CN119739999A - A patient health warning processing method and system for multiple heart monitoring data - Google Patents

Abstract

The present invention discloses a patient health warning processing method and system for multiple heart monitoring data, the method comprising the following operating steps: collecting heart monitoring data from a target patient, performing sampling frequency and waveform preprocessing on the heart monitoring data to obtain an electrocardiogram signal; confirming the starting point and the ending point of the waveform of the electrocardiogram signal, and using the starting point and the ending point of the waveform to find the inflection point of the waveform trend; extracting heart rate mutation characteristics according to the inflection point of the waveform trend, and identifying the evaluation results of heart health risk symptoms based on the heart rate mutation characteristics; and issuing a warning based on the evaluation results of the heart health risk symptoms.

Description

Patient health early warning processing method and system for various cardiac monitoring data

Technical Field

The invention relates to the field of hearts, in particular to a patient health early warning processing method and system for various heart monitoring data.

Background

Heart diseases, particularly arrhythmias, heart failure and the like, have become a health problem with high mortality and disability rates worldwide.

With the continuous development of medical technology, cardiac monitoring devices and techniques are becoming mature, making it possible to monitor the cardiac health status of a patient in real time.

These devices are capable of recording in detail the electrical activity of the heart via Electrocardiogram (ECG) signals, providing important diagnostic information to the clinician.

However, although electrocardiography is widely used in clinic, due to the influence of noise, motion artifact, environmental interference and other factors, the original electrocardiographic signal often contains a large amount of noise and incomplete information, which affects the quality of the signal and reduces the analysis accuracy and reliability.

Therefore, how to effectively pre-process the electrocardiogram signal to improve the quality of data and the accuracy of subsequent analysis is a great challenge in the current heart monitoring technology.

Furthermore, the complexity of the electrocardiogram signals makes highly accurate waveform analysis techniques necessary for the detection of heart disease.

The traditional electrocardiogram analysis method is mostly dependent on manual interpretation, has strong subjectivity and long time consumption, and cannot realize rapid and automatic real-time monitoring and early warning.

Therefore, how to efficiently extract valuable heart disease features from massive electrocardiographic data through an intelligent analysis method and discover potential heart health risks in time has become an important direction of research and development.

Disclosure of Invention

The invention aims to provide a patient health early warning processing method and system for various cardiac monitoring data, which solve the technical problems pointed out in the prior art.

The invention provides a patient health early warning processing method of various cardiac monitoring data, which comprises the following operation steps:

Collecting heart monitoring data of a target patient, and preprocessing sampling frequency and waveform of the heart monitoring data to obtain an electrocardiogram signal;

Confirming a starting point of a waveform and an ending point of the waveform of the electrocardiogram signal, and searching waveform trend inflection points by utilizing the starting point of the waveform and the ending point of the waveform;

and early warning is carried out according to the evaluation result of the heart health risk symptoms.

The invention also provides a patient health early warning processing system for various cardiac monitoring data, which comprises an acquisition module, an analysis module, an early warning module, a data acquisition module and a data acquisition module;

the acquisition module is used for acquiring heart monitoring data of a target patient, and preprocessing the sampling frequency and the waveform of the heart monitoring data to obtain an electrocardiogram signal;

The analysis module is used for confirming a starting point of a waveform and an ending point of the waveform of the electrocardiogram signal, searching waveform trend inflection points by utilizing the starting point of the waveform and the ending point of the waveform, extracting heart rate mutation features according to the waveform trend inflection points, and identifying the heart rate mutation features to output an evaluation result of heart health risk symptoms;

The early warning module is used for early warning according to the evaluation result of the heart health risk symptoms.

Compared with the prior art, the embodiment of the invention has at least the following technical advantages:

The patient health early warning processing method and system for analyzing the plurality of cardiac monitoring data provided by the invention can be used for removing noise and obtaining stable and clear electrocardiogram signals by carrying out sampling frequency and waveform pretreatment on the cardiac monitoring data in specific application;

Further, the electrocardiogram signal is provided with a search window sliding search feature point to obtain heart rate abrupt change feature points, the first derivative of the waveform is calculated to obtain the inflection point capable of identifying the change rate, the second derivative is calculated to obtain the acceleration which is helpful for revealing the heart rate abrupt change feature points of the electrocardiogram signal, the change trend of the electrocardiogram signal is known, the acceleration change threshold e is preset, whether the acceleration of the change rate is larger than the acceleration change threshold e is judged, so that whether the electrocardiogram signal has the fluctuation point is judged, the stable part or the transition section of the waveform in the electrocardiogram is extracted, the waveform of the electrocardiogram signal is traversed to find the local maximum value point and the local minimum value point to obtain the peak value of the R wave and the T wave, the local minimum value point is also used for representing the trough value of the Q wave and the S wave, the starting point and the ending point of the waveform are obtained to serve as the recovery or calm stage of the electrocardiogram signal, the R wave of the QRS wave is extracted to calculate RR interval, the data of the heart rate is the basis for researching heart rhythm and heart rate fluctuation, the difference between the calculation RR, the RR can reflect the difference between the heart rhythm and the fluctuation, the abnormal stress fluctuation feature sequences can be obtained through the abnormal change of the abnormal change feature sequences, the abnormal change feature sequences can be obtained through the abnormal change of the heart rate, the abnormal change feature sequences can be obtained through the abnormal change of the peak values, the abnormal change feature sequences can be obtained through the calculation, the abnormal change of the abnormal change feature values, the abnormal change of the peak values can be obtained, and identifying heart results (identifying heart mutation features and cycle gradient features to output heart evaluation results) of the heart mutation features and the cycle gradient features, and judging acute and short-term heart diseases of the target patient so as to generate early warning.

Drawings

FIG. 1 is a main flow chart of a patient health pre-warning processing method for multiple cardiac monitoring data according to the first embodiment;

FIG. 2 is a flowchart showing a method for performing cardiac identification according to the patient health pre-warning processing of a plurality of cardiac monitoring data according to the first embodiment;

fig. 3 is a schematic diagram of a QRS complex confirmation method for patient health pre-warning processing of multiple cardiac monitoring data according to the first embodiment;

FIG. 4 is a flowchart showing a method for performing evaluation results of heart judgment by using RR intervals according to the patient health pre-warning processing method of various cardiac monitoring data in the first embodiment;

FIG. 5 is a flow chart of a method for patient health pre-warning processing of multiple cardiac monitoring data using cyclogradation features and heart rate sudden change features to identify a heart according to the first embodiment;

FIG. 6 is a flowchart of a method for patient health pre-warning processing of multiple cardiac monitoring data according to the first embodiment for identifying a heart based on QT interval;

FIG. 7 is a schematic diagram of a QT interval of a patient health pre-warning processing method for multiple cardiac monitoring data according to the first embodiment;

Fig. 8 is a flow chart of a patient health pre-warning processing system for multiple cardiac monitoring data according to the second embodiment.

