herein, in order to improve the accuracy of calculation, the QRS wave needs to be detected, and in the related art, pan-Tompkins method is mainly adopted, where although the method has higher identification accuracy for waveforms with relatively obvious QRS waves such As normal sinus rhythm, the algorithm identification accuracy is relatively low for the defibrillation chamber speed signal with distorted QRS waves, the QRS wave identification method of the present embodiment is exemplarily described below, taking the analysis window length As WL As an example, maxAvg, minAvg two variables are the average value of the amplitude within 1s, as and De respectively represent the number of points of continuous rising and falling of the waveforms, the first screening coefficient is C1, and the second screening coefficient is C2:
When De is greater than a preset descending threshold value and the peak point is searched, searching for the valley point is started, when the valley value is smaller than minAvg, determining that the valley point is a valid valley point, and otherwise, discarding the invalid valley point;
when As is larger than a preset rising threshold value and the valley point is searched, searching for a peak point is started, and when the peak point is larger than maxAvg, determining that the peak point is a valid peak point, otherwise, discarding the invalid peak point;
and when C1×peak < valley < C2×peak is satisfied, determining that the effective valley point is the R wave, otherwise, determining that the effective peak point is the R wave, wherein peak is the effective peak point and valley is the effective valley point.
Referring to fig. 7, the upper graph of fig. 7 shows QRS waves identified by Pan-Tompkins method, and the lower graph shows QRS waves identified by the above method, so that it can be seen from the graph that the lower graph can identify more QRS waves, the identification accuracy is higher, and the accuracy of rhythm analysis can be improved.
After each R wave is identified, R wave information is stored in r_info, the variable information contains R wave amplitude value r_amp and R wave position information r_pos, respectively, on the basis of which a search QRS wave start-stop window is established with R wave position as a midpoint, a search space threshold is s_wl, and a search range is [ R ] Pos -S WL ,R Pos +S WL ]Front (front) Searching for the QRS wave starting point Qstart, searching for the QRS wave ending point Qend in the backward direction, and completing calculation through the calculation formula of the QRS wave width.
Additionally, in an embodiment, the second defibrillation condition comprises:
the heart rate parameter is greater than a preset first heart rate threshold, and the QRS complex width is greater than a preset QRS complex width threshold;
the heart rate parameter is greater than a preset second heart rate threshold, wherein the second heart rate threshold is greater than the first heart rate threshold.
With reference to fig. 8, the following illustrates a second defibrillation condition of the present embodiment by a specific example, in which the first heart rate threshold is exemplified by HRJ, the QRS wave width threshold is exemplified by qrsJ, and the second heart rate threshold is exemplified by HRJ 1:
based on the description of the above embodiments, when SD > SDJ is satisfied, it can be determined that ventricular fibrillation has not occurred, and a determination is made as to the defibrillatable ventricular rate. On the basis, when the HR is larger than or equal to HRJ and the QRS wave width is larger than or equal to qrsJ and the HR is larger than or equal to HRJ1, the rhythm recognition result can be determined to be the rapid pulse-free ventricular rate of the heart rate, the defibrillation process is executed, otherwise, the rhythm recognition result is determined to be other defibrillation ventricular rates, the conventional recognition process is entered, and the signal collection is repeated.
As shown in fig. 9, fig. 9 is a block diagram of a defibrillation device control apparatus based on rhythm recognition according to an embodiment of the present invention. The invention also provides a defibrillation equipment control device based on rhythm recognition, which comprises:
The processor 901 may be implemented by a general purpose central processing unit (Central Processing Unit, CPU), a microprocessor, an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), or one or more integrated circuits, etc. for executing related programs to implement the technical solutions provided by the embodiments of the present application;
the Memory 902 may be implemented in the form of a Read Only Memory (ROM), a static storage device, a dynamic storage device, or a random access Memory (Random Access Memory, RAM). The memory 902 may store an operating system and other application programs, and when the technical solutions provided in the embodiments of the present disclosure are implemented by software or firmware, relevant program codes are stored in the memory 902, and the processor 901 is used to invoke the defibrillation device control method based on rhythm recognition to execute the embodiments of the present disclosure;
an input/output interface 903 for inputting and outputting information;
the communication interface 904 is configured to implement communication interaction between the device and other devices, and may implement communication in a wired manner (e.g. USB, network cable, etc.), or may implement communication in a wireless manner (e.g. mobile network, WIFI, bluetooth, etc.);
A bus 905 that transfers information between the various components of the device (e.g., the processor 901, the memory 902, the input/output interface 903, and the communication interface 904);
wherein the processor 901, the memory 902, the input/output interface 903 and the communication interface 904 are communicatively coupled to each other within the device via a bus 905.
