Method and device for recognizing acute myocardial ischemia, wearable electrocardiogram monitoring device

Abstract

The embodiment of the present application relates to the technical field of electrocardio monitoring, and discloses an acute myocardial ischemia identification method and device and a wearable electrocardio monitoring equipment.The method comprises the following steps: detecting whether a real R wave arrives when a microprocessor is triggered by an R wave detector; identifying an ST segment starting point after determining that a real R wave arrives; and performing ST elevation or ST depression identification according to the ST segment starting point; determining whether the ST elevation or ST depression event meets preset conditions when the ST elevation or ST depression event is detected; and outputting a preset warning signal when it is determined that the ST elevation or ST depression event meets the preset conditions, so that the acute myocardial ischemia can be identified in real time and accurately, and the power consumption can be significantly saved and the equipment endurance time can be improved.

Description

Technical Field

[0001] This invention relates to the field of electrocardiogram (ECG) monitoring technology, and more particularly to a method and device for identifying acute myocardial ischemia and a wearable ECG monitoring device. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] Myocardial ischemia refers to a hypoxic state of the myocardium caused by insufficient blood supply from the coronary arteries. The coronary arteries are the main blood vessels supplying the heart, responsible for delivering oxygen and nutrients to the myocardial cells. When the coronary arteries narrow, spasm, become blocked, or have insufficient blood flow, the myocardium cannot receive enough oxygen and nutrients, leading to myocardial ischemia and hypoxia. Acute myocardial ischemia is divided into acute angina and acute myocardial infarction. Angina-type acute myocardial ischemia refers to a sudden coronary artery spasm, resulting in insufficient blood supply to the myocardium and ST segment depression on an electrocardiogram. Persistent angina may trigger an acute myocardial infarction.

[0004] Infarct-type acute myocardial ischemia refers to a sudden blockage of the coronary artery in the myocardium, resulting in ST segment elevation on the electrocardiogram during the acute phase due to lack of blood supply to the myocardium. Persistent acute myocardial infarction can lead to myocardial necrosis, which is a critical condition that seriously endangers human life and health, and is also one of the important causes of sudden death.

[0005] Electrocardiography (ECG) is the primary method for detecting acute myocardial ischemia. Current routine clinical ECG tests require visits to specialized medical institutions, but acute myocardial ischemia is characterized by its sudden and unpredictable nature, making routine clinical ECG tests ineffective in addressing this characteristic.

[0006] Existing conventional portable 24-hour Holter monitors require the ECG data to be played back to a computer and analyzed by a program 24 hours later to provide results for diagnosing acute myocardial ischemia, which cannot meet the requirement of real-time alerts for acute myocardial ischemia.

[0007] like Figure 1 As shown, existing medical-grade wearable motion recorders 101 require wireless communication (such as Bluetooth A) to forward signals to a mobile communication device 102 (such as a mobile phone) for the diagnosis of acute myocardial ischemia via electrocardiogram. The mobile phone then sends the signal to a cloud server 104 via a mobile communication network 103. The cloud server 104 program identifies the signal and provides the result, which is then sent back to the mobile communication device 102 via the mobile communication network 103. In this closed loop of signal flow, many unpredictable influencing factors exist, such as:

[0008] (1) Recorder 101 cannot communicate with mobile phone in real time: If the user does not have a mobile phone or changes in body position and disconnects the Bluetooth communication between the device and the mobile phone, the data of acute myocardial ischemia cannot be sent to the cloud in real time via Bluetooth.

[0009] (2) Communication between mobile phone and WiFi data repeater is not smooth: such as distance, obstacles, etc., which prevent the device data from being effectively sent to the mobile phone and also prevent the real-time transmission of acute myocardial ischemia data to the cloud server.

[0010] (3) Mobile communication network is not smooth: such as taking the subway or other means of transportation, or being far away from the mobile communication base station, which makes it impossible to send acute myocardial ischemia data to the cloud in real time.

[0011] Existing civilian-grade wearable heart rate monitors (such as watch-type devices) can only rely on real-time heart rate to identify common arrhythmias and cannot provide real-time reporting of acute myocardial ischemia.

[0012] Therefore, there is an urgent need to provide a precise and real-time identification method for acute myocardial ischemia in order to improve the treatment outcome for patients. Summary of the Invention

[0013] This invention provides a method and device for identifying acute myocardial ischemia, a wearable electrocardiogram monitoring device and medium. The device uses an R-wave detector to trigger a microprocessor to perform a self-learning algorithm for detecting acute myocardial ischemia. This method can identify acute myocardial ischemia in real time and accurately, while also significantly saving power consumption and increasing the device's battery life.

[0014] In a first aspect, embodiments of the present invention provide a method for identifying acute myocardial ischemia, applied to a wearable electrocardiogram (ECG) monitoring device. The device includes: an R-wave detector, an ECG signal acquisition module, a memory, and a microprocessor. The R-wave detector is connected to ECG electrodes and the microprocessor, and is used to detect R-wave arrival signals, triggering the microprocessor upon detection of an R-wave arrival signal. The microprocessor is also connected to the ECG signal acquisition module and the memory. The ECG signal acquisition module is connected to the ECG electrodes and is used to convert the acquired analog ECG signals into digital ECG signals. The microprocessor acquires the digital ECG signals at a preset sampling frequency and stores the acquired digital ECG signals in the memory. The microprocessor enters sleep mode after completing a set task within a preset period. The identification method is executed by the microprocessor within the preset period, and the method includes:

[0015] When the microprocessor is triggered by the R-wave detector, it detects whether a real R-wave has arrived. When it is determined that a real R-wave has arrived, it identifies the ST segment start point and performs ST elevation or ST depression identification based on the ST segment start point.

[0016] When an ST rise or ST fall event is detected, it is determined whether the ST rise or ST fall event meets a preset condition. When it is determined that the ST rise or ST fall event meets the preset condition, a preset warning signal is output.