Reference numerals are the acquisition module 10, the analysis module 20 and the early warning module 30.

Detailed Description

The following description of the embodiments of the present invention will be made apparent and fully in view of the accompanying drawings, in which some, but not all embodiments of the invention are shown.

All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

The invention will now be described in further detail with reference to specific examples thereof in connection with the accompanying drawings.

Example 1

As shown in fig. 1, the invention provides a patient health early warning processing method of various cardiac monitoring data, which comprises the following operation steps:

S1, collecting heart monitoring data of a target patient, and preprocessing sampling frequency and waveform of the heart monitoring data to obtain an electrocardiogram signal;

The heart monitoring data is subjected to sampling frequency and waveform preprocessing, so that noise can be removed, and the signal quality is optimized, thereby ensuring that the subsequent analysis is accurate;

S2, confirming a starting point of a waveform and an ending point of the waveform of the electrocardiogram signal, and searching waveform trend inflection points by utilizing the starting point of the waveform and the ending point of the waveform;

It should be noted that, by analyzing the starting point and the ending point of the waveform and searching for the inflection point of the waveform trend, abnormal changes (such as sudden heart rate changes) in the electrocardiogram signal can be efficiently detected;

Determining heart rate mutation characteristics and evaluating whether the heart disease results in an acute risk or a chronic risk based on the characteristics is helpful for identifying potential heart problems in advance, including arrhythmia, heart failure, etc., and has important reference value in particular for judging sinus arrhythmia;

S3, early warning is carried out according to the evaluation result of the heart health risk symptoms;

it is noted that according to the technical scheme, the heart disease assessment result based on the electrocardiogram signals can give out early warning in time to help medical staff find and treat potential heart risks, and the early warning can provide enough time for intervention before the disease progresses to an acute stage, so that the risk of acute attack is reduced, and the survival rate of patients is improved;

Specifically, as shown in fig. 2, in step S2, a starting point of a waveform and an ending point of the waveform are confirmed for an electrocardiogram signal, a waveform trend inflection point is found by using the starting point of the waveform and the ending point of the waveform, a heart rate abrupt change feature is extracted according to the waveform trend inflection point, and the heart rate abrupt change feature is identified to output an evaluation result of heart health risk symptoms, and the specific operation steps are as follows:

S21, setting a search window for the electrocardiogram signal, and sliding the electrocardiogram signal according to the search window to search for characteristic points to obtain heart rate mutation characteristic points;

It should be noted that, a reasonable search window is set according to the sampling frequency and the waveform characteristics of the signal, for example, the QRS complex in the electrocardiogram is usually between 100 milliseconds and 300 milliseconds, so the search window can be set in the range, the search window is affected by the heart rate, and when the heart rate changes, the period and waveform characteristics also change, so the window size needs to be adjusted in real time;

For convenience in processing, a sliding search window method is used for gradually sliding and searching heart rate mutation feature points along an electrocardiogram signal sequence;

S22, calculating a first derivative of the waveform (namely, the change rate of the waveform) of the electrocardiogram signal to obtain the change rate of the waveform at each moment of the electrocardiogram signal (namely, a slope, wherein the slope is a mathematical concept used for describing the inclination degree of a straight line or curve; the slope in the electrocardiogram signal indicates the speed of signal change and also reflects the steep change of the rising and falling of the waveform), wherein the calculation formula is as follows: ;

Wherein slope (i) is the rate of change between the ith heart rate mutation feature point and the (i+1) th heart rate mutation feature point, Δt is the time interval between the two heart rate mutation feature points;

Calculating the second derivative of the electrocardiogram signal by using the change rate of the waveform of each moment of the electrocardiogram signal to obtain the acceleration (namely the slope change rate) of the change rate, wherein the calculation formula is as follows: ;

It should be noted that, when the first derivative formula is used to express that x (t) represents the potential change in the electrocardiogram, the change speed of the electrocardiogram signal or the inclination degree of the signal at the moment is expressed;

Next, calculating the second derivative of the electrocardiogram signal, expressed by a formula, representing the change of the rate of change of the electrocardiogram signal, also called acceleration, wherein the second derivative reflects the degree of change of the rate of change of the signal;

When the acceleration of the electrocardiogram signal is large, the change rate of the electrocardiogram signal is greatly changed, and the change rate is usually the inflection point of a waveform;

the rate of change of the electrocardiogram signal tends to be smooth, typically the flat-top or flat-bottom portion of the waveform, with the acceleration of the electrocardiogram signal being zero or near zero;

S23, presetting an acceleration change threshold e, and judging whether the acceleration of the change rate is larger than the acceleration change threshold e or not;

If yes, judging heart rate abrupt change feature points of the waveform position of the electrocardiogram signal as fluctuation points;

If not, judging that the waveform of the electrocardiogram signal does not have a fluctuation point;

It should be noted that, when the acceleration of the change rate (i.e., the slope change rate) is greater than the set threshold, it is usually indicated that the signal is rapidly changed or suddenly changed, for example, the boundary of the QRS complex, especially near the R wave, the electrical activity in the electrocardiogram is rapidly changed, resulting in a large change rate of the change rate;

When the slope rate of change of the waveform is less than a set threshold, this generally indicates that the rate of change of the waveform is relatively gentle and there is no apparent point of fluctuation, which generally corresponds to a plateau or transition of the waveform in the electrocardiogram, and does not involve a region of abrupt change such as the QRS complex (i.e., the start and end phases of the P wave are indicated as P waves representing atrial depolarizations, which have a relatively gentle change in potential and therefore relatively small slope rates, the P wave generally does not exhibit a significant abrupt change, the transition of the T wave is indicated as T waves representing ventricular repolarizations, which although the T wave has a certain change, has a relatively slow rate of change relative to the rapid change of the QRS complex, and therefore, the slope rate of change at the start and end of the T wave is generally small, the transition of the waveform is indicated as being between the QRS complex and the T wave, which may gradually slow down, the slope rate of change is below the threshold, generally indicates that the waveform tends to be smooth, which indicates the electrocardiogram is recovered or at a calm phase);

S24, traversing the waveform of the electrocardiogram signal, and searching local maximum value points and local minimum value points in heart rate abrupt change characteristic points of the waveform of the electrocardiogram signal;

Calculating the extreme value amplitude difference between the local maximum value point and the local minimum value point to obtain an extreme value difference point;

Presetting an extreme point threshold r, and judging whether the value of the extreme difference point is larger than the extreme point threshold r;

If not, judging that the waveform of the electrocardiogram signal has no atypical waveform;

If yes, judging that a pseudo extremum point exists in the heart rate mutation feature point of the waveform of the electrocardiogram signal, and eliminating the heart rate mutation feature point of the pseudo extremum point;

the peak values of the R wave and the T wave are represented by local maximum points;

