CN117224131A - Intelligent bracelet, electrocardiosignal detection method, device and medium - Google Patents

Abstract

The present application relates to the field of signal detection, and in particular, to a smart bracelet, an electrocardiogram signal detection method, a device and a medium. The smart bracelet may include: a processor configured to perform the following operations: collect the ECG signal of the wearer; detect whether the wearer's heartbeat is abnormal based on the ECG signal; if the wearer's heartbeat is abnormal, Abnormal ECG segments are determined in the electrical signal and stored. Abnormal ECG segments are segments with abnormal heartbeats in the center of the ECG signal; when a connection to a medical staff terminal device is detected, each stored abnormal ECG segment is , feedback to the medical staff’s terminal equipment. This application has the effect of improving the efficiency of doctors in detecting heart diseases.

Description

A smart bracelet, electrocardiogram signal detection method, device and medium

Technical field

The present application relates to the field of signal detection, and in particular, to a smart bracelet, an electrocardiogram signal detection method, a device and a medium.

Background technique

For electronic watches or bracelets that can detect heart rate, they will be in contact with the human body through the electrode pads on the electronic watch. When the human heart beats, a specific potential difference will be formed on the skin surface. By collecting the potential difference on the skin surface, that is It can capture the waveform of the human heart beating. This heart beating waveform is the ECG signal. The ECG signal can be used to detect the frequency of the human heart beating, that is, the heart rate.

At this stage, for the population, cardiovascular diseases are getting younger and younger, and the incidence of cardiovascular diseases is also increasing. For some cardiovascular diseases, the waveform of the ECG signal can be identified to determine whether there is an abnormality. When an abnormality is detected, timely intervention and treatment can be performed to reduce the risk of cardiovascular disease.

However, at present, ECG signal detection equipment is widely used in hospitals. People need to be tested in the hospital to view the ECG signal. However, the ECG signal detection equipment in hospitals is large and difficult to popularize to meet the public's demand for ECG signals. Testing needs.

When the person's heartbeat becomes abnormal, the person will go to the hospital for medical treatment. The doctor can only collect the ECG signal after the person's arrival and conduct problem analysis based on the collected ECG signal. However, within a period of time after the collection, the ECG signal will not be recovered. The electrical signal may continue to remain at a normal level, or it may be difficult to reproduce the abnormal heartbeat. In order to fully detect and determine the user's condition, doctors often need medical staff to wear detection equipment for a long time to detect whether medical staff are experiencing abnormality over a long period of time. ECG signals make it less efficient for doctors to detect and identify heart diseases, and it is difficult to detect heart problems in medical personnel in a timely manner.

Contents of the invention

In order to improve the efficiency of doctors in detecting heart diseases, this application provides a smart bracelet, an ECG signal detection method, a device and a medium.

In the first aspect, this application provides a smart bracelet that adopts the following technical solution:

A smart bracelet, the smart bracelet includes:

A processor configured to:

Collect the ECG signals of the wearer;

According to the ECG signal, detect whether the heartbeat of the wearer is abnormal;

If the wearer's heartbeat is abnormal, an abnormal ECG segment is determined from the ECG signal and stored. The abnormal ECG segment is an abnormal heartbeat segment in the ECG signal. ;

When a connection with the medical staff terminal device is detected, each stored abnormal ECG segment is fed back to the medical staff terminal device.

By adopting the above technical solution, the smart bracelet is used to monitor and analyze the ECG signal of the wearer in real time to detect whether the ECG signal is abnormal. When the wearer's heartbeat is abnormal, the abnormal ECG fragment is stored. When the ECG signal is detected, When connected to the medical staff's terminal equipment, the stored abnormal ECG fragments are fed back to the medical staff's terminal equipment, so that the medical staff can diagnose the wearer's heart disease based on the wearer's abnormal ECG fragments or can diagnose the heart disease during the diagnosis. This abnormal ECG segment can be referenced at all times, thereby improving the efficiency of doctors in detecting cardiac diseases of the wearer.

In a possible implementation, the processor is configured to determine an abnormal ECG segment from the ECG signal and store the abnormal ECG segment when the wearer's heartbeat is abnormal. In the process, specific implementation:

If the wearer's heartbeat is abnormal, detect whether the wearer is in motion during the abnormal heartbeat period;

If not in motion, detect whether the wearer's emotion is in a stable emotional state;

If the patient is in a stable emotional state, abnormal ECG segments are determined from the ECG signals, and the abnormal ECG segments are stored.

By adopting the above technical solution, when an abnormality occurs, it can be detected whether the wearer is in a state of movement or whether the wearer's mood is in a stable emotional state, so as to eliminate misjudgments caused by whether the abnormality is movement or emotional ups and downs, thereby making the wearer feel calmer. When the electrical signal is abnormal, and the abnormality is not a misjudgment, and the abnormality is not a misjudgment caused by the wearer's emotional ups and downs, the abnormal ECG fragments are determined from the ECG signal and stored, which is beneficial to reducing the risk of heart failure. There is a small chance that ECG abnormalities caused by exercise and adverse emotions will affect the diagnosis of medical staff.

In another possible implementation, the processor is configured to detect whether the wearer is in a state of exercise during the abnormal heartbeat period when the wearer's heartbeat is abnormal, specifically implementing:

When the heartbeat of the wearer is abnormal, obtain the abnormal time when the heartbeat of the wearer is abnormal;

Based on the abnormal time, determine whether the abnormal time is in a preset rest period;

When the abnormal moment is not in the preset rest period, it is detected whether the wearer is in a state of exercise during the abnormal heartbeat period.

By adopting the above technical solution, when detecting whether the wearer is in motion, when the abnormal moment does not appear in the preset rest period, it is then detected whether the wearer is in motion during the abnormal heartbeat period, so that when the non-wearing person does not Judging the wearer's motion status during the rest period will help reduce the chance of misjudgment of the wearer's motion status due to the wearer's actions while resting.

In another possible implementation, the processor is configured to specifically implement: in the process of detecting whether the wearer is in motion during an abnormal heartbeat period:

Obtain the arm vibration information of the wearer during the abnormal heartbeat period, and the arm vibration information is used to characterize the changes in the vibration amplitude of the wearer's arm over time;

Determine the vibration frequency according to the arm vibration information. The vibration frequency is used to represent the frequency of occurrence of a target moment. The target moment is the moment when the vibration amplitude exceeds the preset vibration amplitude threshold;

Detect whether the vibration frequency is greater than a preset frequency to detect whether the wearer is in a state of exercise during abnormal heartbeat.

By adopting the above technical solution, when detecting whether the wearer is in motion, the vibration frequency of the arm during the abnormal heartbeat period can be determined based on the vibration amplitude of the wearer's arm, so that based on the vibration frequency, it can be determined whether the wearer is in the abnormal heartbeat period. In the state of motion, the determination of the state of motion is realized.