[0017] As an embodiment, the method further includes: using the baseline of the electrocardiogram signal as the X-axis, determining the intersection point of the Y-axis and X-axis based on the arrival time of the R wave to establish four quadrants, wherein during ST elevation, the QRS complex electrocardiogram signal is located in the first quadrant, and during ST depression, the QRS complex electrocardiogram signal is located in the fourth quadrant; identifying the ST segment initiation point, including:

[0018] The last maximum signal value of the ECG signal within a preset time interval before and after the R wave arrives at the trigger time is identified as the R wave peak. The position after the R wave peak and in the first quadrant where the absolute value of the first occurrence of the difference value is less than or equal to a preset difference threshold is identified as the starting point of the elevated ST segment. The position after the R wave peak and in the fourth quadrant where the absolute value of the first occurrence of the difference value is less than or equal to a preset difference threshold is identified as the starting point of the depressed ST segment.

[0019] The difference value is the difference between consecutive electrocardiogram (ECG) signal values.

[0020] As an example, the method further includes: using the baseline of the electrocardiogram signal as the X-axis, determining the intersection point of the Y-axis and the X-axis based on the arrival time of the R wave to establish four quadrants, wherein when the ST is elevated, the QRS complex electrocardiogram signal is located in the first quadrant, and when the ST is depressed, the QRS complex electrocardiogram signal is located in the fourth quadrant.

[0021] The step of identifying ST elevation or ST depression based on the starting point of the ST segment includes:

[0022] If all ST segment ECG signals are located in the fourth quadrant, and the phase of the continuous linear pattern corresponding to the ST segment ECG signal remains unchanged and is parallel to the baseline, then it is identified as ST depression.

[0023] If all ST segment ECG signals are located in the first quadrant, and the phase of the continuous linear pattern corresponding to the ST segment ECG signal remains unchanged and is a unidirectional curve, then it is identified as ST elevation.

[0024] Among them, phase invariance refers to the phase of the electrocardiogram signal located in the first or fourth quadrant.

[0025] As an example, the steps for determining whether the phase of the continuous linear pattern corresponding to the ST segment ECG signal located in the fourth quadrant remains unchanged and is parallel to the baseline are as follows:

[0026] The duration during which the difference value of the ECG signal within the ST segment is less than or equal to the difference threshold is greater than or equal to the first duration threshold;

[0027] Or the duration for which the difference value of the ECG signal within the ST segment is less than or equal to the difference threshold is greater than or equal to the first duration threshold, and the algebraic sum of the difference values ​​within the ST segment is less than or equal to the difference sum threshold;

[0028] The steps for determining whether a continuous linear pattern corresponding to an ST segment ECG signal in the first quadrant has an unchanged phase and exhibits a unidirectional curve are as follows:

[0029] The duration for which the difference value of the ECG signal within the ST segment is less than or equal to the difference threshold is greater than or equal to the first duration threshold, or the duration for which the difference value of the ECG signal within the ST segment is less than or equal to the difference threshold is greater than or equal to the first duration threshold and the algebraic sum of the difference values ​​within the ST segment is less than or equal to the difference sum threshold.

[0030] As one embodiment, determining whether the ST rise or ST fall event meets a preset condition includes:

[0031] When ST elevation or ST depression satisfies both the site similarity condition and the area similarity condition, and the duration is greater than the second duration threshold, the ST elevation or ST depression event is determined to meet the preset conditions.

[0032] As an example, the steps for determining whether ST elevation or ST depression meets the site similarity condition are as follows:

[0033] If the offset between the current QRS complex ST segment and the corresponding ST segment of the target QRS complex is less than or equal to a preset offset threshold, then the sites are considered similar. If the proportion of similar sites within the current QRS complex ST segment is greater than or equal to the site similarity ratio threshold, then the ST elevation or ST depression of the current QRS complex is determined to satisfy the site similarity with the ST elevation or ST depression of the target QRS complex.

[0034] The steps for determining whether raising or lowering ST satisfies the area similarity condition are as follows:

[0035] The integral of the envelope corresponding to the ST segment of the QRS group in the first quadrant is taken as the area of ​​the ST segment when ST is raised, and the integral of the envelope corresponding to the ST segment of the QRS group in the fourth quadrant is taken as the area of ​​the ST segment when ST is lowered.

[0036] If the difference between the ST segment area of ​​the current QRS group and the ST segment area of ​​the target QRS group is less than a preset area difference threshold, then it is determined that the ST elevation or ST depression of the current QRS group satisfies the area similarity with the elevation or depression of the target QRS group.

[0037] As an example, the target QRS complex is either a single ST-surge or ST-surge QRS complex or N QRS complexes that satisfy both site similarity and area similarity; N is a natural number greater than 1.

[0038] When there are multiple target QRS groups, the location of the target QRS group is the average of the ST segment locations of the multiple QRS groups at the same time, and the area of ​​the target QRS group is the average of the ST areas of the multiple QRS groups.

[0039] Secondly, embodiments of the present invention provide an acute myocardial ischemia device configured in a wearable electrocardiogram (ECG) monitoring device. The device includes: an R-wave detector, an ECG signal acquisition module, a memory, and a microprocessor. The R-wave detector is connected to ECG electrodes and the microprocessor, and is used to detect R-wave arrival signals, triggering the microprocessor upon detection of an R-wave arrival signal. The microprocessor is also connected to the ECG signal acquisition module and the memory. The ECG signal acquisition module is connected to the ECG electrodes and is used to convert the acquired analog ECG signals into digital ECG signals. The microprocessor acquires the digital ECG signals at a preset sampling frequency and stores the acquired digital ECG signals in the memory. The microprocessor enters sleep mode after completing a preset task within a preset period. The identification method is executed by the microprocessor within the preset period. The device includes:

[0040] The ST elevation or depression identification module is used to detect whether a real R wave has arrived when the microprocessor is triggered by the R wave detector. When it is determined that a real R wave has arrived, the ST segment start point is identified, and ST elevation or ST depression identification is performed according to the ST segment start point.

[0041] An acute myocardial ischemia matching module is used to determine whether a ST elevation or ST depression event meets preset conditions when an ST elevation or ST depression event is detected.

[0042] The alarm module is used to output a preset warning signal when it is determined that the ST rise or ST fall event meets the preset conditions.

