Data processing method, electronic device, wearable device and communication system

Abstract

The present application relates to electronic technology. Provided are a data processing method, an electronic device, a wearable device and a communication system, which are used for monitoring a physiological parameter of a user in real time, prompting the user to cooperate to input related data upon detecting that the physiological parameter is abnormal, and performing related detection. The method is applied to an electronic device, and the electronic device establishes a connection with a wearable device. The method comprises: when a wearable device is worn on a body part of a user, acquiring, on the basis of a connection, a first parameter value corresponding to a preset physiological parameter, which is collected from the user by means of the wearable device, wherein the preset physiological parameter comprises at least one of the following: a pulse wave velocity (PWV), a heart rate, a heart rate variability (HRV), a blood pressure and a respiratory rate; analyzing the first parameter value to obtain a first analysis result; and when the first analysis result represents that the preset physiological parameter of the user is abnormal, sending first prompt information, wherein the first prompt information is used for prompting the user to cooperate to input preset data, so as to perform new analysis on the preset physiological parameter.

Description

Data processing method, electronic device, wearable device and communication system

[0001] This application claims priority to the Chinese patent application filed with the State Intellectual Property Office on December 11, 2023, with application number 202311688769.2 and invention name “A data processing method, electronic device, wearable device and communication system”, the entire contents of which are incorporated by reference into this application. Technical Field

[0002] The embodiments of the present application relate to electronic technology, and in particular to a data processing method, electronic equipment, wearable device, and communication system. Background Art

[0003] Coronary atherosclerotic heart disease (CHD) is one of the most lethal diseases worldwide. In practice, electrocardiograms (ECGs) are a common method for initial screening of CHD. However, the ECG typically displays characteristic findings only during a CHD attack.

[0004] A coronary heart disease attack is usually characterized by regular, mild pain that resolves on its own after rest. Therefore, the pain caused by a coronary heart disease attack is often underestimated or ignored, leading to a delay in seeking medical attention and missed opportunities for electrocardiogram (ECG) testing.

[0005] Summary of the Invention

[0006] The embodiments of the present application provide a data processing method, electronic device, wearable device and communication system for real-time monitoring of a user's physiological parameters, and prompting the user to cooperate in entering relevant data and performing relevant tests when abnormal physiological parameters are detected.

[0007] To achieve the above objectives, the embodiments of the present application adopt the following technical solutions:

[0008] In a first aspect, a data processing method is provided, which is applied to an electronic device connected to a wearable device. The method includes:

[0009] When the wearable device is worn on a user's body, the electronic device can obtain a first parameter value corresponding to a preset physiological parameter collected by the wearable device based on the connection. The preset physiological parameter includes at least one of the following: pulse wave velocity (PWV), heart rate, heart rate variability (HRV), blood pressure, and respiratory rate. The electronic device can then analyze the first parameter value to obtain a first analysis result. If the first analysis result indicates that the user's preset physiological parameter is abnormal, a first prompt message can be issued. The first prompt message is used to prompt the user to cooperate in entering preset data to perform a new analysis of the preset physiological parameter.

[0010] In this solution, the electronic device can collect parameter values ​​corresponding to the user's preset physiological parameters based on the wearable device and analyze the parameter values ​​corresponding to the preset physiological parameters. Furthermore, if the analysis determines that the corresponding parameter value is abnormal, the electronic device can also prompt the user to cooperate in entering the preset data by issuing a first prompt message, thereby facilitating further analysis of the parameter value. In this way, by relying on the wearable device to monitor the user's preset physiological parameters, the parameter analysis can be used to find the right time to prompt the user to pay attention to the physical condition and cooperate in entering relevant data, and then further in-depth examinations can be carried out. This reduces the possibility of missing the opportunity for relevant detection due to the user ignoring or getting used to the pain.

[0011] In one possible implementation of the first aspect, issuing the first prompt information may specifically include: issuing the first prompt information on the electronic device; and / or, the electronic device sending a notification message to the wearable device, causing the wearable device to issue the first prompt information. This can better remind the user to pay attention to their physical condition in a timely manner.

[0012] In a possible implementation of the first aspect, the first prompt information may be issued in different prompt forms such as sound, vibration, indicator light, and / or image, thereby enriching the prompt forms.

[0013] In a possible implementation of the first aspect, the preset data includes sensory information of the user's target body part. After issuing the first prompt message, the above method further includes: obtaining the sensory information of the target body part input by the user. Afterwards, the electronic device can further analyze the sensory information of the target body part and the first parameter value to obtain a second analysis result, thereby determining whether the abnormality of the preset physiological parameter is associated with the target body part. If the abnormality of the preset physiological parameter is associated with the target body part, it means that the target body part may be abnormal. In addition, when the second analysis result indicates that the target body part of the user is abnormal, the electronic device can issue a second prompt message. The second prompt message is used to prompt the user to perform a preset detection through the wearable device.

[0014] In this solution, if an abnormality occurs in the first parameter value, the electronic device can prompt the user to enter the sensory information of the target body part, such as whether pain symptoms occur and the characteristic manifestations when pain occurs. After receiving the sensory information of the target body part input by the user, the electronic device can further analyze whether the abnormality of the detected first parameter value is associated with the target body part based on the sensory information. Finally, if it is determined that the second analysis result indicates that an abnormality exists in the target body part, the electronic device can prompt the user to perform a preset test. In this way, if there may be an abnormality in the target body part, the user can be reminded to perform relevant tests in a timely manner to avoid missing the opportunity for detection.

[0015] At the same time, after performing preset detection through the wearable device, the detection results of the preset detection during the period when abnormalities may occur can be stored, which can help users with further detection or diagnosis later.

[0016] In a possible implementation of the first aspect, the target body part may be the chest. Thus, the electronic device can analyze whether abnormalities in preset physiological parameters are associated with body parts near the chest, thereby helping the user better understand their physical condition.

[0017] In a possible implementation of the first aspect, the above-mentioned analysis of the perception information of the target body part and the first parameter value to obtain the second analysis result may specifically include: inputting the perception information of the target body part and the first parameter value into a first preset prompt model. The first preset prompt model is determined through training. The electronic device can obtain the first output result of the first preset prompt model. The second analysis result includes the first output result; the first output result is used to characterize the probability that the user's target body part is abnormal. In this solution, the second analysis result characterizes that the user's target body part is abnormal, and a second prompt message is issued. Specifically, it may include: if the first output result is greater than a first preset threshold and less than or equal to a second preset threshold, a second prompt message is issued; wherein the second preset threshold is greater than the first preset threshold. Both the first preset threshold and the second preset threshold can be determined based on the first preset prompt model.

[0018] In this solution, a pre-trained preset prompt model is used to quickly determine the probability of an abnormality in a target body part based on a first parameter value and sensory information about the target body part. Furthermore, the output probability is compared with two preset thresholds determined based on the preset prompt model. If the probability is greater than the first preset threshold and less than or equal to the second preset threshold, a second prompt is used to notify the user that the target body part is abnormal.

[0019] In a possible implementation of the first aspect, the method may further include: issuing a third prompt message if the first output result is greater than a second preset threshold. The third prompt message is used to inform the user that there is an abnormality in the target body part, and the urgency level corresponding to the third prompt message is higher than the urgency level corresponding to the second prompt message.

[0020] In one possible implementation of the first aspect, both the second and third prompts are in the form of sound prompts. The urgency level corresponding to the third prompt is higher than that corresponding to the second prompt. Specifically, the duration of the third prompt is longer than that of the second prompt. Alternatively, the volume of the third prompt is higher than that of the second prompt. Alternatively, the sound of the third prompt is more urgent than that of the second prompt. In this way, the user can be more intuitively informed of the urgency level.

[0021] In one possible implementation of the first aspect, both the second and third prompts are in the form of vibration prompts. The urgency level corresponding to the third prompt is higher than that corresponding to the second prompt. Specifically, the vibration duration of the third prompt is longer than that of the second prompt. Alternatively, the vibration amplitude of the third prompt is greater than that of the second prompt. This allows the user to be more intuitively informed of the urgency level.

[0022] In one possible implementation of the first aspect, both the second and third prompts are in the form of indicator lights. The third prompt corresponds to a higher level of urgency than the second prompt. Specifically, this can be manifested by the indicator light flashing at a higher frequency than the second prompt. Alternatively, the indicator light for the third prompt can be brighter than the second prompt. This allows the user to be more intuitively informed of the level of urgency.

[0023] In one possible implementation of the first aspect, analyzing the first parameter value to obtain the first analysis result may specifically include: inputting the first parameter value into a second preset prompt model. The second preset prompt model is determined through training. Obtaining a second output result of the second preset prompt model. The first analysis result includes a second output result; the second output result is used to characterize the probability that the user's preset physiological parameter is abnormal. In this solution, the first analysis result characterizing the user's preset physiological parameter as abnormal includes: the second output result being greater than a third preset threshold.

[0024] In this solution, a pre-trained preset prompt model is used to quickly determine the probability of a preset physiological parameter being abnormal based on the first parameter value. Furthermore, by comparing the output probability with a preset threshold value determined based on the preset prompt model, it is also possible to quickly determine whether the first parameter value is abnormal.

[0025] In one possible implementation of the first aspect, the electronic device stores reference values ​​corresponding to preset physiological parameters and preset user information. The analysis of the first parameter value to obtain the first analysis result may specifically include analyzing the reference value, the preset user information, and the first parameter value to obtain the first analysis result. In this way, the reference value and the preset user information can be combined to determine whether the first parameter value is abnormal, resulting in a more accurate analysis result.

[0026] In a possible implementation of the first aspect, the reference value, the preset user information, and the first parameter value are analyzed to obtain a first analysis result, which can specifically include: inputting the reference value, the preset user information, and the first parameter value into a second preset prompt model to obtain a second output result of the second preset prompt model.

[0027] In a possible implementation of the first aspect, different users, as well as users with different ages, genders, and user habits, may have different preset physiological parameters. Therefore, the above analysis of the reference value, preset user information, and the first parameter value to obtain the first analysis result may specifically include: combining the reference value and the preset user information to determine the normal indicator range corresponding to the preset physiological parameter. Then, the electronic device determines whether the first parameter value corresponding to the preset physiological parameter exceeds the corresponding normal indicator range. In this solution, the above first analysis result characterizes that the preset physiological parameter of the user is abnormal, and specifically may include: at least the first parameter value corresponding to the preset physiological parameter of the preset item exceeds the corresponding normal indicator range. The preset items can be set according to the timing, such as being set to 2 or 3 items.