In another possible implementation, the processor is configured to specifically implement: during the process of detecting whether the wearer's emotion is in a stable emotional state:

Obtain emotion detection information, and determine whether the wearer's emotion is in a stable emotional state based on the emotion detection information; or,

Obtain emotion detection information, generate and display emotion prompt information based on the emotion detection information; detect whether preset conditions are met to detect whether the wearer's emotion is in a stable emotional state, and the preset conditions include a preset time period A smooth feedback instruction indicating a stable mood is received from the wearer.

By adopting the above technical solution, to detect whether the wearer's emotion is in a stable emotional state, on the one hand, the obtained emotion detection information can be used to determine whether the wearer's emotion is in a stable emotional state; on the other hand, the emotion detection information can also be obtained Finally, based on the stable feedback instructions fed back by the wearer, it is determined whether the wearer's emotion is in a stable emotional state. The feedback of the wearer is used to further determine the wearer's emotion, which can further improve the accuracy of determining the wearer's emotion.

In another possible implementation, the processor is also used to implement the following steps:

An intensity acquisition module, configured to acquire the exercise intensity level of the wearer when it is detected that the wearer is in a state of exercise during an abnormal heartbeat period;

An intensity early warning module, configured to generate intensity early warning information when the exercise intensity level exceeds a preset level, and feedback the intensity early warning information to the wearer's terminal device. The intensity early warning information is used to monitor the wearer's current exercise. Warning for excessive status.

By adopting the above technical solution, when the wearer is in exercise during an abnormal heartbeat period, and when the wearer's exercise intensity level exceeds the preset level, it indicates that the wearer may exercise excessively and may also cause heart disease. By generating intensity warning information , providing an early warning to the wearer of possible excessive exercise, which helps the wearer reduce the range of motion or stop exercise, thereby reducing the chance of heart disease caused by excessive exercise.

In another possible implementation, the processor is configured to specifically implement: during the process of obtaining the exercise intensity level of the wearer:

Based on the arm vibration information, the duration of the exercise is determined, and based on the duration of the exercise, the exercise intensity level of the wearer is determined and obtained.

By adopting the above technical solution, when obtaining the exercise intensity level of the wearer, the duration of exercise can be determined through the arm vibration information, and the exercise intensity level of the wearer can be determined and obtained based on the duration of exercise, thereby achieving the acquisition of the exercise intensity level of the wearer. .

In the second aspect, this application provides a method for detecting ECG signals, adopting the following technical solution:

An electrocardiogram signal detection method, the method includes:

Collect the ECG signals of the wearer;

According to the ECG signal, detect whether the heartbeat of the wearer is abnormal;

When the wearer's heartbeat is abnormal, an abnormal ECG segment is determined from the ECG signal and stored. The abnormal ECG segment is an abnormal heartbeat segment in the ECG signal. ;

When a connection with the medical staff terminal device is detected, each stored abnormal ECG segment is fed back to the medical staff terminal device.

By adopting the above technical solution, the smart bracelet is used to monitor and analyze the ECG signal of the wearer in real time to detect whether the ECG signal is abnormal. When the wearer's heartbeat is abnormal, the abnormal ECG fragment is stored. When the ECG signal is detected, When connected to the medical staff's terminal equipment, the stored abnormal ECG fragments are fed back to the medical staff's terminal equipment, so that the medical staff can diagnose the wearer's heart disease based on the wearer's abnormal ECG fragments or can diagnose the heart disease during the diagnosis. This abnormal ECG segment can be referenced at all times, thereby improving the efficiency of doctors in detecting cardiac diseases of the wearer.

In a possible implementation, if the heartbeat of the wearer is abnormal, determining the abnormal ECG segment from the ECG signal and storing the abnormal ECG segment includes:

If the wearer's heartbeat is abnormal, detect whether the wearer is in motion during the abnormal heartbeat period;

If not in motion, detect whether the wearer's emotion is in a stable emotional state;

If the patient is in a stable emotional state, abnormal ECG segments are determined from the ECG signals, and the abnormal ECG segments are stored.

In another possible implementation, if the heartbeat of the wearer is abnormal, detecting whether the wearer is in motion during the abnormal heartbeat period includes:

If the wearer's heartbeat is abnormal, obtain the abnormal time when the wearer's heartbeat is abnormal;

Based on the abnormal time, determine whether the abnormal time is in a preset rest period;

If the abnormal time is not in the preset rest period, it is detected whether the wearer is in a state of exercise during the abnormal heartbeat period.

In another possible implementation, detecting whether the wearer is in motion during an abnormal heartbeat period includes:

Obtain the arm vibration information of the wearer during the abnormal heartbeat period, and the arm vibration information is used to characterize the changes in the vibration amplitude of the wearer's arm over time;

Determine the vibration frequency according to the arm vibration information. The vibration frequency is used to represent the frequency of occurrence of the target moment. The target moment is the moment when the vibration amplitude exceeds the preset vibration amplitude threshold; detect whether the vibration frequency is greater than the preset frequency. , to detect whether the wearer is in motion during abnormal heartbeat.

In another possible implementation, the detection of whether the wearer's emotion is in a stable emotional state includes any of the following:

Obtain emotion detection information, and determine whether the wearer's emotion is in a stable emotional state based on the emotion detection information;

Obtain emotion detection information, generate and display emotion prompt information based on the emotion detection information; detect whether preset conditions are met to detect whether the wearer's emotion is in a stable emotional state, and the preset conditions include a preset time period A smooth feedback instruction indicating a stable mood is received from the wearer.

In another possible implementation, the method further includes:

If it is detected that the wearer is in a state of exercise during the abnormal heartbeat period, the exercise intensity level of the wearer is obtained;

If the exercise intensity level exceeds the preset level, intensity warning information is generated and fed back to the wearer's terminal device. The intensity warning information is used to warn the wearer of the current excessive exercise state.

In another possible implementation, obtaining the exercise intensity level of the wearer includes:

Based on the arm vibration information, the duration of the exercise is determined, and based on the duration of the exercise, the exercise intensity level of the wearer is determined and obtained.

In the third aspect, this application provides an ECG signal detection device, adopting the following technical solution:

An electrocardiogram signal detection device, including:

Signal acquisition module, used to collect the ECG signal of the wearer;

An abnormality detection module, used to detect whether the heartbeat of the wearer is abnormal based on the ECG signal;

A segment determination module, configured to determine an abnormal ECG segment from the ECG signal when the wearer's heartbeat is abnormal, and store the abnormal ECG segment, where the abnormal ECG segment is the ECG signal. Fragments of abnormal heartbeats in the signal;

The abnormality feedback module is used to feed back each stored abnormal ECG segment to the medical staff terminal equipment when the connection with the medical staff terminal equipment is detected.

In the fourth aspect, this application provides a computer-readable storage medium, adopting the following technical solution:

A computer-readable storage medium includes: a computer program stored therein that can be loaded by a processor and execute the above electrocardiographic signal detection method.

To sum up, this application at least includes the following beneficial technical effects:

By using the smart bracelet to monitor and analyze the wearer's ECG signal in real time to determine whether the ECG signal is abnormal, when the wearer's heartbeat is abnormal, the abnormal ECG fragment is stored. When connected, the stored abnormal ECG fragments are fed back to the medical staff's terminal equipment, so that the medical staff can diagnose the wearer's heart disease based on the wearer's abnormal ECG fragments or refer to the abnormal ECG during diagnosis. fragments, thereby improving doctors' efficiency in detecting heart disease in people who wear them.