The trough values of the Q wave and the S wave are represented by local minimum value points;

It should be noted that, identifying local maxima and minima are key feature points of the determined waveform, especially for R wave, T wave, Q wave, S wave, by traversing the electrocardiogram signal, finding the point of the local maxima, usually at the R wave and T wave peak values, R wave being the strongest peak, the peak of the T wave being usually lower, finding the point of the local minima in the electrocardiogram signal, Q wave and S wave being the first negative peak and the second negative peak in the electrocardiogram respectively, Q wave being the earliest occurring negative wave, and S wave being the normal time of QRS wave group being 0.06-0.10S, namely 1.5-2.5 cells, never exceeding 3 cells, as shown in fig. 3;

The amplitude difference (such as the amplitude difference of R wave and S wave) between the local maximum value point and the local minimum value point can be calculated, and the difference is helpful for distinguishing the waveform modes of normal and abnormal (i.e. atypical waveform);

S25, presetting a threshold position t for the change rate, and judging whether the change rate exceeds the threshold position t for the first time;

If not, judging that the current change rate of the heart map signal is a fluctuation point exceeding a threshold t for the last time, and taking the current change rate as an ending point of the waveform;

if so, the current change rate of the heart map signal is determined to be a fluctuation point exceeding the threshold position t for the first time, and the fluctuation point is taken as a starting point of the waveform.

It should be noted that, in the process of electrocardiogram signal, the change rate of waveform refers to the change rate of the electrocardiogram signal potential (i.e. the slope of the electrocardiogram signal), the QRS complex is the part with the largest change rate in the electrocardiogram, so we can effectively distinguish the QRS complex (i.e. the QRS complex component is divided into Q waves: the first downward deflected wave in the QRS complex, R waves: the upward deflected wave in the QRS complex, S waves: the downward deflected wave after the R wave, and the QRS complex is formed, and the QRS complex is the part with the largest change rate in the electrocardiogram and can also represent the normal or abnormal state of the electrocardiogram signal) from other relatively gentle waveforms (such as P wave and T wave), and select a suitable change rate threshold (i.e. the threshold position T) to help distinguish the start point and the end point of the QRS complex;

The starting point of the QRS complex can be determined by determining whether the rate of change of the electrocardiogram signal exceeds a preset threshold position t for the first time. The onset of the QRS complex typically occurs where the signal potential rises sharply, i.e., the first time the slope exceeds a threshold, this location is typically the R-wave onset of the QRS complex, marking the onset of ventricular depolarization;

If the electrocardiogram signal does not exceed the preset rate of change threshold again, we can consider the last time the threshold was exceeded as the end point of the QRS complex, which will typically occur after the S wave, marking the end of the ventricular depolarization process;

s26, obtaining the starting point time and the ending point time of the QRS complex through the starting point of the waveform and the ending point of the waveform, and obtaining the duration of the QRS complex through calculation of the starting point time and the ending point time;

It should be noted that by determining the starting point and the ending point of the QRS complex, the duration of the QRS complex can be calculated, which is an important indicator for assessing the ventricular depolarization process, and is important for further analysis of the electrocardiogram (e.g., detecting heart rhythm problems);

s27, marking boundary points of the internal waveform segments through the starting point and the ending point of the QRS complex;

Extracting waveform segments of all R waves of an electrocardiogram signal (namely all R waves of a QRS wave group in the electrocardiogram signal) through boundary points, and calculating time difference between every two adjacent R waves in the electrocardiogram signal to obtain an RR interval sequence (namely RR is every two adjacent R waves in the electrocardiogram signal, and the RR interval sequence is a time value of each RR interval extracted from the electrocardiogram signal);

calculating a difference value for each RR interval in the RR interval sequence to obtain an RR interval difference value;

Calculating a difference standard deviation by using the RR period difference value, wherein the calculation formula is as follows:

;

in the formula, Is the average value of the RR interval difference value sequence; Denoted as RR interval difference, N is the number of data points (i.e. the data points are actual values extracted from the electrocardiogram signal), each RR interval value (i.e. the time difference between two adjacent R-waves) is a data point, if an electrocardiogram signal is monitored, after detection of R-waves, a series of RR intervals are obtained, which are data points, and when calculating the RR interval difference, a difference calculation is performed based on these data points, e.g. if 10 RR intervals (R1 to R10) are extracted, there are 10 data points);

It should be noted that, by determining the starting point and the ending point of the QRS complex, boundary points of each waveform segment (such as the starting point and the ending point of R wave of each segment in the QRS complex) can be accurately marked, and these boundary points are the basis of electrocardiogram analysis and diagnosis, so as to help doctors judge the heart health state;

The R wave is usually the strongest wave in electrocardiogram and represents the depolarization of heart chamber and is the sign of heart beat detection, so that taking the R wave of electrocardiogram signal as example, the heart is early-warning and identified, the RR interval is the time difference between two adjacent R waves, the time interval between every two adjacent R waves (i.e. the value of every RR interval) is extracted from electrocardiogram signal to obtain RR interval sequence, which provides the data of heart beat period and is the basis for researching heart rhythm and heart rate fluctuation, the ith two adjacent R wave time differences in RR interval sequence are represented by RR (i), the two adjacent R wave time differences adjacent to RR (i) time difference are represented by RR (i+1), the time difference between RR (i.e. RR (i) and RR (i+1) is the time difference between two adjacent RR intervals) is represented by the formula Representing the calculation of RR interval difference (i.e. RR interval difference is) The difference value reflects the fluctuation condition of the heart beat period change, the RR interval difference value is smaller when the heart rate is stable, and the RR interval difference value is larger when the heart rate change is larger (namely, the arrhythmia symptom can be represented);

Calculating RR interval difference Standard Deviation (SDRR) which is a statistical measure of RR interval difference and represents the fluctuation degree of RR interval difference, and can identify abnormal heartbeat, arrhythmia and other problems and reflect heart health;

S28, calculating the average value of n data points before and after each RR interval in the RR interval sequence;

calculating the change rate (i.e. slope) of the RR interval sequence by the standard deviation of the average value and the difference value;

obtaining periodic gradual change characteristics of the RR interval sequence according to the change rate of the RR interval sequence;

recording waveform trend inflection points which appear in the RR interval sequence due to the change rate according to the periodic gradual change characteristics;

It should be noted that the n-point moving average is a method for smoothing signals, and by processing the n-point moving average, the interference caused by instantaneous fluctuation or noise in the electrocardiogram can be effectively removed, so that the heart rate variation trend on a long time scale is more obvious;