[0028] In one possible implementation of the first aspect, different preset physiological parameters have different frequency of output. The above-mentioned analysis of the first parameter value to obtain the first analysis result may specifically include: analyzing the first parameter values ​​obtained within the same cycle to obtain the first analysis result. The electronic device obtains the parameter value corresponding to each preset physiological parameter within the same cycle. That is, within a cycle, the electronic device can obtain the parameter value corresponding to each preset physiological parameter, but the frequency of output of different preset physiological parameters varies. In this solution, the above-mentioned method may further include: upon detecting that the first parameter value corresponding to the first preset physiological parameter exceeds the corresponding normal indicator range, immediately obtaining, via the wearable device, a third parameter value corresponding to a second preset physiological parameter. The first preset physiological parameter includes one or more of the preset physiological parameters, and the second preset physiological parameter includes other physiological parameters other than the first preset physiological parameter. That is, within the same cycle, if the parameter value corresponding to the preset physiological parameter first obtained by the electronic device exceeds the corresponding normal indicator range, the wearable device may be triggered to immediately acquire the parameter value corresponding to the other preset physiological parameter, without having to wait until the other preset physiological parameters within the cycle have output values. The electronic device can then analyze the reference value, the preset user information, the first parameter value corresponding to the first preset physiological parameter, and the third parameter value to obtain a third analysis result. Furthermore, if the third analysis result indicates that the user's preset physiological parameter is abnormal, the electronic device can also issue a first prompt. This can expedite the process of collecting physiological parameters if a user's physiological parameters are suspected of being abnormal, thereby more quickly alerting the user when an abnormality occurs.

[0029] In a possible implementation of the first aspect, after the ECG detection prompt is issued, the method further includes: performing a single-lead ECG detection in response to an activation operation of the ECG detection function; obtaining a first detection result of the single-lead ECG detection; and performing a multi-lead ECG detection if the first detection result is normal.

[0030] In one possible implementation of the first aspect, the multi-lead ECG test may specifically include: first performing a first multi-lead ECG test and obtaining a second test result of the first multi-lead ECG test. Then, if the second test result is normal, performing a second multi-lead ECG test; and then obtaining a third test result of the second multi-lead ECG test. Finally, if the third test result is normal, indicating that the user is normal, the electronic device may issue a health reminder. The multi-lead ECG test includes the first multi-lead ECG test and the second multi-lead ECG test. In this way, the user can be reminded to perform ECG tests in sequence.

[0031] In a possible implementation of the first aspect, the method further includes: if the first test result is abnormal, or the second test result is abnormal, or the third test result is abnormal, a fourth prompt message is issued; the fourth prompt message is used to prompt that the test result of the ECG test is abnormal; the urgency corresponding to the fourth prompt message is higher than the urgency corresponding to the first prompt message. The posture required for the user to cooperate with multi-lead ECG testing is more complicated than that required for the user to cooperate with single-lead ECG testing. Therefore, a single-lead ECG test is performed first and then a multi-lead ECG test. If the single-lead ECG test result is normal, the user can be prompted to pay attention to his or her physical condition. The user can choose to perform the single-lead ECG test again, or choose whether to continue the multi-lead ECG test. This can provide better comfort for the user.

[0032] In one possible implementation of the first aspect, the electronic device stores reference values ​​corresponding to preset physiological parameters and preset user information. The analysis of the sensory information of the target body part and the first parameter value to obtain the second analysis result may specifically include analyzing the reference value, the preset user information, the sensory information of the target body part, and the first parameter value to obtain the second analysis result. In this way, the reference value and the preset user information can be combined to determine whether the first parameter value is abnormal, resulting in a more accurate analysis result.

[0033] In a possible implementation of the first aspect, analyzing a reference value, preset user information, sensory information of a target body part, and a first parameter value to obtain a second analysis result may specifically include: inputting the reference value, preset user information, sensory information of the target body part, and the first parameter value into a first preset prompt model. The first preset prompt model is determined through training. The electronic device may obtain a first output result of the first preset prompt model. The second analysis result includes the first output result; the first output result is used to characterize the probability that the user's target body part is abnormal. In this solution, the second analysis result characterizes that the user's target body part is abnormal, and a second prompt message is issued. Specifically, the second analysis result may include: if the first output result is greater than a first preset threshold and less than or equal to a second preset threshold, a second prompt message is issued; wherein the second preset threshold is greater than the first preset threshold. Both the first preset threshold and the second preset threshold can be determined based on the first preset prompt model.

[0034] In a possible implementation of the first aspect, before obtaining a first parameter value corresponding to a preset physiological parameter of the user, the method further includes: displaying a first interface for entering preset user information. Then, receiving and saving the preset user information entered by the user on the first interface. The preset user information may include the user's age and gender.

[0035] In a possible implementation of the first aspect, the preset user information may also include: whether the user has a history of chest pain (typical chest pain type of coronary heart disease), whether the user has diabetes, whether the user has hypertension, whether the blood lipids are abnormal, and whether the user smokes. One or more of the following.

[0036] In one possible implementation of the first aspect, the first interface further includes a first control configured to trigger acquisition of a reference value of a preset physiological parameter. In response to the triggering operation on the first control, the electronic device may transmit a second parameter value corresponding to the preset physiological parameter acquired via the wearable device to the wearable device. The second parameter value may be saved as the reference value of the preset physiological parameter.

[0037] In a possible implementation of the first aspect, the electronic device may display the first interface at regular intervals to prompt the user to re-enter the preset user information and the reference values ​​of the preset physiological parameters. This ensures that the data is updated and closer to the user's actual situation.

[0038] In a possible implementation manner of the first aspect, the preset physiological parameter includes PWV, and the corresponding first parameter value may include a PWV value.

[0039] In a possible implementation manner of the first aspect, the preset physiological parameter includes heart rate, and the corresponding first parameter value may include parameter values ​​such as heart rate value, heart rate increase amplitude, and heart rate decrease rate.

[0040] In a possible implementation of the first aspect, the preset physiological parameters include HRV, and the corresponding first parameter value may include relevant parameters of HRV, such as the standard deviation of heart beat intervals, and the proportion of consecutive heart beat interval differences exceeding 50ms.

[0041] In a possible implementation of the first aspect, the preset physiological parameter includes blood pressure, and the corresponding first parameter value may include parameter values ​​such as blood pressure value, blood pressure increase amplitude, and blood pressure decrease ratio per minute.

[0042] In a possible implementation manner of the first aspect, the preset physiological parameter includes a respiratory frequency, and the corresponding first parameter value may include: a respiratory frequency value.

[0043] In a second aspect, the present application provides a data processing method, which is applied to a wearable device, and the wearable device establishes a connection with an electronic device. The method includes: when the wearable device is worn on a part of the user's body, collecting a first parameter value corresponding to a preset physiological parameter of the user. The first parameter value is sent to the electronic device through the connection. The first parameter value is used by the electronic device to analyze the first parameter value to obtain a first analysis result. When the first analysis result indicates that the preset physiological parameter of the user is abnormal, a first prompt message is issued, and the first prompt message is used to prompt the user to cooperate in entering the preset data to perform a new analysis of the preset physiological parameter.

[0044] In a possible implementation manner of the second aspect, the wearable device can collect parameter values ​​corresponding to preset physiological parameters in real time.

[0045] In a third aspect, the present application provides a data processing method, which is applied to a wearable device. The method includes: when the wearable device is worn on a part of the user's body, collecting a first parameter value corresponding to a preset physiological parameter of the user. The preset physiological parameters include at least one of the following: pulse wave velocity PWV, heart rate, heart rate variability HRV, blood pressure, and respiratory rate. Obtain a reference value corresponding to the preset physiological parameter and preset user information. Analyze the first parameter value to obtain a first analysis result. The first analysis result indicates that the preset physiological parameter of the user is abnormal, and issues a first prompt message, which is used to prompt the user to cooperate in entering the preset data to perform a new analysis on the preset physiological parameter.

[0046] In this solution, the collection and analysis of parameter values ​​corresponding to preset physiological parameters can be achieved on the wearable device, and reminders can be issued when the parameter values ​​are abnormal.

[0047] In a fourth aspect, the present application further provides an electronic device. The electronic device may include a processor and a memory. The memory is configured to store computer-executable instructions. When the electronic device is in operation, the processor executes the computer-executable instructions stored in the memory to cause the electronic device to perform the data processing method described in any one of the first aspects or the data processing method described in any one of the third aspects.

[0048] In a fifth aspect, the present application further provides a wearable device. The wearable device may include a photoplethysmography (PPG) sensor, a processor, and a memory. The PPG sensor and the memory are each coupled to the processor. The PPG sensor is configured to collect parameter values ​​corresponding to preset physiological parameters. The memory stores computer program code, which includes computer instructions. The processor executes the computer-executable instructions stored in the memory to cause the wearable device to perform the data processing method described in any one of the second aspects above.

[0049] In a possible implementation of the fifth aspect, the wearable device may further include an electrocardiogram (ECG) sensor coupled to the processor and configured to perform electrocardiogram (ECG) detection.

[0050] In a sixth aspect, the present application further provides a communication system. The communication system includes the electronic device according to any one of the fourth aspects and the wearable device according to any one of the fifth aspects. The electronic device establishes a connection with the wearable device, and the electronic device can obtain parameter values ​​corresponding to preset physiological parameters collected by the wearable device through the connection.

[0051] In a seventh aspect, the present application provides a computer-readable storage medium, which stores instructions. When the computer-readable storage medium is run on a computer, the computer can execute any one of the data processing methods in the first aspect.

[0052] In an eighth aspect, a computer program product comprising instructions is provided, which, when executed on an electronic device, enables the electronic device to execute any one of the data processing methods in the first aspect.

[0053] In a ninth aspect, a device (for example, a chip system) is provided, which includes a processor for supporting an electronic device in implementing the functions described in the first aspect. In one possible design, the device also includes a memory for storing program instructions and data necessary for the electronic device. When the device is a chip system, it can be composed of a chip or include a chip and other discrete devices.