The embodiment of the application also provides a defibrillation device, which comprises the defibrillation device control device based on rhythm recognition.
The embodiment of the application also provides a storage medium, which is a computer readable storage medium, and the storage medium stores a computer program, and the computer program realizes the defibrillation equipment control method based on rhythm recognition when being executed by a processor.
The memory, as a non-transitory computer readable storage medium, may be used to store non-transitory software programs as well as non-transitory computer executable programs. In addition, the memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one magnetic disk storage device, flash memory device, or other non-transitory solid state storage device. In some embodiments, the memory optionally includes memory remotely located relative to the processor, the remote memory being connectable to the processor through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof. The apparatus embodiments described above are merely illustrative, in which the elements illustrated as separate components may or may not be physically separate, implemented to reside in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
Those of ordinary skill in the art will appreciate that all or some of the steps, systems, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as known to those skilled in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Furthermore, as is well known to those of ordinary skill in the art, communication media typically include computer readable instructions, data structures, program modules, or other data in a modulated data signal, such as a carrier wave or other transport mechanism, and may include any information delivery media.
While the preferred embodiment of the present invention has been described in detail, the present invention is not limited to the above embodiments, and those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit and scope of the present invention, and these equivalent modifications or substitutions are included in the scope of the present invention as defined in the appended claims.
The above described apparatus embodiments are merely illustrative, wherein the units illustrated as separate components may or may not be physically separate, i.e. may be located in one place, or may be distributed over a plurality of network nodes. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
Those of ordinary skill in the art will appreciate that all or some of the steps, systems, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer readable storage media (or non-transitory media) and communication media (or transitory media). The term computer-readable storage medium includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information, such as computer-readable instructions, data structures, program modules or other data, as known to those skilled in the art. Computer-readable storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Furthermore, as is well known to those of ordinary skill in the art, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media.
While the preferred embodiments of the present application have been described in detail, the present application is not limited to the above embodiments, and various equivalent modifications and substitutions can be made by those skilled in the art without departing from the spirit of the present application, and these equivalent modifications and substitutions are intended to be included in the scope of the present application as defined in the appended claims.
Claims (10)
1. A method of controlling a defibrillation device based on rhythm recognition, the method comprising:
determining a target sampling rate according to a preset initial sampling rate and a downsampling coefficient, and collecting a signal to be analyzed according to the target sampling rate;
denoising and smoothing the signal to be analyzed to obtain a smooth signal, and searching the smooth signal to determine an amplitude average value and an amplitude probability;
when the amplitude mean value and the amplitude probability meet a preset beat stopping rhythm condition, controlling the defibrillation equipment to execute CPR operation;
when the amplitude mean value and the amplitude probability do not meet the beat rhythm condition, converting the smooth signal into a dimensionless standard signal, and determining a waveform complexity parameter, a waveform amplitude parameter, a heart rate parameter and a QRS wave width of the standard signal;
And when the waveform complexity parameter and the waveform amplitude parameter meet a preset first defibrillation condition, or the heart rate parameter and the QRS wave width meet a second defibrillation condition, controlling the defibrillation equipment to execute defibrillation operation.
2. The method for controlling a defibrillation device based on rhythm recognition according to claim 1, wherein the denoising and smoothing the signal to be analyzed to obtain a smoothed signal comprises:
filtering the signal to be analyzed according to a preset Butterworth band-stop filter to obtain a filtered signal;
denoising the filtered signal to obtain a denoised signal, and smoothing the denoised signal according to the signal amplitude of the denoised signal, a preset smoothing window length and a preset window sliding step length to obtain a smoothed signal;
wherein the smoothing process is obtained by the following formula:
wherein AS i To smooth the signal amplitude of the signal, N is the signal length of the denoising signal, N is the window sliding step length, A i WS is the smooth window length, which is the signal amplitude of the denoising signal and satisfies N>WS, i is a natural number.