[0043] Thirdly, embodiments of the present invention provide a wearable electrocardiogram (ECG) monitoring device, comprising: an R-wave detector, an ECG signal acquisition module, a memory, and a microprocessor; the R-wave detector is connected to ECG electrodes and the microprocessor, and is used to detect R-wave arrival signals, and triggers the microprocessor when an R-wave arrival signal is detected; the microprocessor is also connected to the ECG signal acquisition module and the memory, the ECG signal acquisition module is connected to the ECG electrodes and is used to convert the acquired analog ECG signals into digital ECG signals, the microprocessor acquires the digital ECG signals according to a preset sampling frequency and stores the acquired digital ECG signals in the memory, and the microprocessor enters sleep mode after completing a set task within a preset period; the recognition method is executed by the microprocessor within the preset period, and the microprocessor is used to read the computer program in the memory and implement the acute myocardial ischemia recognition method as described in the first aspect when executing the program.

[0044] Fourthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the acute myocardial ischemia identification method as described in the first aspect.

[0045] Compared with the prior art, the technical solution provided by the embodiments of the present invention has at least the following positive effects:

[0046] In the technical solution of this invention, the microprocessor collects digital electrocardiogram signals at a preset sampling frequency and stores them in a memory. When triggered by an R-wave detector within the sampling period, it immediately executes an acute myocardial ischemia identification task. Since the hardware detection of the R-wave signal by the R-wave detector has low time cost, it can ensure real-time monitoring. The acute myocardial ischemia identification task includes identifying whether a real R-wave signal has arrived. After detecting a real R-wave signal, it identifies the ST segment start point, and then identifies whether ST elevation or ST depression occurs, and whether the ST elevation or ST depression meets preset conditions, such as matching the symptoms of acute myocardial ischemia. When acute myocardial ischemia is identified, a preset warning signal is output to control the alarm. The identification of acute myocardial ischemia can be completed within the sampling period. If ST elevation or ST depression is not identified, the microprocessor enters sleep mode after sampling, which can significantly save power consumption, increase the device's battery life, meet the requirements of long-term real-time and accurate acute myocardial ischemia monitoring, and improve the patient's treatment effect. Attached Figure Description

[0047] Figure 1 This is a schematic diagram of the signal flow structure of an existing acute myocardial ischemia recognition system;

[0048] Figure 2 This is a schematic diagram of the structure of a wearable electrocardiogram monitoring device provided in an embodiment of the present invention;

[0049] Figure 3 A flowchart of an acute myocardial ischemia identification method provided in an embodiment of the present invention;

[0050] Figure 4a An example electrocardiogram of ST-segment elevation acute myocardial ischemia provided in an embodiment of the present invention;

[0051] Figure 4b An example electrocardiogram of ST-segment depression-type acute myocardial ischemia provided in an embodiment of the present invention;

[0052] Figure 4c The R-wave detector identified based on the embodiments of the present invention Figure 4a The corresponding actual R-wave arrival signal on the electrocardiogram;

[0053] Figure 4d The microprocessor modified based on the embodiments of the present invention Figure 4a The corresponding actual R-wave arrival signal on the electrocardiogram;

[0054] Figure 4e The microprocessor modified based on the embodiments of the present invention Figure 4b The corresponding actual R-wave arrival signal on the electrocardiogram;

[0055] Figure 5a This is a structural view of a unidirectional curve of an ST-segment elevation electrocardiogram provided in an embodiment of the present invention;

[0056] Figure 5b for Figure 5a A schematic diagram of the location of the unidirectional curve shown;

[0057] Figure 6a This is a horizontal linear structural view of the ST-suppression type electrocardiogram provided in an embodiment of the present invention;

[0058] Figure 6b for Figure 6a A schematic diagram of the horizontal line-shaped location shown;

[0059] Figure 7 A schematic diagram of the four quadrants provided for embodiments of the present invention;

[0060] Figure 8 This is a schematic diagram of the structure of the R-wave detector of the wearable electrocardiogram monitoring device provided in an embodiment of the present invention;

[0061] Figure 9 This is a schematic diagram of the structure of the acute myocardial ischemia identification device provided in an embodiment of the present invention. Detailed Implementation

[0062] The above embodiments are merely illustrative of the principles and effects of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or alter the above embodiments without departing from the spirit and scope of the present invention. Therefore, all equivalent modifications or alterations made by those skilled in the art without departing from the spirit and technical concept disclosed in the present invention should still be covered by the claims of the present invention.

[0063] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0064] The following description, with reference to the accompanying drawings, outlines an acute myocardial ischemia identification method and apparatus, a wearable electrocardiogram (ECG) monitoring device, and a storage medium according to embodiments of this application. Addressing the issue mentioned in the background art that existing technologies are inadequate for the sudden and unpredictable nature of acute myocardial ischemia, and cannot meet the requirement for real-time identification of acute myocardial ischemia, the inventors propose an acute myocardial ischemia identification method based on a wearable ECG monitoring device. By accurately locating the arrival time of the R wave in the real-time ECG signal, this method accurately identifies ST elevation or ST depression, thereby precisely and in real-time identifying acute myocardial ischemia and improving patient treatment outcomes.

[0065] This application provides a method for identifying acute myocardial ischemia. In this method, when the microprocessor is triggered by an R-wave detector, it detects whether a real R-wave has arrived. If a real R-wave has arrived, it identifies the ST segment initiation point and performs ST elevation or ST depression identification based on the ST segment initiation point. When an ST elevation or ST depression event is detected, it is determined whether the ST elevation or ST depression event meets preset conditions. When the ST elevation or ST depression event meets the preset conditions, a preset warning signal is output. This allows the microprocessor to complete the sampling of ECG signals, correction of R-wave arrival signals, and identification of ST elevation or ST depression events within a preset sampling period, and ultimately complete the identification of acute myocardial ischemia. This achieves real-time and accurate identification of acute myocardial ischemia. Furthermore, the microprocessor can enter sleep mode after completing the acute myocardial ischemia identification task, which can significantly save power consumption, increase battery life, and achieve long-term real-time monitoring.