[0054] Among them, the technical effects brought about by any design method in the second to ninth aspects can refer to the technical effects brought about by different design methods in the first aspect, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] FIG1 is a schematic diagram of the structure of a communication system provided in an embodiment of the present application;

[0056] FIG2 is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application;

[0057] FIG3 is a schematic diagram of the hardware structure of a wearable device provided in an embodiment of the present application;

[0058] FIG4 is a schematic structural diagram of a wearable device provided in an embodiment of the present application;

[0059] FIG5 is a schematic structural diagram of a wearable device provided in an embodiment of the present application;

[0060] FIG6 is a schematic diagram of a twelve-lead ECG provided in an embodiment of the present application;

[0061] FIG7 is a schematic diagram of a six-limb lead ECG provided in an embodiment of the present application;

[0062] FIG8 is a schematic diagram of a detection posture of six limb leads provided in an embodiment of the present application;

[0063] FIG9 is a comparison diagram of six preset positions on the chest and six equivalent positions provided in an embodiment of the present application;

[0064] FIG10 is a schematic diagram of an equivalent precordial lead detection principle provided by an embodiment of the present application;

[0065] FIG11 is a schematic diagram of detection postures and detection electrode positions of six precordial leads provided by an embodiment of the present application;

[0066] FIG12 is a flow chart of a data processing method provided in an embodiment of the present application;

[0067] FIG13 is a flow chart of a data processing method provided in an embodiment of the present application;

[0068] FIG14 is a schematic diagram of an interface of a mobile phone provided in an embodiment of the present application;

[0069] FIG15 is a schematic diagram of the interface of a mobile phone provided in an embodiment of the present application;

[0070] FIG16 is a schematic diagram of an interaction process between a smartwatch and a mobile phone provided in an embodiment of the present application;

[0071] FIG17 is a schematic diagram of a single-lead ECG sensor and a PPG sensor for measuring PWV using parameters acquired by the sensor according to an embodiment of the present application;

[0072] FIG18 is a schematic diagram of a single-lead ECG sensor and a PPG sensor for measuring PWV using parameters acquired by the sensor according to an embodiment of the present application;

[0073] FIG19 is a schematic diagram of a complete flow chart of a data processing method provided in an embodiment of the present application;

[0074] FIG20 is a schematic diagram of a mobile phone interface during a single-lead ECG test performed using a smartwatch according to an embodiment of the present application;

[0075] FIG21 is a schematic diagram of a mobile phone interface during a multi-lead ECG test performed using a smartwatch according to an embodiment of the present application;

[0076] FIG22 is a schematic diagram of a mobile phone interface during a multi-lead ECG test performed using a smartwatch according to an embodiment of the present application;

[0077] FIG23 is a schematic diagram of an interface of a smart watch provided in an embodiment of the present application;

[0078] Figure 24 is an architectural diagram of a chip system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0079] To facilitate understanding, the following briefly describes the technical terms that may be involved in the embodiments of the present application.

[0080] 1. Coronary heart disease can be divided into chronic coronary syndrome (chronic coronary syndrome) and acute coronary syndrome (acute coronary syndrome).

[0081] 2. Pulse wave velocity (PWV) reflects the elasticity of the body's large arteries. When the arteries are elastic, the pulse wave velocity is slow; when the arteries are inelastic, the pulse wave velocity is fast.

[0082] 3. Heart rate refers to the number of times the human heart beats per minute and is one of the basic vital signs of a person.

[0083] 4. Heart rate variability (HRV) reflects the state of the human autonomic nervous system. The autonomic nervous system is primarily composed of the sympathetic and parasympathetic nervous systems. Both the sympathetic and parasympathetic nervous systems control the frequency and rhythm of the heartbeat. When the sympathetic nervous system is excited, the heartbeat frequency increases, the rhythm becomes more regular, and HRV-related parameters change accordingly. When the vagus nerve within the parasympathetic nervous system is excited, the heartbeat frequency decreases, the rhythm becomes irregular, and HRV-related parameters also change accordingly.

[0084] 5. Blood pressure refers to the lateral pressure exerted on the blood vessel wall per unit area when blood flows in the blood vessels. What is measured is generally the arterial blood pressure of the systemic circulation, including systolic pressure and diastolic pressure.

[0085] 6. Respiratory rate is the number of breaths per minute. People with coronary heart disease often experience an increased respiratory rate during an attack.

[0086] 7. The photoplethysmography (PPG) sensor is based on a light emitting diode (LED) light source and a light receiver. It measures the attenuated light after reflection and absorption by human blood vessels and tissues, records the pulsation state of blood vessels, and uses the pulsation frequency, rhythm, waveform, etc. to monitor heart rate, respiratory rate, pulse wave velocity, blood pressure, HRV and other information.

[0087] The gold standard for diagnosing coronary artery disease is coronary angiography, but this technique is invasive and costly. In practice, electrocardiograms (ECGs) are a common method for initial screening of coronary artery disease. However, typical ECG findings are only seen during acute attacks of acute coronary syndromes and chronic coronary syndromes. Furthermore, the majority of patients with coronary artery disease have chronic coronary syndromes. Without an acute attack, ECGs are unlikely to yield diagnostically valuable results.

[0088] The acute attack of chronic coronary syndrome is often short, lasting about 5-10 minutes. Therefore, even if people with chronic coronary syndrome go to the hospital for examination after an acute attack, it will be difficult to get a clear diagnosis because the attack time has been missed. The commonly used screening method in hospitals is the exercise treadmill test, which induces an acute attack of coronary heart disease by increasing the patient's exercise load, and continuously monitors the electrocardiogram during exercise to obtain a clear diagnosis. However, this examination takes a lot of time and has certain risks. At the same time, the attack of chronic coronary syndrome is usually regular pain with mild pain, and it can usually be relieved on its own after rest. Therefore, the pain caused by coronary heart disease attacks is often underestimated or ignored by people, and they fail to go to the hospital for a complete examination in time, which eventually leads to worsening of the disease.

[0089] Acute coronary syndrome (ACS) often presents with rapid onset and severe symptoms, characterized by characteristic changes in physiological parameters and electrocardiographic findings. However, most people with ACS develop symptoms of chronic ACS. A habit of neglecting chest pain can delay seeking medical attention, leading to delayed diagnosis and treatment, which can be life-threatening.

[0090] In related technologies, multi-lead electrocardiogram (ECG) sensors are installed in electronic devices (such as wearable devices). These electronic devices can detect and record the user's ECG signals through the multi-lead ECG sensor. However, in some cases, users may ignore symptoms such as chest pain, or if there is no obvious chest pain during a coronary heart disease attack, users may not be able to accurately find the right time to use the multi-lead ECG sensor for ECG testing.

[0091] Based on this, an embodiment of the present application proposes a data processing method and an electronic device. The method can obtain the parameter values ​​of physiological parameters in real time through a wearable device connected to the electronic device. Thus, the changes in the user's physiological parameters are monitored in real time, and when it is detected that the physiological parameters meet certain conditions, the user is prompted to cooperate in entering preset data to further analyze the parameter values ​​of the physiological parameters. In this way, by relying on the wearable device to monitor the user's preset physiological parameters, the parameter analysis can be used to find the right time to prompt the user to pay attention to the physical condition and cooperate in entering relevant data, and then further in-depth inspections can be carried out. This reduces the possibility of missing the opportunity for relevant detection due to the user ignoring or getting used to the pain.

[0092] People with coronary heart disease may experience a coronary heart attack under the influence of certain inducements. At this time, they may experience related symptoms (chest pain) and changes in some indicators, such as PWV, HRV, heart rate, blood pressure, respiratory rate, heart rate recovery, and blood pressure recovery. The most typical feature of an acute attack of coronary heart disease is changes in the electrocardiogram. In the data processing method proposed in the embodiment of the present application, changes in physiological parameters such as PWV, HRV, heart rate, blood pressure, and respiratory rate are monitored in real time by a PPG sensor. In addition, when it is detected that the changes in physiological parameters meet certain conditions, the user can be prompted to perform an electrocardiogram test.

[0093] In some embodiments, the above data processing method can be applied to an electronic device. The electronic device can be connected to and communicate with a wearable device. As shown in Figure 1, electronic device 2 is connected to and communicates with wearable device 1. Wearable devices are usually worn by users on parts of the body, such as the wrist, for a long time. A PPG sensor can be set on the wearable device. When the user wears the wearable device on a part of the body, the wearable device can monitor changes in physiological parameters such as PWV, HRV, heart rate, blood pressure, and respiratory rate in real time through the PPG sensor. Then, the electronic device obtains the above physiological parameters of the user from the wearable device. Afterwards, the electronic device can analyze the changes in the above physiological parameters of the user and provide prompts based on the analysis results.

[0094] Exemplarily, the electronic devices may be mobile phones, tablet computers, personal computers (PCs), smart screens, desktop computers, laptop computers, handheld computers, notebook computers, ultra-mobile personal computers (UMPCs), netbooks, smart watches and other wearable devices, artificial intelligence (AI) speakers and vehicle-mounted devices, and may also be various teaching aids (such as learning machines, early childhood education machines), smart toys, portable robots, personal digital assistants (PDAs), augmented reality (AR) and virtual reality (VR) devices, media players and other devices, and may also be devices with mobile office functions, devices with smart home functions, devices with audio and video entertainment functions, devices that support smart travel, etc. The embodiments of the present application do not impose any special restrictions on the specific form of the device.

[0095] FIG2 illustrates the hardware structure of an electronic device 100 in some embodiments. The electronic device 100 may include a processor 110, an external memory interface 120, an internal memory 121, a universal serial bus (USB) interface 130, a charging management module 140, a power management module 141, a battery 142, an antenna 1, an antenna 2, a mobile communication module 150, a wireless communication module 160, an audio module 170, a sensor module 180, a button 190, a motor 191, a camera 192, a display 193, and a subscriber identification module (SIM) card interface 194. The sensor module 180 may include a pressure sensor 180A, a touch sensor 180B, and the like.

[0096] It should be understood that the structures illustrated in the embodiments of the present application do not constitute a specific limitation on the electronic device 100. In other embodiments of the present application, the electronic device 100 may include more or fewer components than shown, or may combine or separate certain components, or arrange the components differently. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0097] The processor 110 may include one or more processing units, for example: the processor 110 may include an application processor (AP), a modem processor, a graphics processing unit (GPU), an image signal processor (ISP), a controller, a memory, a video codec, a digital signal processor (DSP), a baseband processor, and / or a neural-network processing unit (NPU), etc. Among them, different processing units can be independent devices or integrated into one or more processors. For example, the processor 110 is used to execute the data processing method in the embodiment of the present application.

[0098] The controller may be the nerve center and command center of the electronic device 100. The controller may generate an operation control signal according to the instruction operation code and the timing signal to complete the control of fetching and executing instructions.

[0099] Processor 110 may also include a memory for storing instructions and data. In some embodiments, the memory in processor 110 is a cache memory. This memory can store instructions or data that have just been used or are being recycled by processor 110. If processor 110 needs to use the same instruction or data again, it can directly retrieve it from the memory. This avoids duplicate accesses, reduces processor 110 latency, and thus improves system efficiency.

[0100] The USB interface 130 is an interface that complies with the USB standard and can be used to connect a charger to charge the electronic device 100, or to transmit data between the electronic device 100 and a peripheral device.

[0101] The external memory interface 120 can be used to connect an external memory card, such as a Micro SD card, to expand the storage capacity of the electronic device 100. The internal memory 121 can be used to store computer executable program codes, which include instructions.

