阅读说明：本技术 一种报警切换方法 (Alarm switching method ) 是由 叶志刚 刘畅 顾煜 刘建斌 潘海洋 于 2020-05-12 设计创作，主要内容包括：本发明实施例涉及一种报警切换方法,所述方法包括：获取第一ECG数据；根据第一数量阈值和第一ECG数据,进行心搏间期差值数据序列系数计算处理,生成第一系数；当第一系数超出一级报警系数阈值时,进行一级报警处理；获取第二ECG数据；根据第一数量阈值和第二ECG数据,进行心搏间期差值数据序列系数计算处理,生成第二系数；当第二系数超出一级报警系数阈值时,根据第二数量阈值和第二ECG数据,进行心搏间期差值数据序列系数计算处理,生成第三系数；当第三系数超出二级报警系数阈值时,进行二级报警处理。本发明解决了常规心电监护设备不能自动切换报警级别的问题,增强了心电监护设备的自适应报警能力。(The embodiment of the invention relates to an alarm switching method, which comprises the following steps: acquiring first ECG data; performing an interval difference data sequence coefficient calculation process based on the first quantity threshold and the first ECG data to generate a first coefficient; when the first coefficient exceeds a first-level alarm coefficient threshold value, performing first-level alarm processing; acquiring second ECG data; performing an interval difference data sequence coefficient calculation process based on the first quantity threshold and the second ECG data to generate a second coefficient; when the second coefficient exceeds the primary alarm coefficient threshold, calculating the interval difference data sequence coefficient according to the second quantity threshold and the second ECG data to generate a third coefficient; and when the third coefficient exceeds the threshold value of the secondary alarm coefficient, performing secondary alarm processing. The invention solves the problem that the conventional electrocardiogram monitoring equipment can not automatically switch the alarm level, and enhances the self-adaptive alarm capability of the electrocardiogram monitoring equipment.)

1. An alarm switching method, characterized in that the method comprises:

acquiring first electrocardiogram ECG data;

performing an interval difference data sequence coefficient calculation process based on a first quantity threshold and the first ECG data to generate a first coefficient;

when the first coefficient is larger than or equal to a first-level alarm coefficient threshold value, performing first-level alarm processing;

acquiring second ECG data;

performing an interval difference data sequence coefficient calculation process based on the first quantity threshold and the second ECG data to generate a second coefficient;

when the second coefficient is larger than or equal to the primary alarm coefficient threshold value, calculating the heart beat interval difference data sequence coefficient according to a second quantity threshold value and the second ECG data to generate a third coefficient; the second quantity threshold is greater than the first quantity threshold;

when the third coefficient is larger than or equal to a secondary alarm coefficient threshold value, performing secondary alarm processing; the secondary alarm coefficient threshold is greater than the primary alarm coefficient threshold.

2. The alarm switching method according to claim 1, wherein the performing an inter-beat interval difference data sequence coefficient calculation process based on a first quantity threshold and the first ECG data to generate a first coefficient specifically comprises:

sequentially extracting QRS complex data from the first ECG data to generate a QRS complex data sequence; the first ECG data comprises a plurality of the QRS complex data; the QRS complex data comprises Q point data, R point data and S point data;

sequentially extracting the R point data of the QRS complex data from the QRS complex data sequence to generate an R point data sequence;

performing absolute difference value calculation processing on the adjacent R point data in the R point data sequence to generate interval of heart beat data, and forming an interval of heart beat data sequence by the interval of heart beat data;

performing absolute difference calculation processing on the adjacent heartbeat interval data in the heartbeat interval data sequence to generate heartbeat interval difference data, and forming the heartbeat interval difference data sequence by the heartbeat interval difference data;

summing the first number of threshold interval difference data at the end of the sequence of interval difference data to generate the first coefficient.

3. The alarm switching method according to claim 1, further comprising:

and when the second coefficient is smaller than the threshold value of the primary alarm coefficient, if the primary alarm processing is still executed, stopping executing the primary alarm processing.

4. The alarm switching method according to claim 1, further comprising:

and when the third coefficient is smaller than the secondary alarm coefficient threshold value, performing primary alarm processing.

5. The alarm switching method according to claim 1, further comprising:

and when the third coefficient is greater than or equal to the secondary alarm coefficient threshold value, before the secondary alarm processing, if the primary alarm processing is still executed, the primary alarm processing is stopped.

6. An electronic device, comprising: a memory, a processor, and a transceiver;

the processor is used for being coupled with the memory, reading and executing the instructions in the memory to realize the method steps of any one of the claims 1-5;

the transceiver is coupled to the processor, and the processor controls the transceiver to transmit and receive messages.

7. A computer program product, characterized in that the computer program product comprises computer program code which, when executed by a computer, causes the computer to perform the method of any of claims 1-5.

8. A computer-readable storage medium having stored thereon computer instructions which, when executed by a computer, cause the computer to perform the method of any of claims 1-5.

Technical Field

The invention relates to the technical field of data processing, in particular to an alarm switching method.

Background

An electrocardiographic monitoring device is a device which can identify abnormal Electrocardiogram (ECG) signals and alarm. ECG signal, with 3 parts of a typical waveform: p-wave, QRS complex (consisting of Q-wave, R-wave, and S-wave), and T-wave. Among them, the QRS complex is the most characteristic waveform, and its higher amplitude (the maximum amplitude point is the R wave peak point, called as R point) makes the QRS complex easier to identify compared with P wave and T wave. In an ECG signal, the time interval of adjacent R points is specifically considered as one cardiac cycle time, called the heart beat interval. A sequence of consecutive inter-beat interval data is referred to as an inter-beat interval data sequence and its differential sequence is an inter-beat interval difference data sequence.