Description of drawings

Figure 1 is a schematic structural diagram of a smart bracelet provided by an embodiment of the present application;

Figure 2 is a schematic flow chart of the ECG signal detection method according to the embodiment of the present application;

Figure 3 is a block diagram of an ECG signal detection device according to an embodiment of the present application;

Figure 4 is a schematic structural diagram of another smart bracelet provided by an embodiment of the present application.

Detailed ways

The present application will be further described in detail below in conjunction with Figures 1-4.

In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments These are part of the embodiments of this application, but not all of them. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of this application.

Embodiments of the present application provide a smart bracelet. The smart bracelet has the function of detecting the ECG signal of the wearer. The wearer refers to the person wearing the smart bracelet. The ECG signal is used to represent the body's changes with the cardiac cycle. The waveform of the potential difference at a specific location of the watch represents the heartbeat fluctuation of the wearer. Wherein, as shown in Figure 1, the smart bracelet includes a processor, wherein the processor is configured to perform the steps shown in Figure 2, wherein:

Step S201: Collect the ECG signal of the wearer.

Specifically, when a person wears a smart bracelet, the smart bracelet continuously monitors the wearer's heartbeat fluctuations to detect and collect the wearer's ECG signals in real time.

Step S202: Detect whether the wearer's heartbeat is abnormal based on the ECG signal.

Specifically, when the wearer's heart is abnormal, such as atrial fibrillation, the potential difference waveform generated by the detected heartbeat of the wearer will be different from the normal waveform. Therefore, it can be determined by identifying the ECG signal. Whether the wearer's heartbeat is abnormal, that is, it is judged whether the wearer's heart is abnormal at the current moment.

Among them, in the embodiment of the present application, the method of using the ECG signal of the wearer to identify whether the ECG signal of the wearer is abnormal is a technical means well known to those skilled in the art, and will not be described again here.

Step S203: If the heartbeat of the wearer is abnormal, the abnormal ECG segment is determined from the ECG signal, and the abnormal ECG segment is stored.

Among them, the abnormal ECG segment is an abnormal heartbeat segment in the ECG signal.

Specifically, when an abnormal heartbeat of the wearer is detected, the abnormal ECG segment corresponding to the abnormal heartbeat is determined from the ECG signal. For example, if the wearer has an abnormal heartbeat between 8:00 and 9:00, then 8 The ECG signal corresponding to :00~9:00 is regarded as an abnormal ECG segment, and the abnormal ECG segment is stored.

More specifically, when the wearer has an abnormal heartbeat, it usually occurs at certain times. For example, an ECG signal occurs at 8:15, 8:30, 9:00, 14:00 and 14:30 on the same day. When determining the abnormal ECG segment, specifically, the abnormal period corresponding to each abnormal heartbeat occurrence moment can be determined based on the abnormal heartbeat occurrence moment, and the ECG signal corresponding to the abnormal period corresponding to the abnormal heartbeat occurrence moment can be determined. The segment is determined to be an abnormal ECG segment. For example, when the abnormal heartbeat occurs at 8:15, the ECG signal from 8:14 to 8:16 can be determined as the abnormal ECG segment.

Step S204: When the connection with the medical staff terminal device is detected, each stored abnormal ECG segment is fed back to the medical staff terminal device.

Specifically, the way of detecting the connection with the medical staff's terminal equipment may be to connect the smart bracelet to the terminal equipment, and identify whether the terminal equipment is the terminal equipment of the medical staff. Specifically, when identifying whether the connected terminal device is the terminal device of a medical staff, the identification can be made by detecting whether an ECG data transmission instruction input by the wearer is received.

When the connection with the medical staff's terminal equipment is detected, each abnormal ECG fragment stored is fed back to the medical staff's terminal equipment, so that the medical staff can monitor the wearer based on each abnormal ECG fragment received by the medical staff's terminal equipment. Preliminary diagnosis of electrocardiographic diseases can be carried out to improve the efficiency of doctors in detecting and identifying the heart diseases of the wearers, and to promptly discover the heart problems of the wearers.

Embodiments of the present application provide a smart bracelet that monitors and analyzes the ECG signal of the wearer in real time to determine whether the ECG signal is abnormal. When the heartbeat of the wearer is abnormal, the abnormal ECG fragment is Store it, and when it is detected that it is connected to the medical staff's terminal equipment, the stored abnormal ECG fragments will be fed back to the medical staff's terminal equipment, so that the medical staff can diagnose the wearer's heart disease based on the abnormal ECG fragments of the wearer. The abnormal ECG segment may be referred to during diagnosis, thereby improving the efficiency of doctors in detecting heart disease in the wearer.

One possible implementation of the embodiment of the present application is that the smart bracelet is configured to determine the abnormal ECG segment from the ECG signal and store the abnormal ECG segment in step S103 if the wearer's heartbeat is abnormal. In the process of the steps of the fragment, it can be specifically implemented: if the heartbeat of the wearer is abnormal, it is detected whether the wearer is in a state of exercise during the abnormal heartbeat. If the wearer is not in a state of exercise, it will detect whether the wearer is in a stable emotional state; if the wearer is in a stable emotional state, abnormal ECG segments will be determined from the ECG signal and the abnormal ECG segments will be stored.

Specifically, the abnormal heartbeat period is used to represent the time period consisting of the moments when the heart is abnormal. When the wearer's heartbeat is abnormal, on the one hand, it may be because the wearer is in a state of exercise such as running, walking, or exercising. When in a state of exercise, The ECG signal of the wearer will be affected, so that the detected waveform may be mistaken for abnormalities such as atrial fibrillation, which will affect the correct judgment of whether the heart is abnormal.

Therefore, when an abnormal heartbeat of the wearer is detected, it is necessary to rule out whether the abnormality is caused by the wearer being in motion. Therefore, it is necessary to detect whether the wearer is in motion during the abnormal heartbeat period. When the wearer is in motion, it indicates that the wearer is in motion. The abnormal heartbeat is most likely caused by the movement of the wearer, and no abnormal warning will be issued at this time.

Among them, the method of detecting whether the wearer is in motion during the period of abnormal heartbeat can be determined by the number of exercise steps of the wearer detected by the smart bracelet, and can also be determined by the smart bracelet detecting whether the wearer is sweating. Whether the wearer is in a state of exercise during an abnormal heartbeat can also be determined based on the detected number of exercise steps and whether the wearer is sweating. When the number of exercise steps increases and/or the wearer is sweating, That means the wearer is in motion.

Specifically, when the wearer is in a state of exercise, the abnormality is most likely caused by the wearer's movement; when not in the state of exercise, the abnormality may also be caused by the wearer's intense emotions such as laughing, crying, or being angry. Caused by emotions, therefore, it is also necessary to rule out whether it is caused by the emotions of the wearer. That is, when it is detected that the wearer is not in a state of exercise and an abnormal heartbeat is detected, a misjudgment caused by judging whether the wearer's emotion is in a stable emotional state is determined to determine whether the abnormal heartbeat of the wearer is emotion.