[0102] The charging management module 140 is configured to receive charging input from a charger. The charger may be a wireless charger or a wired charger. In some wired charging embodiments, the charging management module 140 may receive charging input from the wired charger via the USB interface 130.

[0103] The power management module 141 is used to connect the battery 142, the charging management module 140, and the processor 110. The power management module 141 receives input from the battery 142 and / or the charging management module 140 and provides power to the processor 110, the internal memory 121, the external memory, the display 193, the camera 192, and the wireless communication module 160.

[0104] In some other embodiments, the power management module 141 may also be provided in the processor 110. In some other embodiments, the power management module 141 and the charging management module 140 may also be provided in the same device.

[0105] The wireless communication function of the electronic device 100 can be implemented through the antenna 1, the antenna 2, the mobile communication module 150, the wireless communication module 160, the modem processor and the baseband processor.

[0106] Antenna 1 and Antenna 2 are used to transmit and receive electromagnetic wave signals. Each antenna in electronic device 100 can be used to cover a single or multiple communication frequency bands. Different antennas can also be reused to improve antenna utilization. For example, antenna 1 can be reused as a diversity antenna for a wireless local area network. In other embodiments, the antennas can be used in conjunction with a tuning switch.

[0107] The mobile communication module 150 can provide wireless communication solutions, including 2G / 3G / 4G / 5G, for the electronic device 100. The mobile communication module 150 may include at least one filter, a switch, a power amplifier, a low-noise amplifier (LNA), and the like. The mobile communication module 150 can receive electromagnetic waves from the antenna 1, filter and amplify the received electromagnetic waves, and transmit them to the modem processor for demodulation. The mobile communication module 150 can also amplify the signals modulated by the modem processor and convert them into electromagnetic waves for radiation via the antenna 1.

[0108] The wireless communication module 160 can provide wireless communication solutions including wireless local area networks (WLAN) (such as Wi-Fi), Bluetooth (BT), global navigation satellite system (GNSS), frequency modulation (FM), near field communication (NFC), infrared (IR), etc. applied to the electronic device 100. The wireless communication module 160 can be one or more devices integrating at least one communication processing module. The wireless communication module 160 receives electromagnetic waves via the antenna 2, frequency modulates and filters the electromagnetic wave signals, and sends the processed signals to the processor 110. The wireless communication module 160 can also receive the signal to be sent from the processor 110, frequency modulate it, amplify it, and convert it into electromagnetic waves for radiation through the antenna 2.

[0109] In some embodiments, antenna 1 of electronic device 100 is coupled to mobile communication module 150 , and antenna 2 is coupled to wireless communication module 160 , so that electronic device 100 can communicate with the network and other devices through wireless communication technology.

[0110] The electronic device 100 can implement audio functions such as music playback and recording through the audio module 170 and the application processor.

[0111] The audio module 170 is used to convert digital audio signals into analog audio signals for output, and is also used to convert analog audio input into digital audio signals. The audio module 170 can also be used to encode and decode audio signals. In some embodiments, the audio module 170 can be provided in the processor 110, or some functional modules of the audio module 170 can be provided in the processor 110.

[0112] The pressure sensor 180A is used to sense pressure signals and convert them into electrical signals. In some embodiments, the pressure sensor 180A can be provided on the display screen 193. There are many types of pressure sensors 180A, such as resistive pressure sensors, inductive pressure sensors, capacitive pressure sensors, etc. A capacitive pressure sensor can be a device comprising at least two parallel plates having a conductive material. When a force acts on the pressure sensor 180A, the capacitance between the electrodes changes. The electronic device 100 determines the intensity of the pressure based on the change in capacitance. When a touch operation is applied to the display screen 193, the electronic device 100 detects the intensity of the touch operation based on the pressure sensor 180A. The electronic device 100 can also calculate the position of the touch based on the detection signal of the pressure sensor 180A.

[0113] Touch sensor 180B, also known as a "touch panel," can be disposed on display screen 193. The touch sensor 180B and display screen 193 form a touch screen, also known as a "touch screen." Touch sensor 180B is used to detect touch operations applied thereto or in the vicinity thereof. The touch sensor can transmit the detected touch operations to an application processor to determine the type of touch event. Visual output related to the touch operations can be provided via display screen 193. In other embodiments, touch sensor 180B can also be disposed on the surface of electronic device 100, at a location different from that of display screen 193.

[0114] The buttons 190 include a power button, a volume button, and the like. The buttons 190 may be mechanical buttons or touch buttons. The electronic device 100 may receive key inputs and generate key signal inputs related to user settings and function control of the electronic device 100.

[0115] Motor 191 can generate vibration prompts. Motor 191 can be used for incoming call vibration prompts, and can also be used for touch vibration feedback.

[0116] The camera 192 is used to capture still images or videos. In some embodiments, the electronic device 100 may include one or N cameras 192, where N is a positive integer greater than one.

[0117] Electronic device 100 implements display functionality through a GPU, display screen 193, and an application processor. The GPU is a microprocessor for image processing that connects display screen 193 and the application processor. The GPU is used to perform mathematical and geometric calculations for graphics rendering. Processor 110 may include one or more GPUs that execute program instructions to generate or modify display information.

[0118] The display screen 193 is used to display images, videos, etc. In some embodiments, the electronic device 100 may include 1 or N display screens 193 , where N is a positive integer greater than 1.

[0119] The SIM card interface 194 is used to connect a SIM card. The SIM card can be connected to and disconnected from the electronic device 100 by inserting or removing the SIM card into or from the SIM card interface 194. The electronic device 100 may support one or N SIM card interfaces, where N is a positive integer greater than one.

[0120] The data processing methods involved in the following embodiments can all be executed in the electronic device 100 having the above-mentioned hardware structure.

[0121] For example, the wearable device may be a portable wearable electronic device such as a sports bracelet, a smart watch, a smart armband, etc. The embodiment of the present application does not impose any particular limitation on the specific form of the wrist-type wearable electronic device.

[0122] FIG3 illustrates the hardware structure of a wearable device 200 in some embodiments. The wearable device 200 may include a processor 210, a charging management module 220, a power management module 221, a battery 222, an audio module 230, a display 240, a motor 250, an internal memory 260, a button 270, a sensor module 280, and a wireless communication module 290. The sensor module 280 may include a PPG sensor 280A, an accelerometer 280B, a single-lead ECG sensor 280C, and a multi-lead ECG sensor 280D.

[0123] It is understood that the structures illustrated in the embodiments of the present application do not constitute a specific limitation on the wearable device 200. In other embodiments of the present application, the wearable device 200 may include more or fewer components than shown, or may combine or separate certain components, or arrange the components differently. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.

[0124] For an introduction to the processor 210, charging management module 220, power management module 221, audio module 230, display screen 240, motor 250, internal memory 260, button 270, and wireless communication module 290, please refer to the introduction to the same components in the electronic device 100 shown in Figure 2.

[0125] The PPG sensor 280A, based on a light-emitting diode (LED) and a photodetector (PD), measures the attenuated light reflected and absorbed by human blood vessels and tissues, recording the pulsation state of blood vessels. Furthermore, based on the pulsation frequency, rhythm, and waveform, it can monitor heart rate, respiratory rate, pulse wave velocity, and other information.

[0126] The accelerometer 280B is a meter for measuring the linear acceleration of the vehicle. In the embodiment of the present application, the accelerometer 280B can be used to detect whether the user is in motion.

[0127] The single-lead ECG sensor 280C includes two electrodes and can be used to detect electrocardiographic signals.

[0128] The multi-lead ECG sensor 280D typically has more than two electrodes and can be used to detect electrocardiographic signals. The multi-lead ECG sensor 280D is compatible with the single-lead ECG sensor 280C.

[0129] In an embodiment of the present application, a wearable device uses an ECG sensor with multiple electrodes (e.g., 10 electrodes) (i.e., a multi-lead ECG sensor) to implement a wearable 12-lead ECG sensor detection solution. Nine of the electrodes are detection electrodes, and one electrode is a drive electrode to eliminate common-mode interference.

[0130] The following description uses a wrist-worn wearable device, such as a smartwatch, as an example. When performing a 12-lead ECG sensor measurement, the smartwatch must be removed. As shown in Figures 4 and 5 , the smartwatch 1 includes a body 13, a first fixing strap 14, and a second fixing strap 15. The body 13 is connected to the first fixing strap 14 and the second fixing strap 15, respectively.

[0131] The smartwatch 1 includes a first surface 11 (i.e., the outer side of the watchband) and a second surface 12 (i.e., the inner side of the watchband) formed by a body 13 and two fixing straps. Multiple detection electrodes 2 are provided on each of the first and second surfaces 11, 12, for detecting electrical signals on the human body surface. Specifically, the multiple detection electrodes 2 may include two upper limb electrodes, one lower limb electrode 23, and six chest electrodes. The two upper limb electrodes are provided on the first surface 11, such as the first upper limb electrode 20 and the second upper limb electrode 21 shown in FIG4 , which are respectively RA for contact with the right upper limb and LA for contact with the left upper limb. The lower limb electrodes may be provided on the smartwatch body 13 on the second surface 12, such as the first lower limb electrode 22 and the second lower limb electrode 23 shown in FIG5 , which are respectively RL for contact with the right lower limb and LL for contact with the left lower limb. The six chest electrodes may be provided on the first and second fixing straps 14, 15 on the second surface 12, and may include the detection electrodes 24, 25, ..., and 29 shown in FIG5 .

[0132] The smartwatch 1 described above can be used to detect an electrocardiogram (ECG). Next, we will introduce information related to the ECG. In a twelve-lead ECG, each lead represents a detection vector in one direction, and a single detection vector can only detect abnormalities in one direction. The twelve leads include six limb leads that reflect the cardiac potential in the coronal plane (a longitudinal section that divides the heart into anterior and posterior parts), and six precordial leads that reflect the cardiac potential in the transverse plane (a longitudinal section that divides the heart into upper and lower parts). The six limb leads may include: Lead I, Lead II, Lead III, aVL, Lead aVF, and Lead aVR as shown in FIG6 ; and the six precordial leads may include: Lead V1, Lead V2, Lead V3, Lead V4, Lead V5, and Lead V6 as shown in FIG6 . The twelve leads described above can reflect the electrical activity of different parts of the heart, thereby enabling a more comprehensive and accurate examination of the heart, such as for the detection of conditions such as coronary heart disease.