[0066] Specifically, Figure 3 This is a flowchart illustrating an acute myocardial ischemia identification method provided in Embodiment 1 of this application. This method can be applied to, for example... Figure 2The wearable electrocardiogram (ECG) monitoring device 200 shown is described. The wearable ECG monitoring device 200 may include: an R-wave detector 201, an ECG signal acquisition module 202, a memory 204, and a microprocessor 203. The R-wave detector 201 is connected to the ECG electrodes and the microprocessor 203, and is used to detect the arrival of the R-wave signal, triggering the microprocessor 203 upon detection. The microprocessor 203 is also connected to the ECG signal acquisition module 202 and the memory 204. The ECG signal acquisition module 202 is connected to the ECG electrodes and is used to convert the acquired analog ECG signal into a digital ECG signal. The microprocessor 203 acquires the digital ECG signal according to a preset sampling frequency and stores the acquired digital ECG signal in the memory 204. After completing the set task within a preset period, the microprocessor 203 enters sleep mode. The recognition method is executed by the microprocessor 203 within the preset period. The memory 204 is used to store a computer program; the microprocessor 203 is used to read the computer program in the memory and implement the acute myocardial ischemia recognition method of this application embodiment when executing the program. The acute myocardial ischemia identification method can be executed by an acute myocardial ischemia device provided in the embodiments of this application. The device can be implemented in software and / or hardware and configured in a wearable electrocardiogram monitoring device.

[0067] like Figure 8 As shown, the R-wave detector may include: an ECG amplifier 2011, an R-wave filter 2012, an R-wave half-wave rectifier 2013, an R-wave sample-and-hold circuit 2014, a signal comparator 2015, and two monostable triggers 2016.

[0068] The ECG amplifier 2011 is connected to the ECG lead interface of the wearable ECG monitoring device 200 and is used to amplify the ECG signal before outputting it to the R-wave filter 2012. The R-wave filter 2012 filters the amplified ECG signal and outputs it to the R-wave half-wave rectifier 2013. The R-wave half-wave rectifier 2013 rectifies the filtered ECG signal and outputs it to the input of the signal comparator 2015 and the R-wave sample-and-hold circuit 2014. The R-wave sample-and-hold circuit 2014 samples and holds the rectified ECG signal and outputs it to the reference terminal of the signal comparator 2015 and one of the monostable multivibrators 1026. The output of the signal comparator 2015 is connected to another monostable multivibrator 2016. The two monostable multivibrators 2016 are used to output R-wave arrival pulses to the microprocessor 203, triggering the microprocessor 203 to execute a preset monitoring task.

[0069] The R-wave detector is implemented using hardware circuitry, replacing the microprocessor which uses software to monitor the arrival of R-waves. This reduces time costs, saves microprocessor time resources, allows for more sleep time for the microprocessor, and significantly reduces the overall power consumption of the device, enabling longer monitoring periods with limited power.

[0070] like Figure 3 As shown, the acute myocardial ischemia identification method of this application includes the following steps:

[0071] Step 301: When the microprocessor is triggered by the R-wave detector, it checks whether a real R-wave has arrived. If a real R-wave has arrived, it identifies the ST segment start point and performs ST elevation or ST depression identification based on the ST segment start point.

[0072] The microprocessor 203 has a sampling frequency of 250 Hz and a sampling period of 4 ms. Within each sampling period, the microprocessor performs digital ECG signal acquisition. Upon being triggered by an R-wave trigger, it begins R-wave arrival recognition and correction. After recognizing a genuine R-wave arrival signal, it performs ST-segment elevation and ST-segment depression recognition. Upon ST-segment elevation or ST-segment depression recognition, it continues monitoring the next QRS complex. If a QRS complex lasting for a certain period consistently matches ST-segment elevation or ST-segment depression, it is identified as acute myocardial ischemia, and an alarm signal is output. Simultaneously, the recognition result is recorded in the memory 204. Using the recognition method of this embodiment, the microprocessor 204 can obtain more sleep time after completing the set tasks within each sampling period, significantly saving power. At the same time, it has sufficient time resources to perform acute myocardial ischemia recognition after the R-wave signal arrives.

[0073] Acute myocardial ischemia is mainly characterized by ST segment-specific changes. The ST segment is a relatively flat section after the last peak (or the only peak, such as R-shape or QS-shape) of the QRS complex. The electrocardiogram of acute myocardial ischemia will show changes in the Y-axis (increase or decrease in the electrocardiogram signal value). Only by accurately identifying the ST segment start point (the end of the last peak of the QRS complex) can the morphology and other characteristics of the ST segment be accurately identified.

[0074] In actual electrocardiogram signals, the QRS complex has a variety of morphologies and may contain multiple spikes. The last spike is the true R wave. The hardware R wave detector triggers the microprocessor after detecting the first spike. After being triggered by the R wave detector, the microprocessor will continue to detect and identify the last spike as the true R wave. The microprocessor can use known methods to detect the arrival signal of the true R wave, which will not be elaborated here.

[0075] In this embodiment, the baseline of the electrocardiogram signal is used as the X-axis, and the intersection of the Y-axis and X-axis is determined based on the arrival time of the R wave to establish four quadrants, such as... Figure 7As shown, the Y-axis of a ST-segment elevation ECG signal is determined by the last positive spike, while the Y-axis of a ST-segment depression ECG signal is determined by the last negative spike or inflection point. This ensures that during ST-segment elevation, the QRS complex is located in the first quadrant, and during ST-segment depression, the QRS complex is located in the fourth quadrant. Specifically, the baseline is the isoelectric line of the ECG. The sampling resolution of a digital ECG signal is 8 bits, i.e., 256,128 is the baseline. "Positive" refers to the ECG signal value above the baseline, and "negative" refers to the ECG signal value below the baseline.

[0076] In an electrocardiogram (ECG), the normal ST segment should be horizontal and coincide with the baseline. Theoretically, the ECG signal value (i.e., the Y value) should be equal to 0. When the ST segment Y value deviates from a certain range and has a specific morphological change, such as a unidirectional curve, it is identified as ST elevation. Or, when it is a horizontal line below the baseline, it is identified as ST depression.

[0077] The X-axis range for ST segment measurement is determined based on bioelectrophysiological characteristics. X-axis range = QT - QRS width, where... The unit is seconds. The microprocessor extracts features such as Q, R, S, ST, and T from the sampled ECG signal to obtain the X-axis range.