3. The method of claim 2, wherein the searching the smoothed signal for an amplitude mean and an amplitude probability comprises:
Performing first-order differential calculation on each sampling point of the smooth signal to obtain a first-order differential output matrix;
determining the sampling point corresponding to a value smaller than minus one in the first-order differential output matrix as an alternative peak value point, and determining the sampling point corresponding to a value larger than one in the first-order differential output matrix as an alternative valley value point;
determining a plurality of effective peak points from a plurality of alternative peak points, and obtaining a peak amplitude matrix according to the plurality of effective peak points, wherein the effective peak points are adjacent alternative peak points with the largest value among the plurality of alternative peak points with the interval larger than a preset peak interval threshold;
determining a plurality of effective valley points from a plurality of candidate valley points, and obtaining a valley amplitude matrix according to the plurality of effective valley points, wherein the effective valley points are adjacent candidate valley points with the smallest value in the plurality of candidate valley points with intervals larger than a preset valley interval threshold;
determining a waveform amplitude matrix according to the difference value of the peak amplitude matrix and the trough amplitude matrix, and determining the average value of the waveform amplitude matrix as the amplitude average value;
And determining the ratio of the number of elements with the value smaller than a first amplitude threshold value in the waveform amplitude matrix to the total number of elements of the waveform amplitude matrix as the amplitude probability.
4. The defibrillation device control method based on rhythm recognition according to claim 2, wherein the converting the smoothed signal into a dimensionless standard signal includes:
dividing the smoothed signal into a plurality of data windows according to the window sliding step length;
determining a window amplitude mean value of the data window, and normalizing the window amplitude mean value to obtain the standard signal;
the window amplitude mean value is obtained through the following formula:
the window amplitude mean value is normalized by the following formula:
5. The rhythm recognition-based defibrillation device control method of claim 4 wherein the waveform amplitude parameters include peak amplitude variance and standard signal waveform amplitude, the first defibrillation condition comprising:
The waveform complexity parameter is larger than a preset waveform complexity low threshold value and smaller than a preset waveform complexity high threshold value;
the peak amplitude variance is smaller than or equal to a preset variance threshold;
the standard signal waveform amplitude is greater than a preset second amplitude threshold.
6. A defibrillation device control method based on rhythm recognition according to claim 3, characterized in that the heart rhythm parameter and QRS wave width are determined by:
acquiring two adjacent effective valley points and the effective peak point, and taking the effective valley point as an R wave when the effective valley point is larger than the product of a first screening coefficient and the effective peak point and smaller than the product of a second screening coefficient and the effective peak point, otherwise, taking the effective peak point as the R wave;
determining the R wave quantity of the R waves, the R wave amplitude of each R wave and the R wave position information, and determining the heart rate parameter according to the R wave amplitude, the R wave position information and the R wave number;
establishing a QRS wave start-stop window based on the R wave position information as a center, determining a QRS wave starting point forwards according to a preset space threshold, determining a QRS wave end point backwards, and determining the QRS wave width according to the QRS wave starting point and the QRS wave end point;
Wherein the heart rate parameter is calculated by the following formula:
wherein the QRS complex width is obtained by the following formula:
intervalT j ＝Qend j -Qstart j ,j＝(1,2,…,count)，
interval j ＝sort(intervalT j )，
7. The defibrillation device control method based on rhythm recognition of claim 6, wherein the second defibrillation condition comprises:
the heart rate parameter is greater than a preset first heart rate threshold, and the QRS wave width is greater than a preset QRS wave width threshold;
the heart rate parameter is greater than a preset second heart rate threshold, wherein the second heart rate threshold is greater than the first heart rate threshold.
8. A defibrillation device control apparatus based on rhythm recognition, comprising at least one control processor and a memory for communication connection with the at least one control processor; the memory stores instructions executable by the at least one control processor to enable the at least one control processor to perform the rhythm-recognition-based defibrillation device control method of any of claims 1-7.
9. A defibrillation apparatus comprising the rhythm recognition-based defibrillation apparatus control device of claim 8.
10. A computer-readable storage medium storing computer-executable instructions for performing the rhythm-recognition-based defibrillation device control method according to any one of claims 1 to 9.
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