The ECG monitoring device calculates a corresponding heart interval difference data sequence coefficient by using the heart interval difference data sequence, and when the heart interval difference data sequence coefficient exceeds the alarm coefficient threshold value of a set level, the ECG monitoring device considers that the ECG signal is abnormal and alarms according to the level. The conventional ECG monitoring equipment can automatically alarm, but all alarms are independent, and manual operation is required to be relied on when the alarm level is required to be switched up and down.

Disclosure of Invention

The invention aims to provide an alarm switching method, an electronic device and a readable storage medium aiming at the defects of the prior art, solves the problem that the conventional electrocardiogram monitoring device cannot automatically switch the alarm level, and enhances the self-adaptive alarm capability of the electrocardiogram monitoring device.

In order to achieve the above object, a first aspect of the embodiments of the present invention provides an alarm switching method, where the method includes:

acquiring first ECG data;

performing an interval difference data sequence coefficient calculation process based on a first quantity threshold and the first ECG data to generate a first coefficient;

when the first coefficient is larger than or equal to a first-level alarm coefficient threshold value, performing first-level alarm processing;

acquiring second ECG data;

performing an interval difference data sequence coefficient calculation process based on the first quantity threshold and the second ECG data to generate a second coefficient;

when the second coefficient is larger than or equal to the primary alarm coefficient threshold value, calculating the heart beat interval difference data sequence coefficient according to a second quantity threshold value and the second ECG data to generate a third coefficient; the second quantity threshold is greater than the first quantity threshold;

when the third coefficient is larger than or equal to a secondary alarm coefficient threshold value, performing secondary alarm processing; the secondary alarm coefficient threshold is greater than the primary alarm coefficient threshold.

Preferably, the performing a calculation process on an interval difference data sequence coefficient according to a first quantity threshold and the first ECG data to generate a first coefficient specifically includes:

sequentially extracting QRS complex data from the first ECG data to generate a QRS complex data sequence; the first ECG data comprises a plurality of the QRS complex data; the QRS complex data comprises Q point data, R point data and S point data;

sequentially extracting the R point data of the QRS complex data from the QRS complex data sequence to generate an R point data sequence;

performing absolute difference value calculation processing on the adjacent R point data in the R point data sequence to generate interval of heart beat data, and forming an interval of heart beat data sequence by the interval of heart beat data;

performing absolute difference calculation processing on the adjacent heartbeat interval data in the heartbeat interval data sequence to generate heartbeat interval difference data, and forming the heartbeat interval difference data sequence by the heartbeat interval difference data;

summing the first number of threshold interval difference data at the end of the sequence of interval difference data to generate the first coefficient.

Preferably, the method further comprises:

and when the second coefficient is smaller than the threshold value of the primary alarm coefficient, if the primary alarm processing is still executed, stopping executing the primary alarm processing.

Preferably, the method further comprises:

and when the third coefficient is smaller than the secondary alarm coefficient threshold value, performing primary alarm processing.

Preferably, the method further comprises:

and when the third coefficient is greater than or equal to the secondary alarm coefficient threshold value, before the secondary alarm processing, if the primary alarm processing is still executed, the primary alarm processing is stopped.

A second aspect of an embodiment of the present invention provides an electronic device, including: a memory, a processor, and a transceiver;

the processor is configured to be coupled to the memory, read and execute instructions in the memory, so as to implement the method steps of the first aspect;

the transceiver is coupled to the processor, and the processor controls the transceiver to transmit and receive messages.

A third aspect of embodiments of the present invention provides a computer program product comprising computer program code which, when executed by a computer, causes the computer to perform the method of the first aspect.

A fourth aspect of embodiments of the present invention provides a computer-readable storage medium storing computer instructions that, when executed by a computer, cause the computer to perform the method of the first aspect.

The alarm switching method, the electronic device and the readable storage medium provided by the embodiment of the invention solve the problem that the conventional electrocardiogram monitoring device cannot automatically switch the alarm level, and enhance the self-adaptive alarm capability of the electrocardiogram monitoring device.

Drawings

Fig. 1 is a schematic diagram of an alarm switching method according to an embodiment of the present invention;

FIG. 2 is a schematic diagram of an ECG signal provided according to an embodiment of the present invention;

fig. 3 is a schematic diagram of an alarm switching method according to a second embodiment of the present invention;

fig. 4 is a schematic structural diagram of an electronic device according to a third embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention clearer, the present invention will be described in further detail with reference to the accompanying drawings, and it is apparent that the described embodiments are only a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The alarm switching method comprises the steps of firstly obtaining ECG data, and activating a primary alarm when the heart beat interval difference data sequence coefficient of the ECG data exceeds a primary alarm coefficient threshold value; after the primary alarm is executed, the ECG data is continuously acquired and the interval difference data sequence coefficient of the newly acquired ECG data is continuously judged, the alarm is stopped if the interval difference data sequence coefficient is lower than the primary alarm coefficient threshold value, the primary alarm is kept if the interval difference data sequence coefficient is between the primary alarm coefficient threshold value and the secondary alarm coefficient threshold value, and the secondary alarm is activated if the interval difference data sequence coefficient exceeds the primary alarm coefficient threshold value. By using the invention, the alarm can be automatically given if the ECG data is abnormal in the continuous ECG monitoring process, the alarm can be automatically eliminated if the ECG data is abnormal and the alarm can be automatically upgraded if the ECG data is abnormal and aggravated, thereby solving the problem that the conventional ECG monitoring equipment can not automatically switch the alarm level and enhancing the self-adaptive alarm capability of the ECG monitoring equipment.

As shown in fig. 1, which is a schematic diagram of an alarm switching method according to an embodiment of the present invention, the method mainly includes the following steps:

step 1, obtaining first EGG data.

Specifically, the method comprises the following steps: the ECG monitoring device extracts the latest ECG data with a first time length from the ECG continuously acquired data stored in the local cache region at intervals of a first interval, and the latest ECG data is used as first ECG data.