Further extracting periodic gradual change characteristics of RR interval sequences, for example, the gradual slow down of heart beat is represented by a constant negative value and the gradual acceleration of heart beat is represented by a constant positive value, the periodic gradual change characteristics reveal the gradual change mode of heart rate along with time, heart beat can be gradually accelerated or gradually slowed down under a certain physiological or psychological state, for example, heart beat is gradually accelerated during exercise and heart beat is gradually slowed down during rest, and different physiological or emotional states (such as exercise, pressure, relaxation and the like) can be identified by extracting the gradual change characteristics;

Calculating the slope by means of the mean and difference standard deviations provides rate information of heart rate variation (i.e. rate of change) for each time point, the variation of heart rate usually not sudden but gradual, the acceleration or slowing down process of heart rate can be quantified by calculating the slope at each moment, for example, the heart rate gradually accelerates while exercising, the slope value will gradually increase, the heart rate gradually slows down while resting, the slope value gradually decreases, such quantitative analysis helps to understand the physiological process more accurately;

cycle progression features refer to a pattern of gradual changes in heart rhythm or heart rate over time, typically manifested as gradual increases or decreases in the interval of heart beats (i.e., RR intervals), gradual slowing or speeding of heart rate, gradual accumulation of changes in QRS complex, such progression may be due to gradual changes in the physiological state of the heart, autoregulation, or external stimuli, etc., such as acceleration during exercise, deceleration during rest, etc., gradual changes in heart rate from a normal frequency to a slower or faster rhythm, such changes may occur over a longer period of time, reflecting changes in heart during physiological adaptation;

Calculating the change of the slope through the continuous change trend of the period gradual change characteristic, and identifying inflection points of heart rate change (such as turning points from acceleration to deceleration, namely peak points or valley points in waveform segments of R waves), wherein the acceleration and the deceleration of the heart rate are not always constant, but have certain inflection points;

s29, screening an abnormal periodic sequence according to the periodic gradual change characteristic by the RR interval sequence, marking abnormal fluctuation of the abnormal periodic sequence through waveform trend inflection points to obtain a heart rate abrupt change characteristic;

It should be noted that a sudden change in heart rate is characterized by a sharp, abrupt change in heart rate in a short period of time, typically manifested as a sudden increase or decrease in heart rate, and a large change, such a sudden change may be caused by heart disease, sinus node abnormality, conduction system abnormality, or some external stimulus, by a process including sudden acceleration of heart beat (such as tachycardia or atrial fibrillation), sudden slowing of heart beat (such as bradycardia or sinus arrest), sudden arrhythmia (such as premature beat, ventricular fibrillation, etc.), such as a sudden increase or decrease in heart rate in an electrocardiogram, a large amplitude of heart rate changes that may be associated with an acute disease or abnormal heart function, and a short time;

The cyclogradation feature typically exhibits a gradual, continuous change with a small amplitude of change in heart rate, possibly for a longer period of time, typically associated with normal physiological adaptation or chronic problems; the sudden change of heart rate is characterized by sudden and abrupt changes, the large change amplitude of the heart rate is usually caused by pathological reasons (such as arrhythmia and acute cardiac event) and usually occurs in a short time, so that the time scale, the change mode and the physiological mechanism of the periodic gradual change feature and the sudden change of heart rate are different although the periodic gradual change feature and the sudden change feature of heart rate are related to the change of heart rate;

Specifically, as shown in fig. 4, in step S29, the RR interval sequence screens the abnormal periodic sequence according to the periodic gradient feature, marks the abnormal fluctuation of the abnormal periodic sequence through waveform trend inflection points to obtain a heart rate abrupt change feature, and identifies the heart rate abrupt change feature and the periodic gradient feature to output the evaluation result of the heart, and the specific operation steps are as follows:

s291, presetting a normal period range u according to the period gradual change characteristic (namely, presetting the normal period range u according to the characteristic of the period gradual change characteristic for identifying the physiological state of an individual (namely, identifying the characteristic of acceleration of a heart beat such as a movement center and deceleration of the heart beat in rest), and judging whether an RR interval in an RR interval sequence is in the normal period range u (namely, the RR interval is in the preset normal period range u, and the heart beat is indicated to be normal when the RR interval is in the normal period range u);

if the RR interval is equal to the normal period range u, judging that the RR interval is normal and no abnormality occurs;

If the RR interval is larger than the normal period range u, judging that the RR interval is overlong as an overlong period;

If the RR interval is smaller than the normal period range u, judging that the RR interval is too short, and taking the RR interval as an excessively short period;

establishing a set of overlong periods and excessively short periods as an abnormal period sequence;

It should be noted that, the normal cycle range u is preset according to the characteristic of the cycle gradual change characteristic for identifying the physiological state of the individual (i.e. the characteristic of being able to identify the acceleration of the heart beat in motion and the deceleration of the heart beat in rest), and whether the abnormal heart rate range exists in the RR interval sequence is judged through the normal cycle range u (i.e. the RR interval is obtained through the time difference between two adjacent R waves in the electrocardiogram signal in the above step S26, so the RR interval is a time unit and represents the heart rate condition (i.e. the speed of the heart beat) of the R wave in the RR interval, while the preset normal cycle range u is within a certain time, i.e. the heart rate condition of the R wave of the normal human body, so whether the heart rate of the RR interval is normal can be judged through the normal cycle range u);

if the RR interval is within the normal period range u, the abnormal heart beat period is indicated, and the problems such as arrhythmia and the like are possibly caused;

S292, counting the abnormal periodic sequence, and calculating the duty ratio of the abnormal periodic sequence to the RR interval sequence;

If the duty ratio of the abnormal periodic sequence is greater than half of the RR interval sequence, presetting a periodic mutation threshold o of the RR interval difference value;

Judging whether the RR interval difference value (namely, the RR interval difference value is the RR interval difference value between an excessively long period and an excessively short period which possibly have abnormality, the difference value of the abnormal period in the abnormal period sequence and the difference value of the RR interval which does not belong to the normal heart rate) is larger than a period mutation threshold value o;

If not, judging that the RR interval in the abnormal periodic sequence has no abnormal heart problem;

if yes, judging that the RR interval in the abnormal periodic sequence has periodic mutation;

it should be noted that counting the number of RR intervals in the abnormal periodic sequence, and then judging whether the number of RR intervals in the abnormal periodic sequence accounts for half or more of the total RR interval sequence, is helpful for judging the overall stability of the electrocardiogram signal, if so, it may indicate that there is a problem in heart health;

Abnormal fluctuations in RR interval differences are one of the early signals for detecting arrhythmias.