[0133] Next, we'll explain how to measure six limb leads. When using the smartwatch 1 for lead detection, the user can place the first upper limb electrode 20 and the second upper limb electrode 21 on the right and left upper limbs, respectively, and place the first lower limb electrode 22 and the second lower limb electrode 23 on the lower limbs. In this case, the three detection electrodes (the first upper limb electrode 20, the second upper limb electrode 21, and the second lower limb electrode 23) can measure a total of six limb leads; the first lower limb electrode 22 can serve as the driving electrode.

[0134] Referring to Figure 7 , the potential difference between the first upper limb electrode 20 and the second upper limb electrode 21 can be referred to as Lead I. The potential difference between the second lower limb electrode 23 and the first upper limb electrode 20 can be referred to as Lead II. The potential difference between the second lower limb electrode 23 and the second upper limb electrode 21 can be referred to as Lead III. Simultaneously, using the three detection electrodes, the first upper limb electrode 20, the second upper limb electrode 21, and the second lower limb electrode 23, the potential of the Wilson center point, the central electrical terminal of each of the three electrodes, can be located. By detecting the potential differences between the three detection electrodes, the first upper limb electrode 20, the second upper limb electrode 21, and the second lower limb electrode 23, signals for the three leads, aVR, aVL, and aVF, can be obtained.

[0135] When using the smartwatch 1 shown in Figures 4 and 5 for six-limb lead measurements, the smartwatch must be removed before use. For example, Figure 8 shows a schematic diagram of a six-limb lead detection posture. When performing a six-limb lead ECG measurement, the user can first place the smartwatch 1 in the lower limb 203 position as shown in Figure 8 . Specifically, the left upper limb 202 is brought into contact with the second upper limb electrode 21, and the right upper limb 201 is brought into contact with the first upper limb electrode 20. Furthermore, the left upper limb 202 and the right upper limb 201 are used to press one side of the smartwatch 1 against the human body 200. This ensures that the second surface 12 of the smartwatch 1 is in close contact with the human body 200, ensuring full contact between the second lower limb electrode 23 located on the second surface 12 and the left lower limb 203. In this way, the two upper limb electrodes and the second lower limb electrode 23 can respectively acquire the electrical potentials at corresponding locations on the human body 200. Combined with the method shown in Figure 7 , six-limb lead detection can be achieved. It should be noted that the measurement method shown in Figure 8 is only an example of a posture for six-limb lead measurement. In other embodiments, the user may also adopt other postures to perform six limb lead measurements, provided that the two upper limb electrodes and the two lower limb electrodes of the smartwatch are in contact with corresponding positions of the human body.

[0136] It should be noted that in the embodiments of this application, "upper limbs" refers to the area below the shoulders and above the navel, including the hands. "Lower limbs" refers to the area below the navel, including the feet, lower abdomen, legs, knees, etc. Furthermore, ECG measurements can be performed on both the left and right lower limbs, without limitation.

[0137] Next, the ECG detection of the six precordial leads is explained. Figure 9 shows the distribution of preset positions corresponding to the above-mentioned precordial leads. The six preset positions corresponding to the human precordial leads may include the V1, V2, V3, V4, V5 and V6 positions shown in Figure 9. When measuring the electrocardiogram, detection electrodes can be set at the six preset positions respectively. Among them, the first preset position V1 is located at the fourth intercostal space on the right edge of the sternum, the second preset position V2 is located at the fourth intercostal space on the left edge of the sternum, the third preset position V3 is located at the midpoint of the line connecting the second preset position V2 and the fourth preset position V4, the fourth preset position V4 is located at the intersection of the left midclavicular line and the fifth intercostal space, the fifth preset position V5 is located at the same level as the left anterior axillary line and V4, and the sixth preset position V6 is located at the same level as the left mid-axillary line and V4.

[0138] FIG9 also shows six equivalent positions (R1, R2, R3, R4, R5, and R6) equivalent to the above-mentioned six preset positions. In actual measurement, detection electrodes can be placed at the six equivalent positions to measure the electrocardiogram of the above-mentioned six precordial leads. FIG10 is a schematic diagram of the equivalent precordial lead detection principle in an embodiment of the present application. In FIG10, the vector directions of the six equivalent positions R1 to R6 pointed to by the second center point T2 correspond one to one with the vector directions of the six preset positions V1 to V6 pointed to by the first center point T1.

[0139] When using the smartwatch 1 shown in Figures 4 and 5 to perform six precordial lead measurements, the smartwatch must be removed before use. After removing the smartwatch 1 from the user's wrist, the second surface 12 of the smartwatch 1 can be placed in contact with the chest, as shown in Figure 11. The six precordial electrodes (detection electrodes 24-29) of the smartwatch 1 are placed in contact with the positions indicated by R1-R6 in Figure 9. Simultaneously, the left upper limb contacts the second upper limb electrode 21, and other fingers of the left upper limb press other locations on the watchband to ensure good contact between the electrodes on the second surface 12 (i.e., the inner side of the watchband). The right upper limb contacts the first upper limb electrode 20, and other fingers of the right upper limb press other locations on the watchband to ensure good contact between the precordial electrodes on the second surface 12 (detection electrodes 24-29). This indicates that the upper limb central potential at the second center point T2, determined by the two upper limb electrodes, is the difference between the potentials at the six equivalent locations R1-R6 detected by the six precordial electrodes. The obtained R1 lead, R2 lead, R3 lead, R4 lead, R5 lead and R6 lead can be equivalent to the V1 lead, V2 lead, V3 lead, V4 lead, V5 lead and V6 lead corresponding to their vector directions, respectively, thereby realizing the detection of the equivalent six precordial leads (V1 lead, V2 lead, V3 lead, V4 lead, V5 lead and V6 lead). It should be noted that the measurement method shown in FIG11 is only an example of a posture for measuring the six precordial leads. In other embodiments, on the premise of ensuring that the six detection electrodes on the inner side of the smart watch strap are in contact with the corresponding positions of the human body, the user can also adopt other postures to perform the six precordial lead measurements.

[0140] The user can use the smartwatch 1 to actively perform a multi-lead ECG test at any time using the above method. However, in some cases, the user may ignore symptoms such as chest pain, or if there is no obvious chest pain during a coronary heart disease attack, the user may miss the best time to perform an ECG test. Therefore, the embodiment of the present application proposes a data processing method that can be used to remind the user when to perform an ECG test.

[0141] In some embodiments, when the smartwatch 1 is worn on a user's body part (e.g., wrist), it can collect the user's physiological parameter values ​​in real time. The smartwatch 1 can then transmit the collected physiological parameter values ​​to a mobile phone connected to the smartwatch 1 (e.g., mobile phone 2). Mobile phone 2 analyzes the physiological parameter values ​​and issues a prompt message when it detects that changes in the physiological parameter values ​​meet certain conditions. It should be noted that the smartwatch 1 and mobile phone 2 can be connected and information can be transmitted via any method, such as Bluetooth connection and Wi-Fi connection.

[0142] In other embodiments, the above-mentioned analysis of physiological parameter values ​​and the issuance of a prompt message when a change in the physiological parameter value is detected to meet certain conditions may also be performed by the smart watch 1. That is, the smart watch 1 collects the user's physiological parameter values ​​in real time and analyzes the collected physiological parameter values. Finally, when a change in the physiological parameter value is detected to meet certain conditions, the smart watch 1 issues a prompt message to the user.

[0143] In the following embodiments, a smartwatch 1 is connected to a mobile phone 2, and physiological parameters collected in real time by the smartwatch 1 are transmitted to the mobile phone 2 for analysis, and a prompt message is issued based on the analysis results. The implementation method of the smartwatch 1 completing the collection, analysis, and issuance of prompt messages of physiological parameters can be referred to the implementation method of the embodiments of this application and will not be described in detail.

[0144] In some embodiments, the function of the mobile phone 2 obtaining physiological parameter values ​​from the smart watch 1 , analyzing the physiological parameter values ​​and issuing prompt information can be recorded as a physiological parameter monitoring function.

[0145] The data processing method proposed in the embodiment of the present application is described in detail below with reference to the accompanying drawings.

[0146] Figure 12 shows the flow of a data processing method in some embodiments. The method includes the following steps:

[0147] S301. Obtain a first parameter value corresponding to a preset physiological parameter of the user.

[0148] In an embodiment of the present application, the preset physiological parameters may include physiological parameters with characteristic changes during a coronary heart disease attack. In some embodiments, the preset physiological parameters may include at least one of the following: PWV, heart rate, HRV, blood pressure, and respiratory rate.

[0149] The preset physiological parameter includes PWV, and the corresponding first parameter value may include a PWV value.

[0150] The preset physiological parameters include heart rate, and the corresponding first parameter values ​​may include parameter values ​​such as heart rate value, heart rate increase amplitude, and heart rate decrease rate.

[0151] The preset physiological parameters include HRV, and the corresponding first parameter value may include relevant parameters of HRV, such as the standard deviation of heart beat intervals, and the proportion of consecutive heart beat interval differences exceeding 50ms.

[0152] The preset physiological parameters include blood pressure, and the corresponding first parameter values ​​may include parameter values ​​such as blood pressure value, blood pressure increase amplitude, and blood pressure decrease ratio per minute.

[0153] The preset physiological parameter includes respiratory frequency, and the corresponding first parameter value may include: respiratory frequency value.

[0154] As can be seen from the above description, when the smart watch is worn by the user on the body, it can monitor the user's physiological parameters in real time. Therefore, in the above S301, the mobile phone can obtain the first parameter value from the smart watch in real time.

[0155] When the preset physiological parameters include multiple items, the smartwatch may have different collection cycles and output frequencies for each preset physiological parameter. The process of the smartwatch collecting the parameter values ​​of all preset physiological parameters once is recorded as one cycle. In other words, within one cycle, the mobile phone can obtain the parameter value corresponding to each preset physiological parameter, but the output times corresponding to different preset physiological parameters are different. In some embodiments, in the above S301, the mobile phone can obtain the parameter value corresponding to a preset physiological parameter from the smartwatch after the smartwatch collects the parameter value corresponding to the preset physiological parameter.

[0156] In other embodiments, in S301 above, the mobile phone may also obtain the first parameter value from the smartwatch at regular intervals. In this way, the mobile phone can wait until the smartwatch completes collecting parameter values ​​corresponding to all preset physiological parameters in the same cycle (a collection process) before obtaining the first parameter value from the smartwatch. Thus, the mobile phone can simultaneously obtain the parameter value corresponding to each preset physiological parameter.

[0157] The specific implementation process of the smart watch collecting the first parameter value corresponding to the preset physiological parameter will be described in detail in the following embodiments.

[0158] S302. Obtain reference values ​​corresponding to preset physiological parameters and preset user information.

[0159] The reference value corresponding to the preset physiological parameter may be a parameter value corresponding to the user's preset physiological parameter collected when the user does not have any symptoms (such as coronary heart disease).