The electrocardiograph monitoring device is specifically a terminal device or a server which meets the functions of the embodiment of the invention; the first interval time is the interval time for acquiring ECG data by the ECG monitoring equipment, the first time length is the time length of the extracted ECG data, and the specific value is set by the ECG monitoring equipment; the ECG continuous acquisition data can be ECG data acquired by the ECG monitoring device, or ECG data acquired by the ECG monitoring device by connecting with other acquisition devices or servers.

For example, if the first interval time is 3 seconds and the first time length is 30 seconds, then: every 3 seconds, the ECG monitoring device extracts a section of latest ECG data with the length of 30 seconds from the ECG continuously acquired data stored in the local cache region, and the extracted data is used as first ECG data.

Step 2, according to a first quantity threshold value and first ECG data, calculating a heart interval difference data sequence coefficient to generate a first coefficient;

the method specifically comprises the following steps: step 21, sequentially extracting QRS complex data from the first ECG data to generate a QRS complex data sequence;

wherein the first ECG data comprises a plurality of QRS complex data; the QRS wave group data comprises Q point data, R point data and S point data;

here, as shown in fig. 2, which is a schematic diagram of an ECG signal according to an embodiment of the present invention, the QRS complex is the most characteristic waveform of the ECG signal, and its higher amplitude (the maximum amplitude point is the R peak point, which is called as the R point) makes the QRS complex easier to identify compared with the P wave and the T wave, so the R point of the QRS complex is generally used as the reference point when identifying the cardiac cycle; before the specific extraction of the R point, the electrocardiogram monitoring equipment firstly extracts a QRS complex from ECG data;

for example, if the first ECG data is a 30 second ECG data segment including M QRS complexes, where M is an integer greater than 0, then the QRS complex data sequence includes M QRS complex data;

step 22, sequentially extracting R point data of QRS complex data from the QRS complex data sequence to generate an R point data sequence;

here, the R point in the QRS complex is the maximum amplitude point, the maximum amplitude point is selected from the QRS complex data sequence as the R point, and the corresponding time data is extracted to obtain R point data;

for example, if the QRS complex data sequence includes M QRS complex data, M R point data sequences can be extracted, where the R point data sequence should be an R point data sequence { R₁，R₂…R_M}; wherein R is₁、R₂By analogy, R_MEach is a specific one of the R point data;

step 23, performing absolute difference value calculation processing on adjacent R point data in the R point data sequence to generate interval of heart beat data, and forming an interval of heart beat data sequence by the interval of heart beat data;

for example, R point data sequence { R }₁，R₂…R_M}, the heart beat interval data sequence should be the heart beat interval data sequence { RR }₁，RR₂…RR_M-1Where RR₁＝abs(R₂-R₁)，RR₂＝abs(R₃-R₂) By analogy, RR_M-₁＝abs(R_M-R_M-1) Respectively, a particular one of the interval of heart beats, where abs () is a function of the absolute value;

step 24, performing absolute difference value calculation processing on adjacent heartbeat interval data in the heartbeat interval data sequence to generate heartbeat interval difference value data, and forming a heartbeat interval difference value data sequence by the heartbeat interval difference value data;

for example, an interval of heart data sequence { RR }₁，RR₂…RR_M-1}, the sequence of interval difference data should be heartBeat interval difference data series [ Delta RR ]₁，ΔRR₂…ΔRR_M-2Where Δ RR₁＝abs(RR₂-RR₁)，ΔRR₂＝abs(RR₃-RR₂) By analogy, Δ RR_M-2＝abs(RR_M-1-RR_M-2) Each being specific one of the interval difference data;

step 25, summing a first number of threshold interval difference data at the end of the interval difference data sequence to generate a first coefficient.

Here, in calculating the interval difference data series coefficient, it is specified that a fixed number of interval difference data are extracted from the end of the interval difference data series for calculation so that the calculated interval difference data series coefficient always reflects the latest change of the heart cycle; the fixed number is typically 30 or 60, indicating that the calculated interval difference data series coefficients are associated with the latest 31 or 61 heart cycles, and may also be modified according to application requirements; the first number threshold is the fixed number;

for example, the sequence of interval difference data is a sequence of interval difference data { Δ RR }₁，ΔRR₂…ΔRR_M-2Where the first number threshold is i, the first coefficient is Δ RR_(M-2)-i+1+ΔRR_(M-2)-i+2+…+ΔRR_(M-2)-i+iWhere i is an integer greater than 0.

And 3, judging whether the first coefficient is greater than or equal to a primary alarm coefficient threshold value, if the first coefficient is less than the primary alarm coefficient threshold value, turning to the step 1, and if the first coefficient is greater than or equal to the primary alarm coefficient threshold value, turning to the step 4.

When people are in a healthy state, the inter-cardiac cycle data are not too different, a default abnormal threshold value exists for the inter-cardiac cycle difference data, and if a plurality of continuous inter-cardiac cycle difference data exceed the abnormal threshold value, an alarm needs to be given; the first coefficient is the sum of the first quantity threshold value interval difference data, the primary alarm coefficient threshold value defaults to a first quantity threshold value x abnormal threshold value, if the first coefficient is larger than or equal to the primary alarm coefficient threshold value, most interval difference data in the first ECG data exceed the abnormal threshold value, and the step 4 is required to be immediately transferred to for primary alarm processing; if the first coefficient is smaller than the first-stage alarm coefficient threshold value, the electrocardiogram monitoring equipment considers that the first-stage alarm bottom limit is not exceeded, the alarm is not started, and the step 1 is continuously returned to obtain the next section of first ECG data.

For example, if the first number threshold i is 30 and the abnormality threshold is 100ms, the primary alarm coefficient threshold is 30 × 100 — 3000ms, if the first coefficient is greater than or equal to 3000, the process goes to step 4 to perform the primary alarm process, and if the first coefficient is less than 3000, the process goes to step 1 to acquire the next segment of first ECG data.

And 4, performing primary alarm processing.

The electrocardiogram monitoring equipment activates a primary alarm processing flow, and the function of automatically alarming abnormal ECG data is realized.