Among them, the method of detecting whether the wearer's emotion is in a stable emotional state may specifically include: obtaining the emotion category information of the wearer. The emotion category information is used to represent the type of the wearer's current emotion, such as anger, crying, Laughter and peace of mind, etc. According to the emotion category information, it is determined whether the emotion category information belongs to a stable emotional state or an intense emotional state, so as to determine whether the wearer's emotion is in a stable emotional state.

The way to obtain the emotional category information of the wearer is to collect the user's physiological data, process and analyze the physiological data to learn the wearer's emotion, and determine the type of the wearer's emotion based on the wearer's emotion. To obtain the emotional category information of the wearer. Among them, the user's physiological data may specifically include the user's body temperature, skin surface humidity, body resistance, slope, state duration changes and other data.

Furthermore, if the wearer is in a stable emotional state, it means that the abnormality in the ECG signal of the wearer is neither an error caused by exercise nor an error caused by the wearer's intense emotions, that is, the wearer's ECG signal at this time is not an error. The ECG signal is most likely to be an abnormal ECG signal caused by abnormalities such as heart disease, such as atrial fibrillation. At this time, abnormal ECG segments will be determined from the ECG signal and stored, which will help reduce the chance that abnormal ECG caused by exercise and adverse emotions will affect the diagnosis of medical staff.

Furthermore, if the wearer is in a stable emotional state, abnormal prompt information can be generated based on the abnormality in the wearer's ECG signal and fed back to the wearer's terminal device.

The wearer's terminal device may specifically be a terminal device that interacts with the smart bracelet, for example, a terminal device connected to the smart bracelet through Bluetooth. The wearer's terminal device can also be other devices communicated and connected with the terminal device that interacts with the smart bracelet. For example, the smart bracelet is connected to terminal device A through Bluetooth and interacts with information. Terminal device A also communicates with terminal device B. If there is a communication connection between users, the wearer's terminal device can be terminal device A or terminal device B. When the wearer's terminal device is another device such as terminal device B, the abnormality prompt information can be sent by the smart bracelet to terminal device A that directly interacts with information, and then sent by terminal device A to terminal device B to notify the abnormality prompt. The information is fed back to the wearer's terminal device.

Specifically, when the wearer is also in a stable emotional state, in order to provide an early warning to the wearer's heart health and instruct the wearer or the wearer's guardian that the wearer's heart is abnormal, it is necessary to check in time and take necessary measures. , which is conducive to timely prevention of cardiac abnormalities of the wearer to improve the physical safety of the wearer.

One possible implementation of the embodiment of the present application is that in the above embodiment, the smart bracelet is configured to perform a process of detecting whether the wearer is in a state of exercise during the abnormal heartbeat period when the wearer's heartbeat is abnormal. Specifically, accomplish:

If the wearer's heartbeat is abnormal, the abnormal time when the wearer's heartbeat is abnormal is obtained. Based on the abnormal time, it is determined whether the abnormal time is within the preset rest period. If the abnormal moment is not within the preset rest period, it is detected whether the wearer is in motion during the abnormal heartbeat period.

Specifically, generally speaking, people usually sleep at night and work and live during the day, or rest during the day and work and live at night. Therefore, when the wearer is resting and the ECG signal is abnormal, there is no need to detect whether the wearer is moving; for some non-resting times, it is necessary to determine whether the wearer is currently moving.

When the wearer's heartbeat is abnormal, the time when the wearer's heartbeat is abnormal is obtained, that is, the abnormal time. For example, when the wearer's heartbeat is abnormal at 12:00, the abnormal time is 12:00.

Specifically, in a possible implementation, the preset rest period may be a rest period determined in advance based on the wearer's work and rest cycle. For example, if the wearer goes to bed at 11pm and gets up at 7am every day, the rest period can be from 11pm to 7am. In another possible implementation, the preset rest time period may also be a rest time period determined after a preset rest duration starting from the moment when the wearer is recognized to start taking a rest, for example, the wearer may take a rest at night. The break starts at 11 o'clock, and the default rest duration is 8 hours, so the default rest time period is from 11 pm to 7 am. The preset rest duration may be based on the average rest duration of the wearer.

When the abnormal moment is in the preset rest period, it means that the wearer is very unlikely to be in motion. When the abnormal moment is not in the preset rest period, it means that the wearer may be in motion. The abnormality that occurs is that the wearer may be in motion. It is more likely to be caused by exercise.

Therefore, when the abnormal moment is not in the preset rest period, it is then detected whether the wearer is in motion during the abnormal heartbeat period. When the abnormal moment is within the preset rest period, the abnormal prompt information can be directly fed back to the wearer's terminal device.

In one possible implementation of the embodiment of the present application, the smart bracelet is also used to detect whether the wearer's emotion is in a stable emotional state if the abnormal moment is in a preset rest period. When in a stable emotional state, based on the abnormality in the wearer's electrocardiogram signal, abnormal prompt information is generated and fed back to the wearer's terminal device.

Specifically, when the abnormal moment is in the preset rest period, it can also be determined whether it is necessary to alert the wearer of the abnormality by detecting whether the wearer's emotion is in a stable emotional state.

More specifically, if the moment when the wearer's heartbeat is abnormal is when the wearer is resting, and the wearer's mood is in a stable emotional state, then the abnormality in the wearer's ECG signal is most likely caused by the wearer's heart disease. If an abnormality occurs, abnormal prompt information will be generated and fed back to the wearer's terminal device so that timely intervention can occur when the wearer's heart is abnormal.

Furthermore, if the wearer's mood is not in a stable emotional state, it means that the wearer's mood is relatively agitated, and if the current moment is a time when heart disease is most common, such as 12 pm to 3 a.m., and the wearer's mood is relatively agitated , it means that although the wearer is resting and emotionally excited at this time, the wearer's emotions are very likely to cause heart problems. Therefore, when the wearer's emotions are not in a stable emotional state and the heart is abnormal, When the abnormal time that occurs is the preset high-incidence time of disease, emotional prompt information is generated to remind the wearer to pay attention to the ups and downs of emotions, so that the wearer can adjust the bad mood in time, so as to reduce the risk of cardiovascular disease induced by the bad mood of the wearer. risk.

A possible implementation of the embodiment of the present application. In the above embodiment, the smart bracelet is configured to detect whether the wearer is in a state of exercise during an abnormal heartbeat. Specifically, the following steps can be implemented: Obtaining Arm vibration information of the wearer during abnormal heartbeat period. Based on the arm vibration information, the vibration frequency is determined. Detect whether the vibration frequency is greater than the preset frequency to detect whether the wearer is in motion during abnormal heartbeat.

Among them, the arm vibration information is used to characterize the changes in vibration amplitude of the wearer's arm over time. The vibration frequency is used to characterize the frequency of occurrence of the target moment, which is the moment when the vibration amplitude exceeds the preset vibration amplitude threshold.