[0078] Please see Figures 4a-4e As shown, Figure 4a In the ECG, the first QRS complex (R1) is a normal ECG, and the n QRS complexes from R2 to Rn+1 are ST elevation ECGs. Figure 4b In the ECG, the first QRS complex (R1) is a normal ECG, and the n QRS complexes from R2 to Rn+1 are ST depression type ECGs. Figure 4c The timing diagram of the R-wave arrival signal output by the R-wave detector. Figure 4d The timing diagram of the actual R-wave arrival signal after the microprocessor performs R-wave arrival identification and correction again. Figure 4e This is a timing diagram of the actual R-wave arrival signal after the microprocessor performs R-wave arrival identification and correction again. After the microprocessor identifies the actual R-wave arrival signal, it identifies the start point of the ST segment.

[0079] Identifying the ST segment initiation point can specifically include: within a preset time interval before and after the R wave arrives at the trigger moment, such as within 0.06 seconds, identifying the last maximum signal value of the ECG signal as the R wave peak; and identifying the position after the R wave peak, within the first quadrant, where the absolute value of the first occurrence of the difference value is less than or equal to a preset difference threshold, as the initiation point of an elevated ST segment; and identifying the position after the R wave peak, within the fourth quadrant, where the absolute value of the first occurrence of the difference value is less than or equal to a preset difference threshold, as the initiation point of a depressed ST segment; wherein, the difference value is the difference between adjacent ECG signal values. The preset difference threshold is, for example, the amplitude of the ECG signal corresponding to 1 unit sampling resolution.

[0080] Please see Figures 5a-5b As shown in 6a to 6b, Figure 5a ST elevation type electrocardiogram Figure 5b This is a schematic diagram of the ST-segment elevation electrocardiogram (STEMI). Figure 6a This is an ST-suppression type electrocardiogram. Figure 6b This is a schematic diagram of the location of ST depression in an electrocardiogram.

[0081] ST-segment elevation or ST-segment depression identification based on the ST-segment initiation point may include: if the ST-segment ECG signals are all located in the fourth quadrant, and the phase of the continuous line corresponding to the ST-segment ECG signals remains unchanged and is parallel to the baseline, then it is identified as ST-segment depression; if the ST-segment ECG signals are all located in the first quadrant, and the phase of the continuous line corresponding to the ST-segment ECG signals remains unchanged and is a unidirectional curve, then it is identified as ST-segment elevation; wherein, "phase unchanged" refers to the phase of the ECG signals located in the first or fourth quadrant.

[0082] The steps for determining whether the phase of the continuous linear pattern corresponding to the ST segment ECG signal in the fourth quadrant remains unchanged and is parallel to the baseline are as follows: the duration for which the difference value of the ECG signal in the ST segment is less than or equal to the difference threshold is greater than or equal to the first duration threshold, or the duration for which the difference value of the ECG signal in the ST segment is less than or equal to the difference threshold is greater than or equal to the first duration threshold and the algebraic sum of the difference values ​​in the ST segment is less than or equal to the difference sum threshold.

[0083] The steps for determining whether a continuous linear pattern corresponding to an ST segment ECG signal in the first quadrant has an unchanged phase and exhibits a unidirectional curve are as follows:

[0084] The duration for which the difference value of the ECG signal within the ST segment is less than or equal to the difference threshold is greater than or equal to the first duration threshold, or the duration for which the difference value of the ECG signal within the ST segment is less than or equal to the difference threshold is greater than or equal to the first duration threshold and the algebraic sum of the difference values ​​within the ST segment is less than or equal to the difference sum threshold. The first duration threshold is, for example, 0.16 seconds, the difference sum threshold is, for example, 5, and the difference threshold is, for example, 1; no specific restrictions are imposed here.

[0085] Step 301: When an ST rise or ST fall event is detected, determine whether the ST rise or ST fall event meets the preset conditions. When it is determined that the ST rise or ST fall event meets the preset conditions, output a preset warning signal.

[0086] Determining whether a ST elevation or ST depression event meets preset conditions may include: when the ST elevation or ST depression meets both site similarity and area similarity conditions and its duration exceeds a second duration threshold, the ST elevation or ST depression event is considered to meet the preset conditions. The second duration threshold is, for example, 20 seconds; that is, when the continuous duration of a ST elevation or ST depression event exceeds 20 seconds, acute myocardial ischemia can be considered to have occurred. It is understood that the second duration threshold can be other suitable values, and no excessive restrictions are imposed here.

[0087] The steps for determining whether ST elevation or ST depression meets the site similarity condition are as follows: If the offset between the current QRS complex's ST segment and the target QRS complex's ST segment at the same position is less than or equal to a preset offset threshold, then the sites are considered similar. Furthermore, if the proportion of similar sites within the current QRS complex's ST segment is greater than or equal to a site similarity ratio threshold, then the current QRS complex's ST elevation or ST depression meets the target QRS complex's ST elevation or ST depression condition. The target QRS complex can be a single QRS complex with ST elevation or ST depression, or N QRS complexes that meet both site similarity and area similarity criteria. N is a natural number greater than 1. When there are multiple target QRS complexes, the site of the target QRS complex is the average of the sites in the ST segments of multiple QRS complexes at the same time, and the area of ​​the target QRS complex is the average of the areas in the ST segments of multiple QRS complexes. For example, N can be 8, but this is not specifically limited; for instance, it can also be the average of the areas of all identified similar QRS complexes.

[0088] For example, the preset offset threshold is 3, the site similarity ratio threshold is 75%, and if the absolute value of the difference between the ST segment site of the current QRS complex and the ST segment site of the previous QRS complex is less than or equal to 3, then the ST segment site of the current QRS complex is considered to be similar to the ST segment site of the previous QRS complex. Furthermore, if the ratio of similar sites to the total number of sites within the ST segment is greater than or equal to 75%, then the ST segment of the current QRS complex is considered to be similar to the ST segment curve of the previous QRS complex.

[0089] The steps for determining whether ST elevation or ST depression satisfies the area similarity condition are as follows: The integral of the envelope corresponding to the ST segment of the QRS complex in the first quadrant is taken as the area of ​​the ST segment when ST is elevated; the integral of the envelope corresponding to the ST segment of the QRS complex in the fourth quadrant is taken as the area of ​​the ST segment when ST is depressed. If the difference between the current ST segment area of ​​the QRS complex and the ST segment area of ​​the target QRS complex is less than a preset area difference threshold, then it is determined that the ST elevation or ST depression of the current QRS complex satisfies the area similarity condition with the elevation or depression of the target QRS complex.