Step 5, acquiring second ECG data.

Specifically, the method comprises the following steps: and the ECG monitoring equipment extracts the latest ECG data with a second time length from the ECG continuous acquisition data stored in the local cache region at intervals of a second interval to be used as second ECG data.

Here, the second interval time is an interval time for acquiring ECG data by the electrocardiograph monitoring device, the second time length is a time length of the extracted ECG data, and the specific value is set by the electrocardiograph monitoring device. Compared with the step 1, the electrocardiogram monitoring equipment may shorten the designated time to accelerate the alarm identification rhythm or increase the length of the extracted data to improve the alarm identification precision, so that the second interval time is less than the first interval time, and the second interval time is greater than the first interval time.

For example, the electrocardiographic monitoring device extracts a section of latest ECG data with a length of 30 seconds from the buffered ECG data as the first ECG data every 3 seconds in step 1, and here, may extract a section of latest ECG data with a length of 60 seconds from the buffered ECG data as the second ECG data every 2 seconds; n QRS complexes are included in the second ECG data, where N is an integer greater than 0.

Step 6, according to the first quantity threshold value and the second ECG data, calculating the heart beat interval difference data sequence coefficient to generate a second coefficient;

the method specifically comprises the following steps: step 61, sequentially extracting QRS complex data from the second ECG data to generate a QRS complex data sequence;

wherein the second ECG data comprises a plurality of QRS complex data; the QRS wave group data comprises Q point data, R point data and S point data;

here, the electrocardiographic monitoring device extracts the QRS complex from the ECG data;

for example, the second ECG data is a 60 second ECG data segment including N QRS complexes;

step 62, sequentially extracting R point data of QRS complex data from the QRS complex data sequence to generate an R point data sequence;

here, because the R point in the QRS complex is the maximum amplitude point, the electrocardiographic monitoring device selects the maximum amplitude point from the QRS complex data sequence as the R point, and extracts the corresponding time data to obtain R point data;

for example, if the second ECG data is a 60 second segment of ECG data including N QRS complexes, N R point data sequences may be extracted, where the R point data sequence is the R point data sequence { R₁，R₂…R_N}; wherein R is₁、R₂By analogy, R_NEach is a specific one of the R point data;

step 63, performing absolute difference value calculation processing on adjacent R point data in the R point data sequence to generate interval of heart beat data, and forming an interval of heart beat data sequence by the interval of heart beat data;

for example, the R point data sequence is the R point data sequence { R }₁，R₂…R_N}, the heart beat interval data sequence should be the heart beat interval data sequence { RR }₁，RR₂…RR_N-1Where RR₁＝abs(R₂-R₁)，RR₂＝abs(R₃-R₂) By analogy, RR_N-1＝abs(R_N-R_N-1) Each specific one of the inter-beat data;

step 64, performing absolute difference calculation processing on adjacent heartbeat interval data in the heartbeat interval data sequence to generate heartbeat interval difference data, and forming a heartbeat interval difference data sequence by the heartbeat interval difference data;

for example, the sequence of interval data is the sequence of interval data { RR }₁，RR₂…RR_N-1} then the sequence of heart beat interval difference data should be a sequence of heart beat interval difference data { Δ RR }₁，ΔRR₂…ΔRR_N-2Where Δ RR₁＝abs(RR₂-RR₁)，ΔRR₂＝abs(RR₃-RR₂) By analogy, Δ RR_N-2＝abs(RR_N-1-RR_N-2) Each being specific one of the interval difference data;

step 65, a first number of threshold interval difference data at the end of the interval difference data sequence is summed to generate a second coefficient.

Here, the calculating of the second coefficient and the calculating of the first coefficient are both performed by extracting a first number of threshold heart interval difference data from the end of the sequence of heart interval difference data, with the difference that the sequence of heart interval difference data for calculating the first coefficient is transformed from the first ECG data and the sequence of heart interval difference data for calculating the second coefficient is transformed from the second ECG data; because the subsequent steps need to perform primary alarm judgment on the second ECG data, and the primary alarm coefficient threshold corresponds to the first quantity threshold and the abnormal threshold, the corresponding second coefficient is calculated by adopting the first quantity threshold.

For example, the sequence of interval difference data is a sequence of interval difference data { Δ RR }₁，ΔRR₂…ΔRR_N-2Where the first number threshold is i, then the second coefficient is Δ RR_(N-2)-i+1+ΔRR_(N-2)-i+2+…+ΔRR_(N-2)-i+iWhere i is an integer greater than 0.

And 7, judging whether the second coefficient is greater than or equal to the primary alarm coefficient threshold value, if the second coefficient is less than the primary alarm coefficient threshold value, turning to the step 1, and if the second coefficient is greater than or equal to the primary alarm coefficient threshold value, turning to the step 8.

Here, if the second coefficient is smaller than the primary alarm coefficient threshold, which indicates that the second ECG data has not exceeded the primary alarm threshold, which indicates that the ECG abnormality of the patient has improved and has fallen below the primary alarm coefficient threshold, the electrocardiograph monitoring device returns to step 1 to receive the next first ECG data, and stops the ongoing primary alarm processing; otherwise, if the second coefficient is greater than or equal to the primary alarm coefficient threshold, indicating that the patient's ECG abnormality has not improved, the next step is to go to step 8 to further process whether the ECG abnormality is worsening and the alarm is escalating. Here, when the electrocardiographic monitoring device returns to step 1, an automatic alarm degradation process is actually completed.

For example, if the first number threshold i is 30 and the abnormality threshold is 100ms, the primary alarm coefficient threshold is 30 x 100 x 3000ms, if the second coefficient is less than 3000, the process goes to step 1 to obtain the next segment of first ECG data, and if the second coefficient is greater than or equal to 3000, the process goes to step 8 to calculate the third coefficient.