Specifically, the arm vibration information may be a curve in a vibration amplitude-time coordinate system, and the coordinates of each point on the curve are used to represent the vibration amplitude at the corresponding moment.

Specifically, when the wearer is in motion during the period of abnormal heartbeat, the wearer's arm usually vibrates or continues to vibrate. Therefore, when detecting whether the wearer is in motion during the period of abnormal heartbeat, the vibration of the arm can be used To determine, that is, by obtaining the arm vibration information of the wearer during the abnormal heartbeat period to determine whether the wearer is in a state of exercise.

Among them, the specific method of obtaining the vibration information of the wearer's arm during the abnormal heartbeat period may include: installing a vibration sensor on the smart bracelet worn by the wearer, and using the vibration sensor to detect the vibration of the wearer's arm at any time. Vibration amplitude, based on the corresponding relationship between the measured vibration amplitude and time, to obtain arm vibration information, and based on the arm vibration information, determine the arm vibration information of the wearer during the abnormal heartbeat period.

Specifically, when the vibration amplitude of the arm is less than the preset vibration amplitude threshold, it means that the arm's swing amplitude is very small and it is not in motion. When the arm's vibration amplitude is greater than the preset vibration amplitude threshold, it means that the arm's swing amplitude is large. , may be in motion.

That is, when the heartbeat is abnormal, the ratio of the duration during which the arm's vibration amplitude is greater than the preset vibration amplitude threshold to the total duration of the abnormal heartbeat period is determined, and the ratio is determined as the vibration frequency, which represents the The possibility of being in motion during the abnormal heartbeat period. The longer the vibration amplitude of the arm is greater than the preset vibration amplitude threshold, the greater the possibility that the wearer is in motion during the abnormal heartbeat period.

Specifically, the preset frequency is a preset value, for example, the set preset frequency is 50%. When the vibration frequency is greater than the preset frequency, it means that the wearer is in a state of motion during the period of abnormal heartbeat. When the vibration frequency is not greater than the preset frequency, it means that the wearer is in a non-moving state, that is, in a resting state during the period of abnormal heartbeat. In this way, the vibration frequency of the arm during the abnormal heartbeat period can be determined based on the vibration amplitude of the wearer's arm, so that based on the vibration frequency, it can be determined whether the wearer is in a state of motion during the abnormal heartbeat period, thus realizing the determination of the motion state.

One possible implementation manner of the embodiment of the present application. In the above embodiment, the smart bracelet is configured to detect whether the wearer's emotion is in a stable emotional state. Specifically, the following method 1 and method 2 can be implemented. steps, including:

Method 1: Obtain emotion detection information, and detect whether the wearer's emotion is in a stable emotional state based on the emotion detection information.

Among them, the emotion detection information is used to characterize the detected emotion of the wearer.

Specifically, the emotion detection information may be the emotional state determined by the smart bracelet based on the physiological data collected and processed and analyzed. Emotion detection information includes crying, laughing, anger, excitement and peace of mind. When the emotion detection information corresponds to intense states such as crying, laughing, anger, and excitement, it indicates that the wearer's emotion is not in a stable emotional state. When the emotion detection information corresponds to a peaceful state, it indicates that the wearer's emotion is in a stable emotional state. .

Method 2: Obtain emotion detection information, generate and display emotion prompt information based on the emotion detection information; detect whether the preset conditions are met to detect whether the wearer's emotion is in a stable emotional state. The preset conditions include receiving the information within the preset time period. Smooth feedback instructions input by the wearer that represent emotional stability.

Specifically, it detects whether the wearer's emotion is in a stable emotional state, and can also generate emotion prompt information based on the emotion detection information to prompt whether the wearer's state of mind is stable, and detect whether the wearer's emotion is in a stable state based on whether the wearer inputs a stable feedback command. steady state.

More specifically, the emotion prompt information is used to ask whether the wearer's emotional state is a stable emotional state. When the emotion prompt information is generated based on the emotion detection information, when the corresponding emotion in the acquired emotion detection information is a non-stationary emotional state, Emotional prompt information is generated to prompt the wearer whether the current emotion is in a stable emotional state. When the wearer inputs yes, it means that the stable feedback instruction is received, that is, it satisfies the preset conditions, and it means that the wearer's emotion is in a stable emotional state. , when the wearer does not enter the "yes" option within the preset time period, for example, the wearer enters no or the wearer does not enter the "yes" option within the preset time period, it means that the wearer's emotion is in a non-stationary state.

Further, in a possible implementation manner of the embodiment of the present application, the method of detecting whether the wearer's emotion is in a stable emotional state may also include: when the emotion detection information is obtained, prompt information is generated according to the emotion detection information and fed back to In the wearer's terminal device, it is determined whether the wearer's emotion is in a stable emotional state based on the detected feedback instruction of the wearer, the prompt information, and the emotion detection information. The prompt information generated at this time may specifically include asking the wearer whether the current emotion is the detected emotion.

More specifically, the method of determining whether the wearer's emotion is in a stable emotional state based on feedback instructions, prompt information and emotion detection information may include: if no feedback instructions are received within a preset time period, determining whether the wearer is in a stable emotional state based on the emotion detection information. Whether the mood is in a stable emotional state. For example, when the emotion detection information is a stable emotional state, it indicates that the wearer's emotion is a stable emotional state. If a feedback command is received within the preset time period, it is determined whether the wearer's emotion is in a stable emotional state based on the feedback command and prompt information. More specifically, when the emotion detection information corresponds to a non-stationary emotional state, if the wearer selects Yes within the preset time period, the feedback instruction of the detected wearer is the first feedback instruction, indicating that the wearer's emotion is in a non-stationary state; If the wearer chooses No within the preset time period, the feedback instruction from the wearer is the second feedback instruction, which means that the wearer's emotion is in a stable emotional state. If no feedback instruction from the wearer is received within the preset time period, it means that the wearer is in a stable emotional state. The person's mood is in a non-stationary state. When the emotion detection information corresponds to a stable emotional state, if the wearer chooses Yes within the preset time period, it means that the wearer's emotion is in a stable emotional state. If the wearer chooses No within the preset time period, it means that the wearer's emotion is in a non-normal state. Stable emotional state. If no feedback instruction is received from the wearer within the preset time period, it means that the wearer's emotion is in a stable emotional state.

As a possible implementation method of the embodiment of this application, the smart bracelet is also used to implement:

If it is detected that the wearer is in a state of exercise during an abnormal heartbeat, the exercise intensity level of the wearer is obtained. If the exercise intensity level exceeds the preset level, intensity warning information is generated and fed back to the wearer's terminal device. The intensity warning information is used to indicate that the wearer is currently exercising excessively.

Specifically, when the wearer is in motion, the wearer's excessive movement may also cause a cardiac emergency of the wearer, causing major abnormalities in the wearer's ECG signal. Therefore, when it is detected that the wearer is in motion during an abnormal heartbeat period, it can be determined based on the wearer's exercise intensity level whether the wearer's exercise intensity level exceeds the preset level. The preset level is used to represent the exercise intensity level corresponding to normal exercise intensity. The preset level may be preset, or may be an exercise intensity level determined in advance based on the wearer's historical exercise conditions.