[0160] In some embodiments, when a user wears a smartwatch on a part of the body without suffering a coronary heart disease attack, the user can actively choose to measure a preset physiological parameter on the mobile phone, and collect the parameter value corresponding to the preset physiological parameter (which can be recorded as a second parameter value) through the smartwatch. Exemplarily, the mobile phone sends a collection instruction to the smartwatch in response to this operation of the user. So that the smartwatch responds to the collection instruction and starts collecting the parameter value corresponding to the preset physiological parameter. Afterwards, the mobile phone can obtain the parameter value corresponding to the preset physiological parameter collected by the smartwatch, that is, the above-mentioned second parameter value. Furthermore, the mobile phone can save the parameter value corresponding to the preset physiological parameter obtained at this time as a reference value of the preset physiological parameter.

[0161] Different users have different physical conditions, and the normal reference ranges of physiological parameters may be different, and the possibility of suffering from coronary heart disease is also different. The preset user information may include some physical information that may be related to coronary heart disease. In some embodiments, the preset user information may include the user's age and gender. In other embodiments, in addition to age and gender, the preset user information may also include at least one of the following: whether the user has a history of chest pain (typical chest pain type of coronary heart disease), whether the user has diabetes, whether the user has hypertension, whether the blood lipids are abnormal, and whether the user smokes. The preset user information can be entered by the user into the mobile phone and saved.

[0162] In some embodiments, the mobile phone may prompt the user to enter preset user information and collect reference values ​​corresponding to the preset physiological parameters when the user first uses the physiological parameter monitoring function of the mobile phone. Afterwards, the mobile phone may prompt the user to recollect reference values ​​of the preset physiological parameters at regular intervals (e.g., one month). Figure 14 shows the interface of the mobile phone in some embodiments, which prompts the user to enter preset user information. The interface also includes a prompt for collecting reference values ​​corresponding to the preset physiological parameters.

[0163] As shown in Figure 14, the mobile phone displays the first interface 30, which is used to enter preset user information. In the first interface 30, the user can enter information such as age, gender, whether there is a history of chest pain (typical chest pain type of coronary heart disease), whether he has diabetes, whether he has hypertension, whether he has dyslipidemia, and whether he smokes. Among them, except for age and gender, other information may be optional. The first interface 30 also includes a first control 31 for collecting reference values ​​corresponding to preset physiological parameters. In one example, after the user enters the preset user information in the first interface 30, he can trigger the first control 31 to enter the process of collecting reference values ​​corresponding to the preset physiological parameters.

[0164] In response to a user triggering the first control 31, the mobile phone may display a second interface 32. This second interface 32 may prompt the user to prepare for collecting reference values ​​for preset physiological parameters. For example, the second interface 32 may include two collection preparation steps: 1. Please wear the smartwatch as follows. 2. Please remain still for at least three minutes. The second interface 32 also provides a diagram for wearing the smartwatch. The second interface 32 also includes a second control 33, which specifically reads: "I'm ready. Start collecting." After the user correctly wears the smartwatch and remains still for three minutes, they can trigger this second control 33. In response to the user triggering the second control 33, the mobile phone may display a third interface 34, which may display a prompt stating "Collecting reference values ​​for preset physiological parameters." The mobile phone simultaneously sends a collection instruction to the smartwatch, instructing it to begin collecting the values ​​for the preset physiological parameters.

[0165] After completing the collection, the smartwatch can return the collected parameter values ​​to the mobile phone. After receiving the parameter values ​​returned by the smartwatch, the mobile phone can display a fourth interface 35; a prompt message indicating that the collection is complete can also be displayed on this fourth interface 35. Furthermore, the mobile phone can save the received parameter values ​​as reference values ​​for the preset physiological parameters.

[0166] In some embodiments, a mobile phone can implement a physiological parameter monitoring function through a preset application. The first time a user uses the physiological parameter monitoring function of the mobile phone can specifically correspond to the first time the user opens the preset application. For example, when the mobile phone detects that the user has launched the preset application for the first time, it can display a first interface 30, prompting the user to enter relevant information and collect relevant parameter values.

[0167] In order to ensure the accuracy of the reference values ​​corresponding to the preset physiological parameters, the physiological parameter values ​​of the user under normal healthy conditions are usually collected. Therefore, the reference value collection process can usually be carried out when the user is in a non-exercise state. In some embodiments, before collecting the reference values ​​corresponding to the preset physiological parameters, the mobile phone can also prompt the user on the interface (such as the second interface 32 above) to remain still for a period of time (such as 3 minutes) before starting the collection. During the collection process of the preset physiological parameters, the mobile phone can also prompt the user on the interface (such as the third interface 34 above) to remain still.

[0168] In some embodiments, the above S302 specifically indicates that the mobile phone obtains the reference value and the preset user information from a storage path for storing the reference value and the preset user information.

[0169] S303. Analyze the reference value corresponding to the preset physiological parameter, the preset user information, and the first parameter value to obtain analysis result 1.

[0170] Different physiological parameters typically have corresponding indicator ranges that represent health status, which can be recorded as normal indicator ranges. When a physiological parameter exceeds the normal indicator range, it may indicate that the body's condition is abnormal. The normal indicator range of a physiological parameter can be set based on preset user information and reference values ​​of the user's physiological parameters. In other embodiments, the normal indicator range of a physiological parameter can also be set based on empirical data of the corresponding physiological parameter.

[0171] For example, if the preset physiological parameters include PWV, the first parameter value includes the PWV value. A larger PWV value indicates a higher pulse wave velocity. Pulse wave velocity is slower when arterial elasticity is good, and faster when arterial elasticity is poor. In a non-exercise state, pulse wave velocity can, to a certain extent, reflect the elasticity of a person's arteries. Arterial elasticity is closely related to the risk of coronary artery disease; the lower the arterial elasticity, the greater the risk of coronary artery disease.

[0172] In embodiments of the present application, a smartwatch's accelerometer can be used to detect whether the user is exercising. If the user is determined to be inactive, the PWV value is measured. In some embodiments, the PWV value being within a normal range can specifically include: the PWV value being within a normal PWV range. The normal PWV range can be set based on the user's age or preset user information.

[0173] Taking the preset physiological parameters including heart rate as an example, the first parameter value may include the heart rate value, the amplitude of the heart rate increase and the rate of heart rate decrease. In a non-exercise state, the heart rate of people with chronic coronary syndrome has no obvious characteristics when no acute attack occurs. However, during an acute attack of chronic coronary syndrome, or when an acute coronary syndrome occurs, the heart rate will show characteristic changes. Common manifestations of an acute attack of chronic coronary syndrome or an acute coronary syndrome attack (hereinafter referred to as a coronary heart disease attack) include: the heart rate gradually increases during the attack, and then gradually decreases, and the amplitude of the heart rate increase and the rate of heart rate decrease both have certain characteristic manifestations. For example, the heart rate increase caused by a coronary heart disease attack lasts longer, that is, the heart rate decreases less rapidly.

[0174] In an embodiment of the present application, when it is determined that the user is in a non-exercise state, after detecting an increase in heart rate, the heart rate increase amplitude and the heart rate decrease rate during the heart rate decrease process after the heart rate increase can be analyzed.

[0175] In some embodiments, the first parameter value corresponding to the heart rate is within the normal index range, which may specifically include the following situations: ① The heart rate in a non-exercise state is within the normal heart rate index range. ② The heart rate is outside the normal heart rate index range, and the heart rate increase is less than or equal to the preset heart rate increase. ③ The heart rate is outside the normal heart rate index range, and the heart rate decrease rate is greater than or equal to the preset heart rate decrease rate. Accordingly, the first parameter value corresponding to the heart rate exceeds the normal index range, including: the heart rate increase is greater than the preset heart rate increase, and / or the heart rate decrease rate is greater than or equal to the preset heart rate decrease rate. In some specific embodiments, the preset heart rate increase can be set to 30 beats per minute (bpm). The preset heart rate decrease rate can be set to 18bpm.

[0176] Taking the preset physiological parameters including HRV as an example, the first parameter value may include relevant parameters of HRV, such as the standard deviation of heartbeat intervals and the proportion of consecutive heartbeat interval differences exceeding 50ms. The HRV of people with coronary heart disease has typical characteristics compared to the HRV of healthy people. For example, the standard deviation of the heartbeat intervals of continuously monitored HRV of people with coronary heart disease is lower, and the proportion of consecutive heartbeat interval differences exceeding 50 milliseconds (ms) also has characteristic manifestations.

[0177] In some embodiments, the first parameter value corresponding to HRV is within the normal indicator range, which may specifically include: the standard deviation of the heartbeat interval in the non-exercise state is greater than or equal to the preset heartbeat interval standard deviation value, and the proportion of consecutive heartbeat interval differences exceeding 50ms is greater than or equal to the preset proportion.

[0178] Taking the preset physiological parameter including blood pressure as an example, the first parameter value may include the blood pressure value, the blood pressure rise amplitude, and the blood pressure drop rate per minute. Blood pressure changes characteristically during a coronary heart disease attack, with common manifestations including a gradual increase in blood pressure followed by a slow decrease.

[0179] In some embodiments, the first parameter value corresponding to the blood pressure is within the normal index range, which may specifically include: in a non-exercise state, the blood pressure is within the normal blood pressure index range; or, the blood pressure is outside the normal blood pressure index range, and the blood pressure increase is less than or equal to the preset blood pressure increase; or, the blood pressure drop ratio per minute is greater than or equal to the preset blood pressure drop ratio. Accordingly, the first parameter value corresponding to the blood pressure exceeds the normal index range, including: the blood pressure increase is greater than the preset blood pressure increase, and / or the blood pressure drop ratio per minute is greater than or equal to the preset blood pressure drop ratio. In some specific embodiments, the preset blood pressure increase can be set to 20 mmHg. The preset blood pressure drop ratio can be set to 3% / minute.

[0180] For example, if the preset physiological parameter includes respiratory rate, the first parameter value may include the respiratory rate value. Coronary heart disease attacks often manifest as elevated respiratory rate. In some embodiments, the first parameter value corresponding to the respiratory rate is within a normal indicator range, which may specifically include: the respiratory rate in a non-exercise state is within a normal respiratory rate range.

[0181] In some embodiments, when the preset physiological parameters include multiple of PWV, heart rate, HRV, blood pressure, and respiratory rate, S303 can use the method in the above embodiment to compare the first parameter value corresponding to each preset physiological parameter with the corresponding normal indicator range to obtain analysis result 1. In some embodiments, analysis result 1 can be recorded as the first analysis result.