Step 8, according to the second quantity threshold and the second ECG data, calculating the heart beat interval difference data sequence coefficient to generate a third coefficient;

wherein the second number threshold is greater than the first number threshold;

the method specifically comprises the following steps: step 81, sequentially extracting QRS complex data from the second ECG data to generate a QRS complex data sequence;

wherein the second ECG data comprises a plurality of QRS complex data; the QRS wave group data comprises Q point data, R point data and S point data;

here, the electrocardiographic monitoring device extracts the QRS complex from the ECG data;

for example, the second ECG data is a 60-second ECG data, which includes N QRS complexes, the electrocardiograph monitoring device extracts N QRS complex data from the ECG data to form a QRS complex data sequence;

step 82, sequentially extracting R point data of QRS complex data from the QRS complex data sequence to generate an R point data sequence;

here, because the R point in the QRS complex is the maximum amplitude point, the electrocardiographic monitoring device selects the maximum amplitude point from the QRS complex data sequence as the R point, and extracts the corresponding time data to obtain R point data;

for example, if the second ECG data is a 60 second segment of ECG data including N QRS complexes, N R point data sequences may be extracted, where the R point data sequence is the R point data sequence { R₁，R₂…R_N}; wherein R is₁、R₂By analogy, R_NEach is a specific one of the R point data;

step 83, performing absolute difference value calculation processing on adjacent R point data in the R point data sequence to generate interval of heart beat data, and forming an interval of heart beat data sequence by the interval of heart beat data;

for example, the R point data sequence is the R point data sequence { R }₁，R₂…R_N}, the heart beat interval data sequence should be the heart beat interval data sequence { RR }₁，RR₂…RR_N-1Where RR₁＝abs(R₂-R₁)，RR₂＝abs(R₃-R₂) By analogy, RR_N-1＝abs(R_N-R_N-1) Each specific one of the inter-beat data;

step 84, performing absolute difference value calculation processing on adjacent heartbeat interval data in the heartbeat interval data sequence to generate heartbeat interval difference value data, and forming the heartbeat interval difference value data sequence by the heartbeat interval difference value data;

for example, the sequence of interval data is the sequence of interval data { RR }₁，RR₂…RR_N-1} then the sequence of heart beat interval difference data should be a sequence of heart beat interval difference data { Δ RR }₁，ΔRR₂…ΔRR_N-2Where Δ RR₁＝abs(RR₂-RR₁)，ΔRR₂＝abs(RR₃-RR₂) By analogy, Δ RR_N-2＝abs(RR_N-1-RR_N-2) Each being specific one of the interval difference data;

step 85, summing a second number of interval difference data of the threshold number at the end of the interval difference data sequence to generate a third coefficient.

Here, the calculation of the third coefficient is performed using a sequence of interval difference data extracted from the second ECG data compared to the calculation of the second coefficient, with the difference that the second coefficient is calculated by extracting a first number of threshold interval difference data from the end of the sequence of interval difference data, and the third coefficient is calculated by extracting a second number of threshold interval difference data from the end of the sequence of interval difference data, where the second number threshold is larger than the first number threshold.

For example, the sequence of interval difference data is a sequence of interval difference data { Δ RR }₁，ΔRR₂…ΔRR_N-2J, the third coefficient is Δ RR, and the second quantity threshold is j_(N-2)-j+1+ΔRR_(N-2)-j+2+…+ΔRR_(N-2)-j+jWhere j is an integer greater than i.

And 9, judging whether the third coefficient is greater than or equal to the secondary alarm coefficient threshold value, if so, turning to the step 4, and if not, turning to the step 10.

Here, at the time of the primary alarm, if the ECG signal of the patient abnormally continues to deteriorate, the abnormal inter-cardiac cycle data in the inter-cardiac cycle difference data sequence also increases, and after increasing to a certain amount, it is considered that the deterioration degree is deepened, and the alarm level needs to be increased; the second-level alarm coefficient threshold value is defaulted to be a second quantity threshold value and an abnormal threshold value, the second quantity threshold value is larger than the first quantity threshold value, and the natural second-level alarm coefficient threshold value is also larger than the first-level alarm coefficient threshold value; a third coefficient is a sum of a second number of threshold interval difference data; if the third coefficient is greater than or equal to the secondary alarm coefficient threshold, it indicates that more inter-beat interval difference data in the second ECG data exceed the abnormal threshold, and the step 10 needs to be immediately switched to for secondary alarm; and if the third coefficient is smaller than the secondary alarm coefficient threshold value, the monitoring equipment considers that the secondary alarm lower limit is not exceeded, and then the step 4 is returned to continue to keep primary alarm. Here, when the step 10 is switched to perform the secondary alarm, the electrocardiographic monitoring device completes the process of upgrading the primary automatic alarm.

For example, if the second number threshold j is 60 and the anomaly threshold is 100ms, the secondary alarm coefficient threshold is 60 × 100 — 6000ms, if the third coefficient is greater than or equal to 6000, the process goes to step 10 to perform the secondary alarm process, and if the third coefficient is less than 6000, the process goes to step 4 to continue the primary alarm process.

And step 10, performing secondary alarm processing.

Here, the electrocardiograph monitoring device raises the current alarm level from one level to two levels. After the second-level alarm processing is executed, the method can be circularly used for continuously processing the conditions of three-level, four-level, five-level, analogized in turn, and the like of multi-level automatic lifting.

The alarm switching method in the second embodiment of the invention is different from the first embodiment in that the second coefficient and the third coefficient are not obtained by separate calculation.

As shown in fig. 3, which is a schematic diagram of an alarm switching method provided in the second embodiment of the present invention, the method mainly includes the following steps:

step 101, first ECG data is acquired.

Specifically, the method comprises the following steps: the ECG monitoring device extracts the latest ECG data with a first time length from the ECG continuously acquired data stored in the local cache region at intervals of a first interval, and the latest ECG data is used as first ECG data.

Here, the first interval time is an interval time for acquiring ECG data by the electrocardiograph monitoring device, the first time length is a time length of the extracted ECG data, and the specific value is set by the electrocardiograph monitoring device.