[0090] For example, the preset area difference threshold is, for example, 10% of the ST segment area. If the difference between the ST segment area of ​​the current QRS group and the ST segment area of ​​the target QRS group is less than 10%, then it is determined that the ST elevation or ST depression of the current QRS group satisfies the area similarity with the elevation or depression of the target QRS group.

[0091] Compared with the prior art, the embodiments of the present invention involve a microprocessor that collects digital electrocardiogram signals at a preset sampling frequency and stores them in a memory. Within the sampling period, when triggered by an R-wave detector, it immediately executes an acute myocardial ischemia identification task. Because the hardware detection of the R-wave signal by the R-wave detector has low time cost, real-time monitoring can be guaranteed. The acute myocardial ischemia identification task includes identifying whether a real R-wave signal has arrived. After detecting a real R-wave signal, it identifies the ST segment start point, then identifies whether ST elevation or ST depression occurs, and whether the ST elevation or ST depression meets preset conditions, such as matching the symptoms of acute myocardial ischemia. When acute myocardial ischemia is identified, a preset warning signal is output to control the alarm. The identification of acute myocardial ischemia can be completed within the sampling period. If ST elevation or ST depression is not identified, the microprocessor enters sleep mode after sampling, which can significantly save power consumption, increase device battery life, meet the requirements of long-term real-time and accurate acute myocardial ischemia monitoring, and improve patient treatment outcomes.

[0092] Embodiment 2 of the present invention provides an acute myocardial ischemia identification device, configured in such a way as Figure 2 Wearable electrocardiogram (ECG) monitoring devices. For example... Figure 9 As shown, the device 900 includes: an ST elevation or depression recognition module 901, an acute myocardial ischemia matching module 902, and an alarm module 903.

[0093] ST elevation or depression identification module 901 is used to detect whether a real R wave has arrived when the microprocessor is triggered by the R wave detector. When it is determined that a real R wave has arrived, it identifies the ST segment start point and performs ST elevation or ST depression identification based on the ST segment start point.

[0094] The acute myocardial ischemia matching module 902 is used to determine whether the ST elevation or ST depression event meets preset conditions when the ST elevation or ST depression event is detected.

[0095] The alarm module 903 is used to output a preset warning signal when it is determined that the ST raising or ST lowering event meets the preset conditions.

[0096] Optionally, the device 900 may further include: a quadrant establishment module, used to establish four quadrants by taking the baseline of the electrocardiogram signal as the X-axis and determining the intersection point of the Y-axis and the X-axis according to the arrival time of the R wave, wherein when the ST is elevated, the QRS complex electrocardiogram signal is located in the first quadrant, and when the ST is depressed, the QRS complex electrocardiogram signal is located in the fourth quadrant.

[0097] Optionally, the ST elevation or depression recognition module 901 includes an ST start point recognition submodule, used to identify the last maximum signal value of the ECG signal as the R wave peak within a preset time interval before and after the R wave arrives at the trigger time; to identify the position after the R wave peak and located in the first quadrant where the absolute value of the first occurrence of the difference value is less than or equal to a preset difference threshold as the start point of the ST elevation segment; and to identify the position after the R wave peak and located in the fourth quadrant where the absolute value of the first occurrence of the difference value is less than or equal to a preset difference threshold as the start point of the ST depression segment; wherein the difference value is the difference between adjacent ECG signal values.

[0098] ST elevation or depression recognition module 901 includes a depression recognition submodule and an elevation recognition submodule. The depression recognition submodule is used to recognize ST depression if the ST segment ECG signal is located in the fourth quadrant and the phase of the continuous line corresponding to the ST segment ECG signal remains unchanged and is parallel to the baseline.

[0099] The ST segment recognition submodule is used to identify ST segment elevation if all ST segment ECG signals are located in the first quadrant and the phase of the continuous line corresponding to the ST segment ECG signal remains unchanged and is a unidirectional curve; wherein, the phase remains unchanged refers to the phase of the ECG signal located in the first quadrant or the fourth quadrant.

[0100] Optionally, the suppression identification submodule is specifically used to determine, by means of the following steps, that the phase of the continuous linear pattern corresponding to the ST segment ECG signal remains unchanged and is parallel to the baseline: the duration for which the difference value of the ECG signal in the ST segment is less than or equal to the difference threshold is greater than or equal to the first duration threshold, or the duration for which the difference value of the ECG signal in the ST segment is less than or equal to the difference threshold is greater than or equal to the first duration threshold and the algebraic sum of the difference values ​​in the ST segment is less than or equal to the difference sum threshold.

[0101] Optionally, the elevation recognition submodule is specifically used to determine, using the following steps, that the phase of the continuous linear pattern corresponding to the ST segment ECG signal located in the fourth quadrant remains unchanged and is a unidirectional curve: the duration for which the difference value of the ECG signal located in the ST segment of the first quadrant is less than or equal to the difference threshold is greater than or equal to the first duration threshold, or the duration for which the difference value of the ECG signal located in the ST segment of the first quadrant is less than or equal to the difference threshold is greater than or equal to the first duration threshold and the algebraic sum of the difference values ​​in the ST segment is less than or equal to the difference sum threshold.

[0102] Optionally, the acute myocardial ischemia matching module 902 is specifically used to determine whether the ST elevation or ST depression event meets the preset conditions by adopting the following steps: when the ST elevation or ST depression meets the site similarity condition and the area similarity condition and the duration is greater than the second duration threshold, the ST elevation or ST depression event is determined to meet the preset conditions.

[0103] Furthermore, the acute myocardial ischemia matching module 902 is specifically used to determine whether ST elevation or ST depression meets the site similarity condition using the following steps:

[0104] If the offset between the current QRS complex ST segment and the corresponding ST segment of the target QRS complex is less than or equal to a preset offset threshold, then the sites are considered similar. If the proportion of similar sites within the current QRS complex ST segment is greater than or equal to the site similarity ratio threshold, then the ST elevation or ST depression of the current QRS complex is determined to satisfy the site similarity with the ST elevation or ST depression of the target QRS complex.