[0182] As can be seen from the description of the above embodiments, the smart watch may have different collection cycles and output frequencies for each preset physiological parameter. When the smart watch detects that the first parameter value corresponding to a preset physiological parameter has changed significantly, the other preset physiological parameters may not have been updated yet. Therefore, in some embodiments, after the mobile phone obtains the first parameter value corresponding to the preset physiological parameter (such as the first preset physiological parameter), the first parameter value can be analyzed first. If the first parameter value exceeds the corresponding normal indicator range, and the magnitude of the excess is greater than the preset magnitude (such as 20%, etc.), the mobile phone can notify the smart watch to immediately collect the first parameter values ​​corresponding to other preset physiological parameters (such as the second preset physiological parameter). Afterwards, the mobile phone can analyze the first parameter values ​​corresponding to all preset physiological parameters to obtain analysis result 1. Among them, the first preset physiological parameter includes one or more of the preset physiological parameters, and the second preset physiological parameter includes other physiological parameters other than the first preset physiological parameter.

[0183] In some embodiments, the above S303 may specifically include: inputting the reference value corresponding to the preset physiological parameter, the preset user information and the first parameter value into the preset prompt model 1 (which can be recorded as the second preset prompt model), and obtaining the output result 1 of the preset prompt model 1 (which can be recorded as the second output result). The second output result is used to characterize the probability that the user's preset physiological parameter is abnormal. The output result 1 is the above analysis result 1. Among them, the preset prompt model 1 is a model determined by training a large amount of sample data. The preset prompt model 1 can be used to evaluate whether the first parameter value is abnormal. Among them, the sample data may include the age, gender, whether there is diabetes, whether there is hypertension, whether there is dyslipidemia, whether smoking, PWV, heart rate, HRV parameters (such as SDNN, pNN50, etc.), blood pressure, respiratory rate and changes in these indicators of multiple users.

[0184] In some embodiments, the output result 1 of the preset prompt model 1 is a probability value (which can be recorded as a first probability value), which is used to represent the possibility of abnormality of the preset physiological parameter. The larger the probability value in the output result 1, the greater the possibility of abnormality of the preset physiological parameter.

[0185] S304. Determine whether analysis result 1 meets preset condition 1.

[0186] In some embodiments, analysis result 1 meets preset condition 1, which means that analysis result 1 indicates that the user's preset physiological parameters are abnormal.

[0187] In some embodiments, preset condition 1 may specifically include whether the first parameter value exceeds a normal indicator range. When the preset physiological parameter includes one item, if the first parameter value corresponding to the preset physiological parameter exceeds the normal indicator range, analysis result 1 satisfies preset condition 1. Conversely, if the first parameter value is within the normal indicator range, analysis result 1 does not meet preset condition 1.

[0188] When the preset physiological parameters include multiple parameters, preset condition 1 may specifically include whether the first parameter values ​​corresponding to multiple parameters of PWV, heart rate, HRV, blood pressure, and respiratory rate are within the normal indicator range. For example, if the first parameter values ​​corresponding to at least two of the preset physiological parameters exceed the normal indicator range, analysis result 1 satisfies preset condition 1. Conversely, if fewer than two of the preset physiological parameters have first parameter values ​​that exceed the normal indicator range, analysis result 1 does not meet preset condition 1.

[0189] In some embodiments, if the first parameter values ​​corresponding to any two or more preset physiological parameters exceed the normal indicator range, analysis result 1 may be determined to meet preset condition 1. In other embodiments, the mobile phone may also determine that analysis result 1 meets preset condition 1 when it detects that the first parameter values ​​corresponding to at least three, at least four, or all of the preset physiological parameters in analysis result 1 exceed the normal indicator range.

[0190] In the embodiment where S303 is an analysis of the reference value corresponding to the preset physiological parameter, the preset user information, and the first parameter value by the preset prompt model 1, and the output result 1 is a probability value, the above S304 may specifically include: determining whether the output result 1 is greater than a preset threshold 1 (which may be recorded as a third preset threshold). The preset threshold 1 may be determined based on the trained preset prompt model 1.

[0191] If analysis result 1 does not meet preset condition 1, it indicates that the first parameter value corresponding to the preset physiological parameter collected this time is normal; that is, the user's preset physiological parameters are normal. In this case, the mobile phone can proceed without processing. Furthermore, the mobile phone can continue to obtain new parameter values ​​corresponding to the preset physiological parameters and continue analysis. As shown in Figure 12, if the judgment result of S304 is negative, the process can return to S301 and continue.

[0192] If analysis result 1 meets preset condition 1, then analysis result 1 indicates that the user's preset physiological parameter is abnormal. At this point, the user's chest pain condition can be combined to further determine whether the abnormal preset physiological parameter is related to the target body part. In this embodiment of the present application, if the judgment result of S304 is yes, the mobile phone can execute S305.

[0193] S305. Issue prompt message 1.

[0194] In some embodiments, prompt information 1 is used to prompt the user to cooperate in entering preset data to further analyze the reference value corresponding to the preset physiological parameter, the preset user information, and the first parameter value. In some embodiments, prompt information 1 can be recorded as the first prompt information.

[0195] In some embodiments, the preset data includes sensory information of the user's target body part, and the sensory information may specifically refer to pain information.

[0196] The target body part can specifically be the chest area. In this embodiment, prompt information 1 can also be recorded as chest pain assessment prompt information. In one example, the chest pain assessment prompt information can specifically include: sound prompt information, indicator light prompt information, and / or vibration prompt information. The sound prompt information, indicator light prompt information, and vibration prompt information can be used to remind the user to check their smartwatch or mobile phone. In other embodiments, the target body part can also be other body parts.

[0197] In other embodiments, the chest pain assessment prompt information may also include image prompt information.

[0198] In other embodiments, the chest pain assessment prompt information may also include multiple items of image prompt information, sound prompt information and / or vibration prompt information.

[0199] As can be seen from the above embodiments, the physiological parameter monitoring function can be implemented specifically through a preset application. In this embodiment, the chest pain assessment prompt information can be used to remind the user to open the preset application and, based on their current physical condition, assess and input whether chest pain symptoms occur and the specific manifestations of the chest pain symptoms.

[0200] In other embodiments, when the chest pain assessment prompt information includes image prompt information, the image prompt information may also be a chest pain assessment entry window. The chest pain assessment entry window is used for the user to evaluate and input whether chest pain symptoms occur and the specific manifestations of the chest pain symptoms based on the current physical condition.

[0201] In some embodiments, S305 may specifically include: issuing a prompt message 1 via a mobile phone and / or smartwatch. In embodiments where the chest pain assessment prompt message is used to prompt the user to open a preset application and enter relevant information, the chest pain assessment prompt message issued on the mobile phone may specifically include: "Please open the preset application and enter relevant information." The chest pain assessment prompt message issued on the smartwatch may specifically include: "Please go to your mobile phone to open the preset application and enter relevant information."

[0202] Figure 15 shows an interface for issuing a prompt message 1 on a mobile phone in some embodiments. When the judgment result of S304 is yes, the mobile phone can display an image prompt message 40. The image prompt message 40 specifically includes: "An abnormality in the preset physiological parameters is detected. Do you want to open the preset application?" At the same time, the image prompt message 40 also includes two options: yes and no. When the mobile phone detects that the user triggers the yes option in the image prompt message 40, it can open the preset application and display the chest pain assessment entry page 41. The chest pain assessment entry page displays "Chest pain assessment: Please determine whether chest pain occurs based on your current physical condition." The chest pain assessment entry page 41 also includes a first option 42 and a second option 43. The first option 42 indicates that chest pain occurs, and the second option 43 indicates that chest pain does not occur.

[0203] If the mobile phone detects that the user has triggered the first option 42 on the chest pain assessment entry page 41, it means that the user is currently experiencing chest pain. Furthermore, the mobile phone can also display a chest pain symptom assessment interface 44. In the chest pain symptom assessment interface 44, the user can also be prompted: "Please select the entry that suits your situation", and several different chest pain symptoms are provided. The first chest pain symptom includes: discomfort occurring behind the sternum (including oppression, stuffiness, tightness or heaviness in the chest). The second chest pain symptom includes: duration of no more than 10 minutes. The third chest pain symptom includes: induced by exercise or emotion, which can be relieved within a few minutes after rest or medication. Among them, the chest pain symptom assessment interface 44 provides several chest pain symptoms, and the user can select one or more of them based on the current physical condition.

[0204] The chest pain symptom assessment interface 44 may further include a confirmation option 45. After the user selects an appropriate chest pain symptom item based on the current physical condition, the user may trigger the confirmation option 45 for further assessment.

[0205] In other embodiments, the chest pain symptom assessment interface may also provide the following information for the user to choose: based on the current body limb, select the location of the pain onset (behind the sternum, upper abdomen, shoulder, arm, neck, back or side chest, etc.), the nature of the pain (compression, stuffiness, tightness, heaviness, tingling or colic, etc.), the duration of the pain (less than 1 minute, 1 minute to 10 minutes or more than 10 minutes), the triggering factors of the pain (exercise, intense emotions or none), and whether it can be relieved within a few minutes after rest or medication (yes or no).

[0206] S306. Obtain the perception information of the target part input by the user.

[0207] Taking the chest area as an example, when the user checks the mobile phone according to prompt information 1 and enters whether chest pain symptoms occur and the specific manifestations of the chest pain symptoms, the mobile phone can obtain chest pain information.

[0208] In some embodiments, after the mobile phone detects the triggering operation of the second option 43 of the chest pain assessment entry page 41 shown in Figure 15, or the triggering operation of the confirmation option 45 in the chest pain symptom assessment interface 44 shown in Figure 15, the mobile phone can obtain the user's chest pain information.

[0209] S307. Analyze the reference value corresponding to the preset physiological parameter, the preset user information, the perception information of the target part, and the first parameter value to obtain analysis result 2.

[0210] In some embodiments, analysis result 2 may be recorded as a second analysis result.

[0211] In some embodiments, the above S307 may specifically include: inputting the reference value corresponding to the preset physiological parameter, the preset user information, the perception information of the target part, and the first parameter value into the preset prompt model 2 (which can be recorded as the first preset prompt model), and obtaining the output result 2 of the preset prompt model 2 (which can be recorded as the first output result). The output result 2 is the above analysis result 2. Among them, the preset prompt model 2 is a model determined by training a large amount of sample data. The preset prompt model 2 can be used to evaluate whether the target part is abnormal. The first output result is used to characterize the probability that the target body part of the user is abnormal.

[0212] In some embodiments, output 2 of the preset prompt model 2 is a probability value (which may be denoted as a second probability value), which is used to characterize the likelihood of an abnormality at the target site. A larger second probability value indicates a greater likelihood of an abnormality at the target site. In other words, the greater the likelihood that an abnormality in the preset physiological parameter is associated with chest pain.