The arrhythmia such as atrial fibrillation, ventricular premature beat and the like often shows abnormal changes of RR intervals, and the changes can be identified by calculating the RR interval difference value, so that the periodic mutation threshold value o of the RR interval difference value is preset, and whether the RR interval difference value is larger than the periodic mutation threshold value o is judged, so that the potential arrhythmia problem of the heart rate can be judged;

s293, marking waveform trend inflection points of the periodic abrupt RR intervals as periodic abrupt points;

Calculating mutation amplitude values of two adjacent RR intervals through each marked periodic mutation point, and obtaining mutation amplitude through the mutation amplitude values;

Obtaining heart rate mutation characteristics of the QRS complex through all mutation amplitudes;

it should be noted that, the periodic abrupt points are marked as inflection points of the waveform trend of the RR interval, the RR interval is the time interval between two heartbeats, the abrupt points reflect the abrupt change of the heart rate, such as the occurrence of arrhythmia, and the potential abnormal fluctuation can be early warned by identifying the inflection points;

The mutation amplitude of two adjacent RR intervals is calculated between each periodic mutation point, the mutation amplitude reflects the severe change of the heart beat period and usually corresponds to abnormal fluctuation in an electrocardiogram, which is helpful for detecting and quantifying the severe fluctuation of the heart rate, and is very important in judging whether arrhythmia exists or not;

The QRS complex represents the heart contraction process, can embody the key clue of abnormal heart activity most, and the R wave can embody the change process of the QRS complex on the heart rate most, so that all mutation amplitudes form the heart rate mutation characteristics of the QRS complex;

The heart rate mutation characteristic is used as a basis for reflecting the rapid change of heart rate, and is mainly used for predicting abnormal fluctuation of an electrocardiogram signal;

s294, respectively extracting mutation parameters and gradient parameters of heart rate mutation features and periodic gradient features, and comprehensively evaluating heart early warning by using the mutation parameters and the gradient parameters, wherein the mutation parameters comprise mutation occurrence frequency, and the gradient parameters comprise gradient frequency;

it should be noted that the cyclogradation feature usually shows a gradual, continuous change, with a smaller amplitude of change in heart rate, possibly for a longer period of time, usually associated with normal physiological adaptation or chronic problems, whereas the sudden change in heart rate feature shows a sudden, abrupt change, with a larger amplitude of change in heart rate, usually due to pathological causes (e.g. arrhythmia, acute cardiac event), usually occurring in a short period of time;

Therefore, the gradual change parameters and the abrupt change parameters are extracted through two different characteristics, and the periodic gradual change characteristics can be precursors of heart abrupt change, especially in chronic heart problems, the gradual change state of the heart can finally cause the occurrence of heart rate abrupt change;

The gradual change parameters are helpful for revealing chronic heart diseases or potential physiological adaptation problems, such as heart failure, gradual decline of heart functions and the like;

Specifically, as shown in fig. 5, in step S294, the sudden change and gradual change parameters are extracted from the sudden change and gradual change characteristics of heart rate, and the sudden change and gradual change parameters are used for comprehensive evaluation of heart early warning, which comprises the following steps:

s2941, analyzing periodic mutation points of heart rate mutation characteristics through the duration of the QRS complex, and taking the duration of the QRS complex as the mutation duration of the heart rate mutation characteristics;

The periodic abrupt change point is marked as an inflection point of the waveform trend of the RR interval, the RR interval is the time interval between two heartbeats, the periodic abrupt change point reflects the abrupt change of the heart rate, meanwhile, the duration of the QRS complex is obtained in the step S27, when the duration of the QRS complex is changed significantly, the heart conduction can be considered to have abrupt change, and the abrupt change can be caused to occur in the RR interval, wherein the duration of the abrupt change is the duration of the change of the duration of the QRS complex, and if the duration of the QRS complex is increased or decreased and is changed continuously for a certain period of time, the changed time can be used as the abrupt change duration (TD) of the heart rate abrupt change feature;

s2942, obtaining mutation occurrence frequency for the occurrence frequency of the overlong period and the overlong period of the abnormal period sequence in the mutation duration time;

having been explained in step S291, the abnormal periodic sequence is an abnormal mutation occurring in the RR interval sequence, and the frequency of occurrence of the periodic mutation point is recorded by calculating their occurrence time interval (i.e., the RR interval is the time interval between two heartbeats) in the duration of the QRS complex (i.e., the mutation duration) through the RR intervals of the long period and the too short period, thereby obtaining the mutation occurrence frequency;

s2943, extracting gradient parameters from the periodic gradient characteristics to obtain gradient rate;

In step S28, the periodic gradient feature is obtained by calculating the slope of the standard deviation of the average value and the difference of the RR intervals of the RR interval sequence to provide the rate information of heart rate change (i.e. change rate) for each time point, so the change rate of the RR intervals can be directly used as the gradient rate of the periodic gradient feature;

S2944 determining whether the ramp rate of the cycloramp feature is too long (i.e., whether the acceleration of the ramp rate increases or decreases, i.e., whether the time interval of the RR interval is too long, reflecting the ramp rate and the ramp trend can reveal possible underlying chronic heart disease (e.g., heart failure, myocardial ischemia, etc.));

If not, judging that the heart monitoring data collected by the target patient is normal;

If so, further judging whether the mutation occurrence frequency is suddenly changed in a state that the gradual change rate is too long (namely, if the mutation is suddenly changed in a gradual heart rate background, the transition from a chronic problem to an acute problem occurs; for example, when the gradual change of the heart rate is faster and the amplitude is increased, the sudden rapid fluctuation (mutation) of the heart rate may indicate the occurrence of serious arrhythmia);

If not, judging that the heart monitoring data acquired by the target patient is abnormal, wherein the target patient is suffering from chronic heart disease (namely, firstly, checking whether the target patient is suffering from the chronic heart disease with steady acceleration of gradual change rate (namely, change rate) through periodic gradual change characteristics, and if so, checking that gradual change of heart rate which may suddenly occur is faster and faster (namely, the acceleration of change rate is continuously increased), so that the obtained fixed mutation occurrence frequency is required to monitor, and see whether mutation occurs at a certain frequency, so that the chronic heart disease is converted into acute heart disease, and prompting subsequent medical staff after early warning is sent to prevent the aggravation and timely treatment of the target patient);

If yes, judging that the heart monitoring data acquired by the target patient is abnormal, wherein the target patient has acute heart diseases;

It should be noted that by determining whether the rate of the periodic ramp feature is too long, it is possible to identify the abnormal rate of heart rate changes, which may be associated with potentially chronic heart conditions (e.g., heart failure, myocardial ischemia, etc.), which are often accompanied by changes in ramp rate, particularly changes in heart rate or RR intervals, if the acceleration of such changes (i.e., changes in ramp rate) increases or accelerates, meaning the condition may be worsening, by monitoring these changes, it is possible to detect a potential acute event early, avoiding the patient from entering an acute episode without immediate treatment;

The rapid fluctuation of the heart rhythm can be timely found through the frequency monitoring of the heart rate mutation, the mutation fluctuation usually indicates the occurrence of serious arrhythmia, if the occurrence of acute heart disease can be timely found and treated, the risk of the occurrence of acute heart disease can be greatly reduced, the aggravation of the patient disease condition can be avoided through rapid intervention, when the gradual change rate is abnormal, the transition from the chronic heart problem to the acute problem can be timely found through the monitoring of the mutation occurrence frequency of the heart rate, for example, if the heart rate suddenly fluctuates in case of the acceleration or the acceleration of the gradual change rate is increased, the rapid fluctuation of the heart rate can be the precursor of arrhythmia or other acute disease conditions.