[0105] Furthermore, the acute myocardial ischemia matching module 902 is specifically used to determine whether ST elevation or ST depression meets the area similarity condition using the following steps:

[0106] The integral of the envelope corresponding to the ST segment of the QRS group in the first quadrant is taken as the area of ​​the ST segment when ST is raised, and the integral of the envelope corresponding to the ST segment of the QRS group in the fourth quadrant is taken as the area of ​​the ST segment when ST is lowered.

[0107] If the difference between the ST segment area of ​​the current QRS group and the ST segment area of ​​the target QRS group is less than a preset area difference threshold, then it is determined that the ST elevation or ST depression of the current QRS group satisfies the area similarity with the elevation or depression of the target QRS group.

[0108] Optionally, the target QRS complex is a single QRS complex with ST elevation or depression, or N QRS complexes that satisfy site similarity and area similarity; N is a natural number greater than 1.

[0109] When there are multiple target QRS groups, the location of the target QRS group is the average of the ST segment locations of the multiple QRS groups at the same time, and the area of ​​the target QRS group is the average of the ST areas of the multiple QRS groups.

[0110] This invention provides a computer-readable storage medium storing a computer program thereon, which, when executed by a computer processor, is used to perform the technical solution of any method embodiment.

[0111] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or grid device, etc.) to execute the methods described in the various embodiments of the present invention.

[0112] It is worth noting that in the embodiments of the above-mentioned device, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be realized; in addition, the specific names of each functional unit are only for easy distinction between each other and are not used to limit the scope of protection of the present invention.

[0113] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A method for identifying acute myocardial ischemia, characterized in that, An application is made in a wearable electrocardiogram (ECG) monitoring device, the device comprising: an R-wave detector, an ECG signal acquisition module, a memory, and a microprocessor; the R-wave detector is connected to ECG electrodes and the microprocessor, and is used to detect R-wave arrival signals, and triggers the microprocessor when an R-wave arrival signal is detected; the microprocessor is also connected to the ECG signal acquisition module and the memory, the ECG signal acquisition module is connected to the ECG electrodes and is used to convert the acquired analog ECG signals into digital ECG signals, the microprocessor acquires the digital ECG signals at a preset sampling frequency and stores the acquired digital ECG signals in the memory, and the microprocessor enters sleep mode after completing a set task within a preset period; the recognition method is executed by the microprocessor within the preset period, and the method includes: When the microprocessor is triggered by the R-wave detector, it detects whether a real R-wave has arrived. When it is determined that a real R-wave has arrived, it identifies the ST segment start point and performs ST elevation or ST depression identification based on the ST segment start point. When an ST rise or ST fall event is detected, it is determined whether the ST rise or ST fall event meets a preset condition. When it is determined that the ST rise or ST fall event meets the preset condition, a preset warning signal is output. The method further includes: using the baseline of the electrocardiogram signal as the X-axis, determining the intersection point of the Y-axis and the X-axis based on the arrival time of the R wave to establish four quadrants, wherein when the ST is elevated, the QRS complex electrocardiogram signal is located in the first quadrant, and when the ST is depressed, the QRS complex electrocardiogram signal is located in the fourth quadrant. Identifying the ST segment start point includes: identifying the last maximum signal value of the ECG signal within a preset time interval before and after the R wave arrives at the trigger time as the R wave peak; identifying the position after the R wave peak, within the first quadrant, where the absolute value of the first occurrence of the difference value is less than or equal to a preset difference threshold, as the start point of the ST segment elevation; and identifying the position after the R wave peak, within the fourth quadrant, where the absolute value of the first occurrence of the difference value is less than or equal to a preset difference threshold, as the start point of the ST segment depression; wherein, the difference value is the difference between adjacent ECG signal values. The step of identifying ST elevation or ST depression based on the ST segment start point includes: if all ST segment ECG signals are located in the fourth quadrant, and the phase of the continuous line corresponding to the ST segment ECG signal remains unchanged and is parallel to the baseline, then it is identified as ST depression; if all ST segment ECG signals are located in the first quadrant, and the phase of the continuous line corresponding to the ST segment ECG signal remains unchanged and is a unidirectional curve, then it is identified as ST elevation; wherein, "phase unchanged" refers to the phase of the ECG signal located in the first or fourth quadrant. The steps for determining whether the phase of the continuous linear pattern corresponding to the ST segment ECG signal in the fourth quadrant remains unchanged and is parallel to the baseline are as follows: the duration for which the difference value of the ECG signal in the ST segment is less than or equal to the difference threshold is greater than or equal to the first duration threshold; or the duration for which the difference value of the ECG signal in the ST segment is less than or equal to the difference threshold is greater than or equal to the first duration threshold and the algebraic sum of the difference values ​​in the ST segment is less than or equal to the difference sum threshold. The steps for determining whether the phase of the continuous linear pattern corresponding to the ST segment ECG signal in the first quadrant is unchanged and is a unidirectional curve are as follows: the duration for which the difference value of the ECG signal in the ST segment is less than or equal to the difference threshold is greater than or equal to the first duration threshold, or the duration for which the difference value of the ECG signal in the ST segment is less than or equal to the difference threshold is greater than or equal to the first duration threshold and the algebraic sum of the difference values ​​in the ST segment is less than or equal to the difference sum threshold. Determining whether the ST elevation or ST depression event meets the preset conditions includes: determining that the ST elevation or ST depression event meets the preset conditions when the ST elevation or ST depression meets the site similarity condition and the area similarity condition and the duration is greater than the second duration threshold.

2. The method for identifying acute myocardial ischemia according to claim 1, characterized in that, The steps for determining whether ST elevation or ST depression meets the site similarity criteria are as follows: If the offset between the current QRS complex ST segment and the corresponding ST segment of the target QRS complex is less than or equal to a preset offset threshold, then the sites are considered similar. If the proportion of similar sites within the current QRS complex ST segment is greater than or equal to the site similarity ratio threshold, then the ST elevation or ST depression of the current QRS complex is determined to satisfy the site similarity with the ST elevation or ST depression of the target QRS complex. The steps for determining whether raising or lowering ST satisfies the area similarity condition are as follows: The integral of the envelope corresponding to the ST segment of the QRS group in the first quadrant is taken as the area of ​​the ST segment when ST is raised, and the integral of the envelope corresponding to the ST segment of the QRS group in the fourth quadrant is taken as the area of ​​the ST segment when ST is lowered. If the difference between the ST segment area of ​​the current QRS group and the ST segment area of ​​the target QRS group is less than a preset area difference threshold, then it is determined that the ST elevation or ST depression of the current QRS group satisfies the area similarity with the elevation or depression of the target QRS group.