The higher the exercise intensity level, the greater the exercise intensity of the wearer. When the wearer's exercise intensity level does not exceed the preset level, it means that the wearer is at normal exercise intensity. When the wearer's exercise intensity level exceeds the preset level, it means that the wearer is likely to exercise excessively at this time, causing the wearer to exercise excessively. The person's heartbeat is too strong, and the abnormal heartbeat of the wearer is most likely caused by excessive exercise.

Therefore, when the wearer is in a state of exercise during an abnormal heartbeat, if the preset level is exceeded, intensity warning information is generated and fed back to the wearer's terminal device to remind the wearer that the current exercise intensity is too high. Specifically, When the intensity warning information is fed back to the wearer's terminal device, the ECG signal corresponding to the current moment is also fed back to the wearer's terminal device, so that the wearer can reduce the range of movement or stop movement, thereby reducing the risk of excessive movement. Chances of developing heart disease.

A possible implementation of the embodiment of the present application. In the above embodiment, the smart bracelet is configured to obtain the exercise intensity level of the wearer. Specifically, it can be implemented: based on the arm vibration information, determine the duration of exercise, and determine the exercise duration based on the arm vibration information. The duration of exercise is used to determine and obtain the exercise intensity level of the wearer.

Specifically, generally, when the duration of the wearer's exercise is longer, it indicates that the intensity of the wearer's exercise is greater; when the duration of the wearer's exercise is shorter, it indicates that the intensity of the wearer's exercise is smaller.

That is to say, when the exercise duration is longer, it indicates that the wearer's exercise intensity level is higher. Specifically, when determining the exercise intensity level of the wearer, it can be determined based on the preset corresponding relationship between the exercise duration and the exercise intensity level. . For example, if the exercise duration is 0~1h, the corresponding exercise intensity level is level 1, and if the exercise duration is 1h~2h, the corresponding exercise intensity level is level 2, etc.

Among them, according to the arm vibration information, the way to determine the duration of the movement can be to determine the target time based on the arm vibration information. The target time is the time when the arm vibration amplitude exceeds the preset vibration amplitude threshold, and the start of the movement is determined based on each target time. time, determine the duration between the movement start time and the current time as the movement duration. Among them, when determining the starting moment of the movement, the specific method can be: if the interval between any two adjacent target moments exceeds the preset interval, then the adjacent target moment is determined as the initial moment of the target movement, and each target movement is Among the initial moments, the target motion initial moment with the smallest time interval from the current moment is determined, and the determined moment is used as the motion start moment.

In addition, the exercise intensity of the wearer may also be related to the range of movement of the wearer. When the duration of the wearer's exercise is the same, the exercise intensity corresponding to the wearer's running and cycling is also different. Therefore, in the above embodiment, Determining and obtaining the exercise intensity level of the wearer based on the duration of exercise includes: determining the mean arm vibration amplitude based on the wearer's arm vibration information during the abnormal heartbeat period. Based on the average amplitude of arm vibration and the duration of exercise, the exercise intensity level of the wearer is determined.

Specifically, the mean arm vibration amplitude is the mean value of the vibration amplitude of the wearer's arm during the abnormal heartbeat period, and is used to characterize the movement amplitude level of the wearer during the abnormal heartbeat period.

More specifically, based on the arm vibration information of the wearer during the abnormal heartbeat period, the method of determining the average arm vibration amplitude may include determining the arm vibration amplitude of the wearer during the abnormal heartbeat period at preset time intervals. It can be 5 seconds, or it can be 10 seconds, etc.; calculate the average arm vibration amplitude to determine the average arm vibration amplitude.

Specifically, when determining the exercise intensity level, different mean arm vibration amplitudes correspond to different corresponding relationships between exercise duration and exercise intensity level. For example, when the mean arm vibration amplitude corresponds to the first interval, the corresponding relationship between the exercise duration and the exercise intensity level is the correspondence relationship A. When the mean arm vibration amplitude corresponds to the second interval, the relationship between the exercise duration and the exercise intensity level is The corresponding relationship between is the corresponding relationship B.

When determining the exercise intensity level, the corresponding relationship between the exercise duration and the exercise intensity level is determined based on the average arm vibration amplitude, and then based on the corresponding relationship and the exercise duration, the exercise intensity level of the wearer is determined.

The above embodiment introduces a smart bracelet from the perspective of a physical device, and the following embodiment introduces an ECG signal detection method from the perspective of method flow. For details, see the following embodiments.

Referring to Figure 2, a method for detecting ECG signals is performed by a smart bracelet. The method includes:

Step S201: Collect the ECG signal of the wearer.

Step S202: Detect whether the wearer's heartbeat is abnormal based on the ECG signal.

Step S203: If the heartbeat of the wearer is abnormal, the abnormal ECG segment is determined from the ECG signal, and the abnormal ECG segment is stored.

Among them, the abnormal ECG segment is an abnormal heartbeat segment in the ECG signal.

Step S204: When the connection with the medical staff terminal device is detected, each stored abnormal ECG segment is fed back to the medical staff terminal device.

Specifically, the smart bracelet is used to monitor and analyze the wearer's ECG signal in real time to detect whether the ECG signal is abnormal. When the wearer's heartbeat is abnormal, the abnormal ECG fragment is stored. When the personnel terminal equipment is connected, the stored abnormal ECG fragments are fed back to the medical staff terminal equipment, so that the medical staff can diagnose the heart disease of the wearer based on the abnormal ECG fragments of the wearer or refer to the abnormal ECG fragments during diagnosis. Abnormal ECG segments can improve the efficiency of doctors in detecting heart disease in the wearer.

One possible implementation of the embodiment of the present application is that in step S203, if the heartbeat of the wearer is abnormal, the abnormal ECG fragment is determined from the ECG signal and the abnormal ECG fragment is stored, including:

If the wearer's heartbeat is abnormal, detect whether the wearer is in motion during the abnormal heartbeat period;

If not in motion, detect whether the wearer's mood is in a stable emotional state;

If the patient is in a stable emotional state, abnormal ECG segments are determined from the ECG signals and stored.

A possible implementation of the embodiment of this application is that if the wearer's heartbeat is abnormal, detecting whether the wearer is in motion during the abnormal heartbeat period includes:

If the wearer's heartbeat is abnormal, the abnormal time when the wearer's heartbeat is abnormal is obtained;

Based on the abnormal time, determine whether the abnormal time is within the preset rest period;

If the abnormal moment is not within the preset rest period, it is detected whether the wearer is in motion during the abnormal heartbeat period.

A possible implementation method of the embodiment of this application is to detect whether the wearer is in motion during abnormal heartbeat, including:

Obtain the arm vibration information of the wearer during the abnormal heartbeat period. The arm vibration information is used to characterize the changes in the vibration amplitude of the wearer's arm over time;

Determine the vibration frequency based on the arm vibration information. The vibration frequency is used to characterize the occurrence frequency of the target moment. The target moment is the moment when the vibration amplitude exceeds the preset vibration amplitude threshold; detect whether the vibration frequency is greater than the preset frequency to detect abnormal heartbeats of the wearer. Whether you are in motion during this period.