For example, if the first interval time is 3 seconds and the first time length is 30 seconds, then: every 3 seconds, the ECG monitoring device extracts a section of latest ECG data with the length of 30 seconds from the ECG continuously acquired data stored in the local cache region, and the extracted data is used as first ECG data.

Step 102, according to a first quantity threshold value and first ECG data, calculating an interval difference data sequence coefficient to generate a first coefficient;

the method specifically comprises the following steps: step 1021, sequentially extracting QRS complex data from the first ECG data to generate a QRS complex data sequence;

wherein the first ECG data comprises a plurality of QRS complex data; the QRS wave group data comprises Q point data, R point data and S point data;

here, as shown in fig. 2, the QRS complex is the most characteristic waveform in the ECG signal, and its higher amplitude (the maximum amplitude point is the R peak point, which is called as the R point) makes the QRS complex easier to identify compared with the P wave and the T wave, so the R point of the QRS complex is generally used as the reference point when identifying the cardiac cycle; before the specific extraction of the R point, the electrocardiogram monitoring equipment firstly extracts a QRS complex from ECG data;

for example, if the first ECG data is a 30 second ECG data segment including M QRS complexes, where M is an integer greater than 0, then the QRS complex data sequence includes M QRS complex data;

step 1022, sequentially extracting R point data of QRS complex data from the QRS complex data sequence, and generating an R point data sequence;

here, the R point in the QRS complex is the maximum amplitude point, the maximum amplitude point is selected from the QRS complex data sequence as the R point, and the corresponding time data is extracted to obtain R point data;

for example, if the QRS complex data sequence includes M QRS complex data, M R point data sequences can be extracted, where the R point data sequence should be an R point data sequence { R₁，R₂…R_M}; wherein R is₁、R₂By analogy, R_MEach is a specific one of the R point data;

1023, performing absolute difference value calculation processing on adjacent R point data in the R point data sequence to generate interval data, and forming an interval data sequence by the interval data;

for example, R point data sequence { R }₁，R₂…R_M}, the heart beat interval data sequence should be the heart beat interval data sequence { RR }₁，RR₂…RR_M-1} of whichMiddle RR₁＝abs(R₂-R₁)，RR₂＝abs(R₃-R₂) By analogy, RR_M-1＝abs(R_M-R_M-1) Respectively, a particular one of the interval of heart beats, where abs () is a function of the absolute value;

step 1024, performing absolute difference calculation processing on adjacent heartbeat interval data in the heartbeat interval data sequence to generate heartbeat interval difference data, and forming a heartbeat interval difference data sequence by the heartbeat interval difference data;

for example, an interval of heart data sequence { RR }₁，RR₂…RR_M-1} then the sequence of heart beat interval difference data should be a sequence of heart beat interval difference data { Δ RR }₁，ΔRR₂…ΔRR_M-2Where Δ RR₁＝abs(RR₂-RR₁)，ΔRR₂＝abs(RR₃-RR₂) By analogy, Δ RR_M-2＝abs(RR_M-1-RR_M-2) Each being specific one of the interval difference data;

step 1025 sums a first number of threshold interval difference data at the end of the interval difference data sequence to generate a first coefficient.

Here, in calculating the interval difference data series coefficient, it is specified that a fixed number of interval difference data are extracted from the end of the interval difference data series for calculation so that the calculated interval difference data series coefficient always reflects the latest change of the heart cycle; the fixed number is typically 30 or 60, indicating that the calculated interval difference data series coefficients are associated with the latest 31 or 61 heart cycles, and may also be modified according to application requirements; the first number threshold is the fixed number;

for example, the sequence of interval difference data is a sequence of interval difference data { Δ RR }₁，ΔRR₂…ΔRR_M-2Where the first number threshold is i, the first coefficient is Δ RR_(M-2)-i+1+ΔRR_(M-2)-i+2+…+ΔRR_(M-2)-i+iWhere i is an integer greater than 0.

Step 103, judging whether the first coefficient is larger than or equal to a primary alarm coefficient threshold value, if the first coefficient is smaller than the primary alarm coefficient threshold value, turning to step 101, and if the first coefficient is larger than or equal to the primary alarm coefficient threshold value, turning to step 104.

When people are in a healthy state, the inter-cardiac cycle data are not too different, a default abnormal threshold value exists for the inter-cardiac cycle difference data, and if a plurality of continuous inter-cardiac cycle difference data exceed the abnormal threshold value, an alarm needs to be given; the first coefficient is the sum of the first quantity threshold value interval difference data, the primary alarm coefficient threshold value defaults to a first quantity threshold value x abnormal threshold value, if the first coefficient is larger than or equal to the primary alarm coefficient threshold value, most interval difference data in the first ECG data exceed the abnormal threshold value, and the step 104 needs to be immediately carried out for primary alarm processing; if the first coefficient is smaller than the first-level alarm coefficient threshold value, the monitoring device considers that the first-level alarm bottom limit is not exceeded, the alarm is not started, and the step 101 is continuously returned to obtain the next section of first ECG data.

For example, if the first number threshold i is 30 and the abnormality threshold is 100ms, the primary alarm coefficient threshold is 30 × 100 — 3000ms, if the first coefficient is greater than or equal to 3000, the process goes to step 104 to perform the primary alarm process, and if the first coefficient is less than 3000, the process goes to step 101 to acquire the next segment of first ECG data.

And 104, performing primary alarm processing.

The electrocardiogram monitoring equipment activates a primary alarm processing flow, and the function of automatically alarming abnormal ECG data is realized.

Step 105, second ECG data is acquired.

Specifically, the method comprises the following steps: and the ECG monitoring equipment extracts the latest ECG data with a second time length from the ECG continuous acquisition data stored in the local cache region at intervals of a second interval to be used as second ECG data.