Specifically, as shown in fig. 6, in step S294, the cardiac early warning is comprehensively evaluated by using the mutation parameter and the gradient parameter, and further includes the cardiac early warning for identifying QT interval prolongation by using QT interval, and the specific operation steps are as follows:

s2941' obtaining an RR interval time sequence of an electrocardiogram signal by calculating RR intervals among all R waves in the QRS complex;

It should be noted that the RR interval is the time interval between two adjacent R waves, which are the most significant part of the QRS complex, representing the major part of ventricular depolarization;

The intervals among a plurality of R waves are calculated to form a time sequence called RR interval time sequence, which can be regarded as a periodic time sequence to describe the fluctuation condition of heart rate (or heart beat period) in a certain time period, and the RR interval time sequence not only can reflect normal heart beat rhythm, but also can capture abnormal conditions, especially has good recognition effect when diagnosing diseases such as arrhythmia, QT interval prolongation and the like;

S2942' takes the starting point of the QRS complex as the starting point of the Q wave;

taking the ending point of the QRS complex as the starting point of the T wave;

It should be noted that, in step S26, the starting point and the ending point of the QRS complex have been obtained, and the QRS complex includes a Q wave, an R wave, and an S wave, where the Q wave is the first band in the QRS complex, so the starting point of the QRS complex is the starting point of the Q wave;

The T wave represents the process of repolarization of the ventricle, which is a waveform, usually a positive wave, in the electrocardiogram signal immediately following the QRS complex, after which the T wave occurs immediately, so the end point of the QRS complex can be taken as the starting point of the T wave;

s2943', collecting a section of waveform segment after the QRS complex in an electrocardiogram signal as a preliminarily obtained T wave;

Identifying the static state of a baseline of a waveform segment of a T wave which is preliminarily obtained after the QRS complex in an electrocardiogram signal, and presetting a baseline stability threshold p of the electrocardiogram signal;

Judging whether the baseline of the waveform segment of the T wave is smaller than a baseline stability threshold p;

if not, judging that the base line of the waveform segment of the T wave is unstable, wherein the waveform segment of the T wave cannot determine the ending point of the T wave;

If yes, judging that the base line of the waveform segment of the T wave is stable, and primarily obtaining the waveform segment of the T wave;

Dividing the waveform segment of the preliminarily obtained T wave into a plurality of small segments [ T1, T2], [ T2, T3], [ ti, ti+1], calculating the difference of each small segment to obtain the difference value of each small segment, wherein the calculation formula is as follows:

;

in the formula, A waveform segment of a T wave preliminarily obtained after a QRS complex represented as an electrocardiogram signal;

Judging whether the difference value of each small segment is consistent;

If not, judging that the differential values of each small segment are inconsistent, primarily obtaining that the waveform segment baseline fluctuation of the T wave is large, and collecting the waveform segment after the QRS wave group in the electrocardiogram signal again to be used as the T wave (namely, when the waveform segment is collected again to be used as the T wave, increasing the distance of the waveform segment in the waveform segment of the original collected T wave to obtain the waveform segment of the new collected T wave);

if so, judging that the difference value of each small segment is consistent, and judging that the base line of the waveform segment of the T wave is stable, so as to obtain the finally confirmed T wave;

It should be noted that, a segment of waveform segment after QRS complex in an electrocardiographic signal is collected as a preliminarily obtained T wave, whether the baseline of the waveform segment of the preliminarily obtained T wave is a straight line is identified, firstly, whether the baseline of the waveform segment of the T wave is stable is preliminarily judged through a preset baseline stability threshold p of the electrocardiographic signal, if the baseline of the T wave is a straight line, the signal change in the area should be stable, so that whether the baseline of the waveform segment of the preliminarily judged T wave is stable is judged through the preset baseline stability threshold p of the electrocardiographic signal, if the baseline of the waveform segment of the T wave is in a stable state, whether the baseline of the waveform segment of the T wave is a straight line is further verified, the regularity of the change of the baseline is analyzed by using the difference of signals, and the waveform segment is divided into a plurality of small segments, and the difference (namely the change amount between adjacent points) of each segment of waveform is calculated, so that the trend of the change of the baseline can be obtained. If the difference of each small segment is smaller and consistent, the baseline of the waveform segment is relatively stable, and the baseline is a straight line, so that a T wave is obtained;

S2944', determining the ending point of the T wave through the waveform segment of the T wave;

calculating according to the starting point of the Q wave and the ending point of the T wave to obtain a QT interval;

obtaining a QT interval time sequence of the electrocardiogram signal according to the QT interval;

It should be noted that the time series reflects the time variation of the depolarization and repolarization of the central chamber of each cycle of the heart, that by analyzing the QT interval time series, information about heart rate variation, QT interval variation, and possible heart abnormalities (such as prolongation or shortening of QT interval) can be obtained, as shown in fig. 7, the location of QT interval in the electrocardiogram signal, and the location of QT interval in relation to the start point of the QRS complex and the end point of the T wave.

S2945', carrying out gradual change identification on the QT interval time sequence through a periodic gradual change characteristic, and calculating the change rate of the QT interval, wherein the calculation formula is as follows:;

in the formula, Is the sum of the weighting coefficients (i.e., the sum of coefficients typically used in calculating a weighted average; the effect of this portion is to weight the amount of change (e.g., using exponential decay or other weighting function) such that data closer to the current time has a greater impact on the rate of change);

wi is a weighting system (i.e. this is a weighting coefficient, which is set according to a selected weighting function (e.g. exponential decay) for different time points i; in general, the nearest time point i=0 will have the greatest weight, which gradually decreases over time; this weight is typically: Wherein α is a decay factor that determines the decay rate of the weight, in order to effectively capture the periodicity of the QT interval (i.e., the QT interval is reduced when the heart rate is increased, and the QT interval is prolonged when the heart rate is decreased, forming a periodic fluctuation) and a cyclogradation feature, the decay factor (e.g., exponential decay) may play an important role in weighted averaging or weighted analysis, the decay factor controls the weights at different time points such that the closer time points (typically more relevant to the current time point) occupy more weight in weighted computation, and the contribution of the farther time points (less relevant) to the computation result is gradually reduced, particularly in the periodic fluctuation of the QT interval, the current time point data typically most reflect the instantaneous periodic state, for example, the QT interval is briefly shortened when the heart rate is increased, and this change has the greatest impact on the current heart state, thus, among the periodic changes, the nearest several data points have the strongest impact on the current trend);