One possible implementation method of the embodiment of this application is to detect whether the wearer's emotion is in a stable emotional state, including any of the following:

Obtain emotion detection information and determine whether the wearer's emotion is in a stable emotional state based on the emotion detection information;

Obtain emotion detection information, generate and display emotion prompt information based on the emotion detection information; detect whether the preset conditions are met to detect whether the wearer's emotion is in a stable emotional state. The preset conditions include receiving input from the wearer within a preset time period. Smooth feedback instructions that represent emotional stability.

A possible implementation method of the embodiment of this application also includes:

If it is detected that the wearer is in exercise during an abnormal heartbeat, the exercise intensity level of the wearer is obtained;

If the exercise intensity level exceeds the preset level, intensity warning information is generated and fed back to the wearer's terminal device. The intensity warning information is used to warn the wearer of the current excessive exercise state.

A possible implementation method of the embodiment of this application to obtain the exercise intensity level of the wearer includes:

Based on the arm vibration information, the duration of exercise is determined, and based on the duration of exercise, the exercise intensity level of the wearer is determined and obtained.

Those skilled in the art can clearly understand that for the convenience and simplicity of description, the flow and process of the above-described method can be referred to the corresponding process in the above-described device embodiment, and will not be described again here.

The above embodiment introduces an ECG signal detection method from the perspective of method flow. The following embodiment introduces an ECG signal detection device from the perspective of a virtual module. For details, see the following embodiments.

Referring to Figure 3, an ECG signal detection device 300 is shown. The device 300 includes:

The signal collection module 301 is used to collect the ECG signal of the wearer;

The abnormality detection module 302 is used to detect whether the heartbeat of the wearer is abnormal based on the ECG signal;

The segment determination module 303 is used to determine the abnormal ECG segment from the ECG signal if the wearer's heartbeat is abnormal, and store the abnormal ECG segment;

Among them, the abnormal ECG segment is the segment with abnormal heartbeat in the ECG signal;

The abnormal feedback module 304 is used to feed back each stored abnormal ECG segment to the medical staff terminal device when the connection with the medical staff terminal device is detected.

Specifically, the smart bracelet is used to monitor and analyze the wearer's ECG signal in real time to detect whether the ECG signal is abnormal. When the wearer's heartbeat is abnormal, the abnormal ECG fragment is stored. When the personnel terminal equipment is connected, the stored abnormal ECG fragments are fed back to the medical staff terminal equipment, so that the medical staff can diagnose the heart disease of the wearer based on the abnormal ECG fragments of the wearer or refer to the abnormal ECG fragments during diagnosis. Abnormal ECG segments can improve the efficiency of doctors in detecting heart disease in the wearer.

In one possible implementation of the embodiment of the present application, when the wearer's heartbeat is abnormal, the segment determination module 303 determines the abnormal ECG segment from the ECG signal and stores the abnormal ECG segment. It is specifically used to:

If the wearer's heartbeat is abnormal, detect whether the wearer is in motion during the abnormal heartbeat period;

If not in motion, detect whether the wearer's mood is in a stable emotional state;

If the patient is in a stable emotional state, abnormal ECG segments are determined from the ECG signals and stored.

In one possible implementation manner of this embodiment of the present application, when the wearer's heartbeat is abnormal, the segment determination module 303 detects whether the wearer is in a state of motion during the abnormal heartbeat, and is specifically used to:

If the wearer's heartbeat is abnormal, the abnormal time when the wearer's heartbeat is abnormal is obtained;

Based on the abnormal time, determine whether the abnormal time is within the preset rest period;

If the abnormal moment is not within the preset rest period, it is detected whether the wearer is in motion during the abnormal heartbeat period.

In one possible implementation of this embodiment of the present application, when detecting whether the wearer is in motion during an abnormal heartbeat, the segment determination module 303 is specifically used to:

Obtain the arm vibration information of the wearer during the abnormal heartbeat period. The arm vibration information is used to characterize the changes in the vibration amplitude of the wearer's arm over time;

Determine the vibration frequency based on the arm vibration information. The vibration frequency is used to characterize the occurrence frequency of the target moment. The target moment is the moment when the vibration amplitude exceeds the preset vibration amplitude threshold; detect whether the vibration frequency is greater than the preset frequency to detect abnormal heartbeats of the wearer. Whether you are in motion during this period.

In one possible implementation manner of this embodiment of the present application, when detecting whether the wearer's emotion is in a stable emotional state, the segment determination module 303 is specifically used to:

Obtain emotion detection information and determine whether the wearer's emotion is in a stable emotional state based on the emotion detection information; or,

Obtain emotion detection information, generate and display emotion prompt information based on the emotion detection information; detect whether the preset conditions are met to detect whether the wearer's emotion is in a stable emotional state. The preset conditions include receiving input from the wearer within a preset time period. Smooth feedback instructions that represent emotional stability.

In a possible implementation manner of this embodiment of the present application, the device 300 further includes:

The intensity level acquisition module is used to obtain the exercise intensity level of the wearer if it is detected that the wearer is in motion during an abnormal heartbeat period;

The intensity warning module is used to generate intensity warning information if the exercise intensity level exceeds the preset level, and feedback the intensity warning information to the wearer's terminal device. The intensity warning information is used to warn the wearer of the current excessive exercise state.

In one possible implementation manner of the embodiment of this application, when the intensity level acquisition module obtains the exercise intensity level of the wearer, it is specifically used to:

Based on the arm vibration information, the duration of exercise is determined, and based on the duration of exercise, the exercise intensity level of the wearer is determined and obtained.

The embodiment of the present application also introduces a smart bracelet from the perspective of a physical device, as shown in Figure 4. The smart bracelet 400 shown in Figure 4 includes: a processor 401 and a memory 403. Among them, the processor 401 and the memory 403 are connected, such as through a bus 402. Optionally, the smart bracelet 400 may also include a transceiver 404. It should be noted that in practical applications, the number of transceivers 404 is not limited to one, and the structure of the smart bracelet 400 does not limit the embodiments of the present application.

The processor 401 may be a CPU (Central Processing Unit, central processing unit), a general-purpose processor, a DSP (Digital Signal Processor, data signal processor), ASIC (Application Specific Integrated Circuit, application specific integrated circuit), FPGA (Field Programmable Gate Array, field programmable gate array) or other programmable logic device, transistor logic device, hardware component, or any combination thereof. It may implement or execute the various illustrative logical blocks, modules, and circuits described in connection with this disclosure. The processor 401 may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

Bus 402 may include a path that carries information between the above-mentioned components. The bus 402 may be a PCI (Peripheral Component Interconnect, Peripheral Component Interconnect Standard) bus or an EISA (Extended Industry Standard Architecture, Extended Industry Standard Architecture) bus, etc. The bus 402 can be divided into an address bus, a data bus, a control bus, etc. For ease of presentation, only one thick line is used in Figure 4, but it does not mean that there is only one bus or one type of bus.