Here, the second interval time is an interval time for acquiring ECG data by the electrocardiograph monitoring device, the second time length is a time length of the extracted ECG data, and the specific value is set by the electrocardiograph monitoring device. Compared with the step 101, the electrocardiograph monitoring device may shorten the designated time to accelerate the alarm recognition rhythm or increase the length of the extracted data to improve the alarm recognition accuracy, so that the second interval time is less than the first interval time, and the second interval time is greater than the first interval time.

For example, in step 1, the electrocardiograph device extracts a latest ECG data with a length of 30 seconds from the buffered ECG data every 3 seconds as the first ECG data, and here, may extract a latest ECG data with a length of 60 seconds from the buffered ECG data every 2 seconds as the second ECG data; n QRS complexes are included in the second ECG data, where N is an integer greater than 0.

Step 106, according to the first quantity threshold, the second quantity threshold and the second ECG data, calculating the heart beat interval difference data sequence coefficient to generate a second coefficient and a third coefficient;

wherein the second number threshold is greater than the first number threshold;

the method specifically comprises the following steps: step 1061, sequentially extracting QRS complex data from the second ECG data to generate a QRS complex data sequence;

wherein the second ECG data comprises a plurality of QRS complex data; the QRS wave group data comprises Q point data, R point data and S point data;

here, the electrocardiographic monitoring device extracts the QRS complex from the ECG data;

for example, the second ECG data is a 60-second ECG data, which includes N QRS complexes, the electrocardiograph monitoring device extracts N QRS complex data from the ECG data to form a QRS complex data sequence;

step 1062, sequentially extracting R point data of QRS complex data from the QRS complex data sequence to generate an R point data sequence;

here, because the R point in the QRS complex is the maximum amplitude point, the electrocardiographic monitoring device selects the maximum amplitude point from the QRS complex data sequence as the R point, and extracts the corresponding time data to obtain R point data;

for example, the second ECG data is a 60 second ECG data segment including N QRS wavesGroup, N R point data sequences can be extracted, and the R point data sequence should be an R point data sequence { R }₁，R₂…R_N}; wherein R is₁、R₂By analogy, R_NEach is a specific one of the R point data;

step 1063, performing absolute difference value calculation processing on adjacent R point data in the R point data sequence to generate interval data, and forming an interval data sequence by the interval data;

for example, the R point data sequence is the R point data sequence { R }₁，R₂…R_N}, the heart beat interval data sequence should be the heart beat interval data sequence { RR }₁，RR₂…RR_N-1Where RR₁＝abs(R₂-R₁)，RR₂＝abs(R₃-R₂) By analogy, RR_N-1＝abs(R_N-R_N-1) Each specific one of the inter-beat data;

step 1064, performing absolute difference value calculation processing on adjacent heartbeat interval data in the heartbeat interval data sequence to generate heartbeat interval difference value data, and forming a heartbeat interval difference value data sequence by the heartbeat interval difference value data;

for example, the sequence of interval data is the sequence of interval data { RR }₁，RR₂…RR_N-1} then the sequence of heart beat interval difference data should be a sequence of heart beat interval difference data { Δ RR }₁，ΔRR₂…ΔRR_N-2Where Δ RR₁＝abs(RR₂-RR₁)，ΔRR₂＝abs(RR₃-RR₂) By analogy, Δ RR_N-2＝abs(RR_N-1-RR_N-2) Each being specific one of the interval difference data;

step 1065, summing the first number of threshold interval difference data at the end of the interval difference data sequence to generate a second coefficient;

here, the calculating of the second coefficient and the calculating of the first coefficient are both performed by extracting a first number of threshold heart interval difference data from the end of the sequence of heart interval difference data, with the difference that the sequence of heart interval difference data for calculating the first coefficient is transformed from the first ECG data and the sequence of heart interval difference data for calculating the second coefficient is transformed from the second ECG data; in the subsequent steps, the first-level alarm judgment is carried out on the second ECG data, and the first-level alarm coefficient threshold corresponds to a first quantity threshold value and an abnormal threshold value, so that the corresponding second coefficient is calculated by adopting the first quantity threshold value;

for example, the sequence of interval difference data is a sequence of interval difference data { Δ RR }₁，ΔRR₂…ΔRR_N-2Where the first number threshold is i, then the second coefficient is Δ RR_(N-2)-i+1+ΔRR_(N-2)-i+2+…+ΔRR_(N-2)-i+iWhere i is an integer greater than 0;

step 1066, summing the second number of interval difference data with the threshold value at the end of the interval difference data sequence to generate a third coefficient.

Here, the calculation of the third coefficient is performed using a sequence of interval difference data extracted from the second ECG data compared to the calculation of the second coefficient, with the difference that the second coefficient is calculated by extracting a first number of threshold interval difference data from the end of the sequence of interval difference data, and the third coefficient is calculated by extracting a second number of threshold interval difference data from the end of the sequence of interval difference data, where the second number threshold is larger than the first number threshold.

For example, the sequence of interval difference data is a sequence of interval difference data { Δ RR }₁，ΔRR₂…ΔRR_P-2J, the third coefficient is Δ RR, and the second quantity threshold is j_(N-2)-j+1+ΔRR_(N-2)-j+2+…+ΔRR_(N-2)-j+jWhere j is an integer greater than i.

Step 107, judging whether the second coefficient is greater than or equal to the primary alarm coefficient threshold, if the second coefficient is less than the primary alarm coefficient threshold, turning to step 101, and if the second coefficient is greater than or equal to the primary alarm coefficient threshold, turning to step 108.

Here, if the second coefficient is smaller than the primary alarm coefficient threshold, which indicates that the second ECG data has not exceeded the primary alarm threshold, which indicates that the ECG abnormality of the patient has improved and has fallen below the primary alarm coefficient threshold, the electrocardiographic monitoring device returns to step 101 to receive the next first ECG data, and stops the ongoing primary alarm processing; otherwise, if the second factor is greater than or equal to the primary alarm factor threshold, indicating that the patient's ECG abnormality has not improved, the process proceeds to step 108 to further process whether the ECG abnormality is worsening and the alarm is escalating. Here, when the electrocardiographic monitoring device returns to step 101, an automatic alarm degradation process is actually completed.