A value representing the QT interval at time t-i;

A value representing the QT interval at time t-i-1 (i.e., this term is used to calculate the amount of change in QT interval between adjacent time points, typically to measure the change in QT interval between successive times);

Indicating the difference between the current QT interval and the previous QT interval (i.e., indicating the amount of change in QT interval);

It should be noted that, the QT interval prolongation is not an emergency but a gradual change process, and the QT interval may show periodic change, so that the periodic characteristic of the periodic gradual change is used to identify the gradual change of the QT interval time sequence (i.e., gradual change identification is represented as an identification of the gradual change process of the QT interval, and a periodic change of the change rate of the QT interval is calculated);

s2846', setting a time combination window through the change rate of the RR interval and the change rate of the QT interval;

simultaneously detecting the heart rate mutation of the heart rate mutation syndrome of the QT interval time sequence and the RR interval time sequence in the time combination window;

if the heart rate in the time combination window suddenly increases, judging that the QT interval has a period prolongation, and sending out an early warning signal of the QT interval prolongation;

if the heart rate in the time combination window does not change, judging that the QT interval is normal;

It should be noted that, rapid changes in heart rate may affect the stability of QT interval, resulting in prolongation or irregular fluctuations of QT interval, and thus, heart rate mutations may be closely related to the occurrence of prolongation of QT interval;

By setting a time joint window, monitoring heart rate changes of the time sequence of the QT interval and the time sequence of the RR interval (namely monitoring whether heart rate mutation exists or not), if the heart rate suddenly increases in a certain time joint window, the QT interval has a periodical prolongation trend, and the continuous heart rate is a warning signal of the prolongation of the QT interval;

example two

As shown in FIG. 8, the invention also provides a patient health early-warning processing system for various cardiac monitoring data, which comprises an acquisition module 10, an analysis module 20, an early-warning module 30;

The acquisition module 10 is used for acquiring heart monitoring data of a target patient, and preprocessing sampling frequency and waveform of the heart monitoring data to obtain an electrocardiogram signal;

The analysis module 20 is used for confirming a starting point of a waveform and an ending point of the waveform of the electrocardiogram signal, searching waveform trend inflection points by utilizing the starting point of the waveform and the ending point of the waveform, extracting heart rate mutation features according to the waveform trend inflection points, and identifying the heart rate mutation features to output an evaluation result of heart health risk symptoms;

The early warning module 30 is used for early warning according to the evaluation result of the heart health risk symptoms.

In summary, the patient health early warning processing method and system for various cardiac monitoring data provided by the embodiment of the invention can be used for removing noise and obtaining stable and clear electrocardiogram signals by preprocessing sampling frequency and waveform of cardiac monitoring data;

Further, the electrocardiographic signal is provided with a search window sliding search feature point to obtain heart rate mutation feature points, the first derivative of the waveform is calculated to obtain the inflection point which can identify the change rate, the second derivative of the change rate is calculated to obtain the acceleration which is helpful to reveal the heart rate mutation feature points of the electrocardiographic signal, the change trend of the electrocardiographic signal is known, the acceleration change threshold e is preset, whether the acceleration of the change rate is larger than the acceleration change threshold e is judged, so that whether the electrocardiographic signal has a fluctuation point is judged, and the stable part or the transition section of the waveform in the electrocardiographic signal is extracted;

The method comprises the steps of extracting R waves of a QRS complex, calculating RR intervals, providing data of heart cycle, researching heart rhythm and heart rate fluctuation, calculating difference between the RR intervals, reflecting abnormal heart rate, arrhythmia and the like, calculating average value between the RR intervals, calculating change rate of the RR intervals through the average value and the difference value to obtain cycle gradual change characteristics, extracting the gradual change characteristics, identifying different physiological or emotional states (such as movement, pressure, relaxation and the like), screening abnormal cycle sequences by utilizing the cycle gradual change characteristics, marking abnormal fluctuation of the abnormal cycle sequences through waveform trend inflection points to obtain heart rate mutation characteristics, judging whether acute heart health problems exist in a target patient, identifying heart results of the heart rate mutation characteristics and the cycle gradual change characteristics, judging acute heart diseases and short-term heart diseases of the target patient, and accordingly giving early warning.

Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solutions of the present invention, and not for limiting the same, and that one skilled in the art may modify the technical solutions described in the above-mentioned embodiments or make equivalent substitutions for some or all of the technical features thereof, and these modifications or substitutions do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims (9)

1. A patient health early warning processing method of various cardiac monitoring data is characterized by comprising the following operation steps:

Collecting heart monitoring data of a target patient, and preprocessing sampling frequency and waveform of the heart monitoring data to obtain an electrocardiogram signal;

Confirming a starting point of a waveform and an ending point of the waveform of the electrocardiogram signal, and searching waveform trend inflection points by utilizing the starting point of the waveform and the ending point of the waveform;

and early warning is carried out according to the evaluation result of the heart health risk symptoms.

2. The method for processing patient health warning of a plurality of cardiac monitoring data according to claim 1, wherein the step of confirming a start point of a waveform and an end point of the waveform for the electrocardiographic signal comprises the steps of:

setting a search window for the electrocardiogram signal, and sliding the electrocardiogram signal according to the search window to search for characteristic points to obtain heart rate mutation characteristic points;

Calculating the first derivative of the waveform of the electrocardiogram signal to obtain the change rate of the waveform of the electrocardiogram signal at each moment, wherein the calculation formula is as follows: ;

Wherein slope (i) is the rate of change between the ith heart rate mutation feature point and the (i+1) th heart rate mutation feature point, Δt is the time interval between the two heart rate mutation feature points;

Calculating the second derivative of the electrocardiogram signal by utilizing the change rate of the waveform of each moment of the electrocardiogram signal to obtain the acceleration of the change rate, wherein the calculation formula is as follows: ;

presetting an acceleration change threshold e, and judging whether the acceleration of the change rate is larger than the acceleration change threshold e or not;

If yes, judging heart rate abrupt change feature points of the waveform position of the electrocardiogram signal as fluctuation points;

If not, judging that the waveform of the electrocardiogram signal does not have a fluctuation point;

traversing the waveform of the electrocardiogram signal, and searching local maximum value points and local minimum value points in heart rate abrupt change characteristic points of the waveform of the electrocardiogram signal;

calculating the extreme point amplitude difference between the local maximum value point and the local minimum value point to obtain an extreme value difference point;

presetting an extreme point threshold r, and judging whether the value of the extreme difference point is larger than the extreme point threshold r;

if not, judging that the waveform of the electrocardiogram signal does not have atypical waveform;

If yes, judging that a pseudo extremum point exists in the heart rate mutation feature point of the waveform of the electrocardiogram signal, and eliminating the heart rate mutation feature point of the pseudo extremum point;

Using the local maximum point to represent peak values of R wave and T wave;

using the local minimum point to represent the trough values of the Q wave and the S wave;

presetting a threshold position t for the change rate, and judging whether the change rate exceeds the threshold position t for the first time;

If not, judging that the current change rate of the heart map signal is a fluctuation point exceeding a threshold t for the last time, and taking the current change rate as an ending point of the waveform;

if so, the current change rate of the heart map signal is determined to be a fluctuation point exceeding the threshold position t for the first time, and the fluctuation point is taken as a starting point of the waveform.