The memory 403 may be a ROM (Read Only Memory) or other types of static storage devices that can store static information and instructions, RAM (Random Access Memory, random access memory) or other types that can store information and instructions. Dynamic storage devices can also be EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact DiscRead Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, Laser disc, optical disc, digital versatile disc, Blu-ray disc, etc.), magnetic disk storage medium or other magnetic storage device, or any other device capable of carrying or storing desired program code in the form of instructions or data structures that can be accessed by a computer medium, but not limited to this.

The memory 403 is used to store application program code for executing the solution of the present application, and is controlled by the processor 401 for execution. The processor 401 is used to execute the application program code stored in the memory 403 to implement the contents shown in the foregoing method embodiments.

Embodiments of the present application provide a computer-readable storage medium. The computer-readable storage medium stores a computer program. When run on a computer, the computer can execute the corresponding content in the foregoing method embodiments. In the embodiment of this application, the smart bracelet is used to monitor and analyze the wearer's ECG signal in real time to detect whether the ECG signal is abnormal. When the wearer's heartbeat is abnormal, the abnormal ECG fragment is stored. When the connection with the medical staff's terminal equipment is detected, the stored abnormal ECG fragments are fed back to the medical staff's terminal equipment, so that the medical staff can diagnose the wearer's heart disease based on the wearer's abnormal ECG fragments or can This abnormal ECG segment can be referred to during diagnosis, thereby improving the efficiency of doctors in detecting heart disease in the wearer.

It should be understood that although various steps in the flowchart of the accompanying drawings are shown in sequence as indicated by arrows, these steps are not necessarily performed in the order indicated by arrows. Unless explicitly stated in this article, the execution of these steps is not strictly limited in order, and they can be executed in other orders. Moreover, at least some of the steps in the flow chart of the accompanying drawings may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but may be executed at different times, and their execution order is also It does not necessarily need to be performed sequentially, but may be performed in turn or alternately with other steps or sub-steps of other steps or at least part of the stages.

The above are only some of the embodiments of the present application. It should be pointed out that those of ordinary skill in the art can also make several improvements and modifications without departing from the principles of the present application. These improvements and modifications should also be regarded as This is the protection scope of this application.

Claims (10)

1. A smart bracelet, characterized in that the smart bracelet includes: A processor configured to: Collect the ECG signals of the wearer; According to the ECG signal, detect whether the heartbeat of the wearer is abnormal; If the wearer's heartbeat is abnormal, an abnormal ECG segment is determined from the ECG signal and stored. The abnormal ECG segment is an abnormal heartbeat segment in the ECG signal. ; When a connection with the medical staff terminal device is detected, each stored abnormal ECG segment is fed back to the medical staff terminal device. 2. The smart bracelet according to claim 1, wherein the processor is configured to determine abnormal ECG segments from the ECG signal when the wearer's heartbeat is abnormal, And in the process of storing the abnormal ECG fragments, the specific implementation is: If the wearer's heartbeat is abnormal, detect whether the wearer is in motion during the abnormal heartbeat period; If not in motion, detect whether the wearer's emotion is in a stable emotional state; If the patient is in a stable emotional state, abnormal ECG segments are determined from the ECG signals, and the abnormal ECG segments are stored. 3. The smart bracelet according to claim 2, wherein the processor is configured to detect whether the wearer is in a state of exercise during the abnormal heartbeat period when the wearer's heartbeat is abnormal. ,Implementation: When the heartbeat of the wearer is abnormal, obtain the abnormal time when the heartbeat of the wearer is abnormal; Based on the abnormal time, determine whether the abnormal time is in a preset rest period; When the abnormal moment is not in the preset rest period, it is detected whether the wearer is in a state of exercise during the abnormal heartbeat period. 4. The smart bracelet according to claim 2 or 3, characterized in that the processor is configured to specifically implement: in the process of detecting whether the wearer is in motion during an abnormal heartbeat period: Obtain the arm vibration information of the wearer during the abnormal heartbeat period, and the arm vibration information is used to characterize the changes in the vibration amplitude of the wearer's arm over time; Determine the vibration frequency according to the arm vibration information. The vibration frequency is used to represent the frequency of occurrence of a target moment. The target moment is the moment when the vibration amplitude exceeds the preset vibration amplitude threshold; Detect whether the vibration frequency is greater than a preset frequency to detect whether the wearer is in a state of exercise during abnormal heartbeat. 5. The smart bracelet according to claim 2, wherein the processor is configured to specifically implement: in the process of detecting whether the wearer's emotion is in a stable emotional state: Obtain emotion detection information, and determine whether the wearer's emotion is in a stable emotional state based on the emotion detection information; or, Obtain emotion detection information, generate and display emotion prompt information based on the emotion detection information; detect whether preset conditions are met to detect whether the wearer's emotion is in a stable emotional state, and the preset conditions include a preset time period A smooth feedback instruction indicating a stable mood is received from the wearer. 6. The smart bracelet according to claim 2, wherein the processor is further used to implement the following steps: An intensity acquisition module, configured to acquire the exercise intensity level of the wearer when it is detected that the wearer is in a state of exercise during an abnormal heartbeat period; An intensity early warning module, configured to generate intensity early warning information when the exercise intensity level exceeds a preset level, and feedback the intensity early warning information to the wearer's terminal device. The intensity early warning information is used to monitor the wearer's current exercise. Warning for excessive status. 7. The smart bracelet according to claim 6, wherein the processor is configured to specifically implement: in the process of obtaining the exercise intensity level of the wearer: Based on the arm vibration information, the duration of the exercise is determined, and based on the duration of the exercise, the exercise intensity level of the wearer is determined and obtained. 8. An electrocardiogram signal detection method, characterized in that it is executed by a smart bracelet, and the method includes: Collect the ECG signals of the wearer; According to the ECG signal, detect whether the heartbeat of the wearer is abnormal; If the wearer's heartbeat is abnormal, an abnormal ECG segment is determined from the ECG signal, and the abnormal ECG segment is stored. The abnormal ECG segment is an abnormal heartbeat segment in the ECG signal. ; When a connection with the medical staff terminal device is detected, each stored abnormal ECG segment is fed back to the medical staff terminal device. 9. An electrocardiogram signal detection device, characterized in that the device includes: Signal acquisition module, used to collect the ECG signal of the wearer; An abnormality judgment module, used to detect whether the heartbeat of the wearer is abnormal based on the ECG signal; A segment determination module, configured to determine an abnormal ECG segment from the ECG signal when the wearer's heartbeat is abnormal, and store the abnormal ECG segment, where the abnormal ECG segment is the ECG signal. Fragments of abnormal heartbeats in the signal; The abnormality feedback module is used to feed back each stored abnormal ECG segment to the medical staff terminal equipment when the connection with the medical staff terminal equipment is detected. 10. A computer-readable storage medium with a computer program stored thereon, characterized in that when the computer program is executed in a computer, the computer is caused to execute the ECG signal detection method of claim 8.