For example, if the first number threshold i is 30 and the abnormality threshold is 100ms, the primary alarm coefficient threshold is 30 × 100 — 3000ms, if the second coefficient is less than 3000, the process goes to step 101 to obtain the next segment of first ECG data, and if the second coefficient is greater than or equal to 3000, the process goes to step 108 to determine the third coefficient.

Step 108, judging whether the third coefficient is larger than or equal to the secondary alarm coefficient threshold value, if the third coefficient is smaller than the secondary alarm coefficient threshold value, turning to step 104, and if the third coefficient is larger than or equal to the secondary alarm coefficient threshold value, turning to step 109.

Here, at the time of the primary alarm, if the ECG signal of the patient abnormally continues to deteriorate, the abnormal inter-cardiac cycle data in the inter-cardiac cycle difference data sequence also increases, and after increasing to a certain amount, it is considered that the deterioration degree is deepened, and the alarm level needs to be increased; the second-level alarm coefficient threshold value is defaulted to be a second quantity threshold value and an abnormal threshold value, the second quantity threshold value is larger than the first quantity threshold value, and the natural second-level alarm coefficient threshold value is also larger than the first-level alarm coefficient threshold value; a third coefficient is a sum of a second number of threshold interval difference data; if the third coefficient is greater than or equal to the secondary alarm coefficient threshold, it indicates that more inter-beat interval difference data in the second ECG data exceed the abnormal threshold, and it is necessary to immediately go to step 109 for secondary alarm; if the third coefficient is less than the threshold value of the secondary alarm coefficient, the monitoring device considers that the secondary alarm lower limit has not been exceeded, and returns to step 104 to continue to maintain the primary alarm. Here, when the step 109 is switched to perform the secondary alarm, the electrocardiographic monitoring device completes the process of upgrading the primary automatic alarm.

For example, if the second number threshold j is 60 and the anomaly threshold is 100ms, the secondary alarm coefficient threshold is 60 × 100 — 6000ms, if the third coefficient is greater than or equal to 6000, the process goes to step 109 to perform the secondary alarm process, and if the third coefficient is less than 6000, the process goes to step 104 to continue the primary alarm process.

And step 109, performing secondary alarm processing.

Here, the electrocardiograph monitoring device raises the current alarm level from one level to two levels. After the second-level alarm processing is executed, the method can be circularly used for continuously processing the conditions of three-level, four-level, five-level, analogized in turn, and the like of multi-level automatic lifting.

Fig. 4 is a schematic structural diagram of an electronic device according to a third embodiment of the present invention. The electronic device may be the aforementioned electrocardiographic monitoring device, or may be a device or server connected to the aforementioned electrocardiographic monitoring device for implementing the method according to the embodiment of the present invention. As shown in fig. 4, the electronic device 400 may include: a processor 41 (e.g., CPU), memory 42, transceiver 43; the transceiver 43 is coupled to the processor 41, and the processor 41 controls the transceiving action of the transceiver 43. Various instructions may be stored in memory 42 for performing various processing functions and implementing the methods and processes provided in the above-described embodiments of the present invention. Preferably, the electronic device according to an embodiment of the present invention may further include: a power supply 44, a system bus 45, and a communication port 46. The system bus 45 is used to implement communication connections between the elements. The communication port 46 is used for connection communication between the electronic device and other peripherals.

The system bus mentioned in fig. 4 may be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus or the like. The system bus may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown, but this does not mean that there is only one bus or one type of bus. The communication interface is used for realizing communication between the database access device and other equipment (such as a client, a read-write library and a read-only library). The Memory may include a Random Access Memory (RAM) and may also include a Non-Volatile Memory (Non-Volatile Memory), such as at least one disk Memory.

The Processor may be a general-purpose Processor, including a central processing unit CPU, a Network Processor (NP), and the like; but also a digital signal processor DSP, an application specific integrated circuit ASIC, a field programmable gate array FPGA or other programmable logic device, discrete gate or transistor logic, discrete hardware components.

It should be noted that the embodiment of the present invention also provides a computer-readable storage medium, which stores instructions that, when executed on a computer, cause the computer to execute the method and the processing procedure provided in the above-mentioned embodiment.

The embodiment of the invention also provides a chip for running the instructions, and the chip is used for executing the method and the processing process provided by the embodiment.

Embodiments of the present invention also provide a program product, which includes a computer program stored in a storage medium, from which the computer program can be read by at least one processor, and the at least one processor executes the methods and processes provided in the embodiments.

According to the alarm switching method, the electronic device and the readable storage medium provided by the embodiment of the invention, first-level alarm is activated by judging whether an inter-beat interval difference data sequence coefficient exceeds a first-level alarm coefficient threshold value; and after the primary alarm is executed, continuously judging the heart beat interval difference data sequence coefficient, stopping alarming if the heart beat interval difference data sequence coefficient is lower than a primary alarm coefficient threshold value, keeping the primary alarm if the heart beat interval difference data sequence coefficient is between the primary alarm coefficient threshold value and a secondary alarm coefficient threshold value, and activating the secondary alarm if the heart beat interval difference data sequence coefficient exceeds the primary alarm coefficient threshold value. The invention solves the problem that the conventional ECG monitoring equipment can not automatically switch the alarm level, and enhances the self-adaptive alarm capability of the ECG monitoring equipment.

Those of skill would further appreciate that the various illustrative components and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the various illustrative components and steps have been described above generally in terms of their functionality in order to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.

The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied in hardware, a software module executed by a processor, or a combination of the two. A software module may reside in Random Access Memory (RAM), memory, Read Only Memory (ROM), electrically programmable ROM, electrically erasable programmable ROM, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are merely exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.