3. The method for processing the patient health warning of the plurality of cardiac monitoring data according to claim 2, wherein the method for searching the waveform trend inflection point by using the starting point of the waveform and the ending point of the waveform comprises the following steps:

obtaining the starting point time and the ending point time of the QRS complex by the starting point of the waveform and the ending point of the waveform, and calculating by the starting point time and the ending point time to obtain the duration of the QRS complex;

marking boundary points of the internal waveform segments through the starting point and the ending point of the QRS complex;

extracting waveform segments of all R waves of the electrocardiogram signal through the boundary points, and calculating time difference between every two adjacent R waves in the electrocardiogram signal to obtain an RR interval sequence;

calculating a difference value for each RR interval in the RR interval sequence to obtain an RR interval difference value;

calculating a difference standard deviation by using the RR period difference value, wherein the calculation formula is as follows:

;

in the formula, Is the average value of the RR interval difference value sequence; expressed as RR interval difference value, N is the number of data points;

calculating an average value of n data points before and after each RR interval in the RR interval sequence;

calculating the change rate of the RR interval sequence according to the average value and the standard deviation of the difference value;

obtaining periodic gradient characteristics of the RR interval sequence according to the change rate of the RR interval sequence;

And recording waveform trend inflection points of the RR interval sequence due to the change rate according to the period gradual change characteristic.

4. The method for processing patient health pre-warning of multiple cardiac monitoring data according to claim 3, wherein the steps of extracting heart rate mutation features according to the waveform trend inflection points, and identifying the heart rate mutation features to output the evaluation result of heart health risk symptoms are as follows:

and calling an RR interval sequence to screen an abnormal periodic sequence according to the periodic gradual change characteristic, marking abnormal fluctuation of the abnormal periodic sequence through the waveform trend inflection point to obtain a heart rate abrupt change characteristic, and outputting a heart evaluation result for the heart rate abrupt change characteristic and the periodic gradual change characteristic.

5. The method for processing patient health pre-warning of multiple cardiac monitoring data according to claim 4, wherein the step of calling the RR interval sequence to screen the abnormal periodic sequence according to the periodic gradient feature comprises the following steps:

presetting a normal period range u according to the period gradual change characteristic, and judging whether RR intervals in the RR interval sequence are in the normal period range u or not;

if the RR interval is equal to the normal period range u, judging that the RR interval is normal and no abnormality occurs;

if the RR interval is larger than the normal period range u, judging that the RR interval is overlong as an overlong period;

if the RR interval is smaller than the normal period range u, judging that the RR interval is too short, and taking the RR interval as an excessively short period;

and establishing a set of the overlong period and the overlong period as an abnormal period sequence.

6. The method for processing patient health pre-warning of multiple cardiac monitoring data according to claim 5, wherein the abnormal fluctuation of the abnormal periodic sequence is marked by the waveform trend inflection point, and the heart rate mutation characteristic is obtained, and the specific operation steps are as follows:

Counting the abnormal periodic sequence, and calculating the duty ratio of the abnormal periodic sequence to the RR interval sequence;

If the duty ratio of the abnormal periodic sequence is greater than half of the RR interval sequence, presetting a periodic mutation threshold o of the RR interval difference value;

Judging whether the RR interval difference value is larger than a periodic mutation threshold value o or not;

If not, judging that the RR interval in the abnormal periodic sequence has no abnormal heart problem;

if yes, judging that the RR interval in the abnormal periodic sequence has periodic mutation;

Marking waveform trend inflection points of the periodic abrupt RR intervals as periodic abrupt points;

Calculating mutation amplitude values of two adjacent RR intervals through each marked periodic mutation point, and obtaining mutation amplitude through the mutation amplitude values;

the heart rate abrupt change characteristics of the QRS complex are obtained by all the abrupt change amplitudes.

7. The method for processing patient health pre-warning of multiple cardiac monitoring data according to claim 6, wherein the step of identifying the heart rate abrupt change feature and the periodic gradual change feature to output the heart evaluation result comprises the following steps:

Extracting mutation parameters and gradient parameters from the heart rate mutation characteristics and the periodic gradient characteristics respectively;

the mutation parameters include mutation occurrence frequency;

the fade parameters include fade frequency.

8. The method for processing the patient health pre-warning of the plurality of cardiac monitoring data according to claim 7, wherein the method is characterized in that the sudden change characteristic and the periodic gradual change characteristic of the heart rate are respectively extracted with a sudden change parameter and a gradual change parameter, and the sudden change parameter and the gradual change parameter are utilized for comprehensively evaluating the cardiac pre-warning, and the specific operation steps are as follows:

Analyzing periodic mutation points of heart rate mutation features through the duration of the QRS complex, and taking the duration of the QRS complex as the mutation duration of the heart rate mutation features;

Obtaining mutation occurrence frequency for the occurrence frequency of the overlong period and the overlong period of the abnormal period sequence in the mutation duration;

extracting gradient parameters from the periodic gradient characteristics to obtain gradient rate;

Judging whether the gradual change rate of the periodic gradual change feature is overlong or not;

If not, judging that the heart monitoring data collected by the target patient is normal;

if yes, further judging whether mutation occurs in the mutation occurrence frequency monitored in the state of overlong gradual change rate;

if not, judging that the heart monitoring data acquired by the target patient is abnormal, and enabling the target patient to have chronic heart diseases;

if yes, judging that the heart monitoring data acquired by the target patient is abnormal, and the target patient has acute heart diseases.

9. The patient health early warning processing system for various cardiac monitoring data is characterized by comprising an acquisition module, an analysis module, an early warning module and a data processing module, wherein the acquisition module is used for acquiring various cardiac monitoring data;

the acquisition module is used for acquiring heart monitoring data of a target patient, and preprocessing the sampling frequency and the waveform of the heart monitoring data to obtain an electrocardiogram signal;

The analysis module is used for confirming a starting point of a waveform and an ending point of the waveform of the electrocardiogram signal, searching waveform trend inflection points by utilizing the starting point of the waveform and the ending point of the waveform, extracting heart rate mutation features according to the waveform trend inflection points, and identifying the heart rate mutation features to output an evaluation result of heart health risk symptoms;

The early warning module is used for early warning according to the evaluation result of the heart health risk symptoms.