3. The method for identifying acute myocardial ischemia according to claim 2, characterized in that, The target QRS complex is either a single QRS complex with ST elevation or depression, or N QRS complexes that satisfy both site similarity and area similarity; N is a natural number greater than 1. When there are multiple target QRS groups, the location of the target QRS group is the average of the ST segment locations of the multiple QRS groups at the same time, and the area of ​​the target QRS group is the average of the ST areas of the multiple QRS groups.

4. An acute myocardial ischemia identification device, characterized in that, A wearable electrocardiogram (ECG) monitoring device is configured to include: an R-wave detector, an ECG signal acquisition module, a memory, and a microprocessor. The R-wave detector is connected to ECG electrodes and the microprocessor, and is used to detect R-wave arrival signals, triggering the microprocessor upon detection of an R-wave arrival signal. The microprocessor is also connected to the ECG signal acquisition module and the memory. The ECG signal acquisition module is connected to the ECG electrodes and is used to convert the acquired analog ECG signals into digital ECG signals. The microprocessor acquires the digital ECG signals at a preset sampling frequency and stores the acquired digital ECG signals in the memory. The microprocessor enters sleep mode after completing a set task within a preset period. The device includes: The ST elevation or depression identification module is used to detect whether a real R wave has arrived when the microprocessor is triggered by the R wave detector. When it is determined that a real R wave has arrived, the ST segment start point is identified, and ST elevation or ST depression identification is performed according to the ST segment start point. An acute myocardial ischemia matching module is used to determine whether a ST elevation or ST depression event meets preset conditions when an ST elevation or ST depression event is detected. The alarm module is used to output a preset warning signal when it is determined that the ST rise or ST fall event meets the preset conditions; The device further includes: a quadrant establishment module, used to establish four quadrants by taking the baseline of the electrocardiogram signal as the X-axis and determining the intersection point of the Y-axis and the X-axis according to the arrival time of the R wave, wherein when the ST is elevated, the QRS complex electrocardiogram signal is located in the first quadrant, and when the ST is depressed, the QRS complex electrocardiogram signal is located in the fourth quadrant. The ST elevation or depression identification module includes an ST start point identification submodule, used to identify the last maximum signal value of the ECG signal as the R-wave peak within a preset time interval before and after the R-wave arrives at the trigger time; and to identify the position after the R-wave peak, in the first quadrant, where the absolute value of the first occurrence of the difference value is less than or equal to a preset difference threshold, as the start point of the ST elevation segment; and to identify the position after the R-wave peak, in the fourth quadrant, where the absolute value of the first occurrence of the difference value is less than or equal to a preset difference threshold, as the start point of the ST depression segment; wherein, the difference value is the difference between adjacent ECG signal values; The ST elevation or depression identification module further includes a depression identification submodule and an elevation identification submodule; the depression identification submodule is used to identify ST depression if the ST segment ECG signal is located in the fourth quadrant and the phase of the continuous line corresponding to the ST segment ECG signal remains unchanged and is parallel to the baseline. The ST segment recognition submodule is used to identify ST segment elevation if all ST segment ECG signals are located in the first quadrant and the phase of the continuous linear pattern corresponding to the ST segment ECG signal remains unchanged and is a unidirectional curve; wherein, unchanged phase refers to the phase of the ECG signal located in the first quadrant or the fourth quadrant. The low-suppression identification submodule is specifically used to determine, using the following steps, that the phase of the continuous linear pattern corresponding to the ECG signal in the ST segment located in the fourth quadrant remains unchanged and is parallel to the baseline: the duration for which the difference value of the ECG signal in the ST segment is less than or equal to the difference threshold is greater than or equal to the first duration threshold, or the duration for which the difference value of the ECG signal in the ST segment is less than or equal to the difference threshold is greater than or equal to the first duration threshold and the algebraic sum of the difference values ​​in the ST segment is less than or equal to the difference sum threshold; The elevation recognition submodule is specifically used to determine, using the following steps, whether the phase of the continuous linear pattern corresponding to the ECG signal in the ST segment of the first quadrant remains unchanged and is a unidirectional curve: the duration for which the difference value of the ECG signal in the ST segment is less than or equal to the difference threshold is greater than or equal to the first duration threshold, or the duration for which the difference value of the ECG signal in the ST segment is less than or equal to the difference threshold is greater than or equal to the first duration threshold and the algebraic sum of the difference values ​​in the ST segment is less than or equal to the difference sum threshold; The acute myocardial ischemia matching module is specifically used to determine whether the ST elevation or ST depression event meets the preset conditions by adopting the following steps: when the ST elevation or ST depression meets the site similarity condition and the area similarity condition and the duration is greater than the second duration threshold, the ST elevation or ST depression event is determined to meet the preset conditions.

5. A wearable electrocardiogram (ECG) monitoring device, characterized in that, include: The system comprises an R-wave detector, an electrocardiogram (ECG) signal acquisition module, a memory, and a microprocessor. The R-wave detector is connected to the ECG electrodes and the microprocessor, and is used to detect the arrival of R-wave signals. The microprocessor is triggered when an R-wave arrival signal is detected. The microprocessor is also connected to the ECG signal acquisition module and the memory. The ECG signal acquisition module is connected to the ECG electrodes and is used to convert the acquired analog ECG signals into digital ECG signals. The microprocessor acquires the digital ECG signals at a preset sampling frequency and stores the acquired digital ECG signals in the memory. The microprocessor enters sleep mode after completing a set task within a preset period. The identification method is executed by the microprocessor within the preset period. The microprocessor reads the computer program in the memory and implements the acute myocardial ischemia identification method as described in any one of claims 1-3 when executing the program.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the acute myocardial ischemia identification method as described in any one of claims 1-3.

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