[0213] S308. Determine whether analysis result 2 meets preset condition 2.

[0214] In some embodiments, analysis result 2 may be recorded as a second analysis result. Analysis result 2 meets preset condition 2, indicating that the target part of the user is abnormal.

[0215] In the embodiment where S307 is an analysis of the reference value corresponding to the preset physiological parameter, the preset user information, the sensory information of the target part, and the first parameter value by the preset prompt model 2, and the output result 2 is a second probability value, the above S308 may specifically include: determining whether the second probability value is greater than a preset threshold 2 (which can be recorded as the first preset threshold). The preset threshold 2 is used to represent the minimum value of an abnormality of the target part. The preset threshold 2 can be determined based on the trained preset prompt model 2.

[0216] If the analysis result 2 meets the preset condition 2, the mobile phone can execute S309.

[0217] S309. Issue prompt message 2, which is used to prompt the user to perform a preset test.

[0218] In an embodiment of the present application, prompt message 2 can be used to prompt the user to perform a preset test (such as an electrocardiogram test). The smartwatch shown in Figures 3-5 can conveniently perform electrocardiogram testing. Specifically, the prompt message 2 can prompt the user to use the smartwatch to perform an electrocardiogram test. In some embodiments, prompt message 2 can be recorded as the second prompt message.

[0219] In some embodiments, the urgency level corresponding to prompt information 2 is higher than the urgency level corresponding to prompt information 1.

[0220] In some embodiments, both prompt message 1 and prompt message 2 are in the form of sound prompts. The urgency level corresponding to prompt message 2 is higher than that corresponding to prompt message 1. Specifically, this can be manifested by the prompt duration of prompt message 2 being longer than that of prompt message 1. Alternatively, this can be manifested by the prompt volume of prompt message 2 being higher than that of prompt message 1. Alternatively, the prompt sound of prompt message 2 can be more urgent than that of prompt message 1. In this way, the user can be more intuitively informed of the urgency level.

[0221] In other embodiments, both prompt message 1 and prompt message 2 are in the form of vibration prompts. The urgency level corresponding to prompt message 2 is higher than that corresponding to prompt message 1. Specifically, this can be manifested by the vibration duration of prompt message 2 being longer than that of prompt message 1. Alternatively, the vibration amplitude of prompt message 2 can be greater than that of prompt message 1. This can more intuitively indicate the urgency level to the user.

[0222] In other embodiments, both prompt message 1 and prompt message 2 are in the form of indicator lights. The urgency level corresponding to prompt message 2 is higher than that corresponding to prompt message 1. Specifically, this can be manifested by the indicator light of prompt message 2 flashing at a higher frequency than that of prompt message 1. Alternatively, the indicator light of prompt message 2 can be brighter than that of prompt message 1. This can more intuitively indicate the urgency level to the user.

[0223] In this embodiment of the present application, the mobile phone obtains parameter values ​​corresponding to the user's preset physiological parameters collected in real time by the smartwatch and analyzes them to determine whether they meet preset condition 1. If the parameter values ​​of the preset physiological parameters meet preset condition 1, the user may be prompted to evaluate and enter chest pain information. The mobile phone then analyzes the chest pain information to determine whether it meets preset condition 2. Finally, if it determines that preset condition 2 is met, the mobile phone prompts the user to perform an electrocardiogram (ECG) test. This prevents the user from missing an ECG test due to not feeling or ignoring chest pain symptoms.

[0224] In addition, the preset prompt model 2 can also set a preset threshold 3 (which can be recorded as the second preset threshold). The preset threshold 3 is greater than the preset threshold 2. In the above S308, if the output result 2 of the preset prompt model 2 (i.e., the second probability value) is greater than the preset threshold 2, the mobile phone can continue to compare the second probability value with the preset threshold 3. Then the judgment result of S308 can be further divided into the following two cases: the first case is that the second probability value is greater than the preset threshold 2, and is less than or equal to the preset threshold 3. The second case is: the second probability value is greater than the preset threshold 2, and greater than the preset threshold 3.

[0225] In some embodiments, in the first case, S309 may specifically include: if the second probability value is greater than a preset threshold 2 and less than or equal to a preset threshold 3, issuing prompt information 2. Prompt information 2 may be used to prompt the user to perform a preset test.

[0226] In other embodiments, in the second scenario described above, the second probability value is greater than the preset threshold 3, indicating that the target body part may be abnormal. In this case, the mobile phone may issue a prompt message 3. This prompt message 3 is used to indicate that the target body part is abnormal. In some embodiments, prompt message 3 may be recorded as the third prompt message. Prompt message 3 is used to inform the user that the target body part is abnormal. The urgency level corresponding to prompt message 3 is higher than the urgency level corresponding to prompt message 2. In some embodiments, prompt message 3 may specifically be used to advise the user to seek medical treatment as soon as possible.

[0227] Alternatively, in other embodiments, when it is determined that the second probability value is greater than the preset threshold value 3, the mobile phone may also display prompt information 2 and prompt information 3 simultaneously. This allows the user to choose a treatment method, such as using a smartwatch for an ECG test or going to the hospital for treatment as soon as possible.

[0228] If analysis result 2 does not meet preset condition 2, it means that there is no abnormality in the user's target area. It may be caused by a false detection. In this case, the mobile phone can send a health reminder message.

[0229] S310. Issue health reminder information.

[0230] In some embodiments, health reminder information can be used to remind users to pay attention to their physical condition, diet, and moderate exercise. In another example, health reminder information can also be used to remind users that their mobile phone will continuously monitor changes in physiological parameters through the smartwatch. For example, health reminder information may specifically include: 1. Pay attention to symptoms in the precordial area. If you have obvious discomfort, it is recommended to seek medical attention in time. 2. Eat a healthy diet, exercise moderately, and avoid strenuous activities and emotional excitement. 3. This device will continuously monitor changes in relevant physiological parameters.

[0231] In some embodiments, after the above S309, the user can choose to start the ECG detection function according to the prompt information 1. The ECG detection function can be divided into a single-lead ECG detection function and a multi-lead ECG detection function. Referring to FIG. 13, in this embodiment, the above method further includes the following steps:

[0232] S311. In response to the start-up operation of the ECG detection function, single-lead ECG detection is performed.

[0233] S312. Obtain a first detection result of a single-lead electrocardiogram (ECG) test.

[0234] S313. If the first test result is normal, perform a multi-lead ECG test.

[0235] Furthermore, in some embodiments, the mobile phone performs a multi-lead ECG test, which may specifically include: the mobile phone first performs a first multi-lead ECG test and obtains a second test result of the first multi-lead ECG test. Then, if the second test result is normal, a second multi-lead ECG test is performed. Then, the mobile phone obtains a third test result of the second multi-lead ECG test. Finally, if the third test result is normal, it indicates that the user is normal, and the electronic device may issue a health reminder message. The multi-lead ECG test includes the first multi-lead ECG test and the second multi-lead ECG test. In this way, the user can be reminded to perform ECG tests in sequence.

[0236] Furthermore, in some embodiments, the method further includes: if the first test result is abnormal, or the second test result is abnormal, or the third test result is abnormal, the mobile phone issues a prompt message 4 (which may be recorded as a fourth prompt message). The fourth prompt message is used to indicate that the test result of the electrocardiogram test is abnormal, and the urgency corresponding to the fourth prompt message is higher than the urgency corresponding to the first prompt message.

[0237] Multi-lead ECG testing requires more complex user posture than single-lead testing. Therefore, a single-lead ECG test is performed first, followed by a multi-lead test. If the single-lead ECG result is normal, the user will be prompted to pay attention to their physical condition. The user can choose to repeat the single-lead ECG test or continue with the multi-lead ECG test. This provides greater user comfort.

[0238] The mobile phone can obtain an electrocardiogram after performing electrocardiogram detection through the smart watch in response to the user's operation. In some embodiments, the mobile phone can save the electrocardiogram according to the user's operation.

[0239] Next, the interaction process between the smart watch and the mobile phone is described in conjunction with the data processing method shown in Figure 16. A connection is established between the smart watch and the mobile phone.

[0240] S401. The mobile phone receives preset user information input by the user.

[0241] S402. The mobile phone receives an operation of measuring a preset physiological parameter triggered by the user.

[0242] In one example, the specific implementation of S401 and S402 described above may correspond to the user operation process shown in FIG14 . For example, after the user enters preset user information on the first interface 30, the mobile phone may receive the preset user information entered by the user. After the user triggers the second control 33 on the second interface 32, the mobile phone receives the user-triggered operation to measure the preset physiological parameters.

[0243] In response to the operation of measuring the preset physiological parameter, the mobile phone may execute S403.

[0244] S403. The mobile phone sends a collection instruction to the smart watch.

[0245] Correspondingly, the smart watch can receive the collection instructions sent by the mobile phone.

[0246] S404. The smart watch collects parameter values ​​corresponding to preset physiological parameters in response to the collection instruction.

[0247] In the above S404, the smartwatch collects parameter values ​​based on the user's operation on the mobile phone, which may specifically be the second parameter value in the above embodiment. The specific implementation process of the smartwatch collecting parameter values ​​corresponding to the preset physiological parameters will be described in detail in the following embodiments.

[0248] It should be noted that the parameters corresponding to the preset physiological parameters of the smart watch are executed in response to the collection instruction, and the collection instruction is issued by the mobile phone in response to the operation of measuring the preset physiological parameters triggered by the user. Usually, when the user triggers the operation of measuring the preset physiological parameters, the relevant preparations will be made, such as wearing the smart watch on the body and keeping it still for a period of time (such as 3 minutes). Therefore, after receiving the collection instruction, the smart watch can immediately start collecting the parameter values ​​corresponding to the preset physiological parameters without having to use the accelerometer to determine whether the user is in a non-motion state and maintains it for a period of time. In this way, the waiting time after the user triggers the operation of measuring the preset physiological parameters can be reduced.

[0249] S405. The smart watch sends parameter values ​​corresponding to preset physiological parameters to the mobile phone.

[0250] Correspondingly, the mobile phone receives the parameter value corresponding to the preset physiological parameter sent by the smart watch.

[0251] S406. The mobile phone saves the parameter value corresponding to the preset physiological parameter as a reference value of the preset physiological parameter.

[0252] The above steps S401-S406 may represent the interaction between a mobile phone and a smartwatch when a user first uses the physiological parameter monitoring function. In some embodiments, after the mobile phone obtains and saves the user's preset user information and the reference values ​​of the preset physiological parameters, the mobile phone can activate the physiological parameter monitoring function. The smartwatch can then monitor the user's physiological parameters in real time and transmit the physiological parameters to the mobile phone for analysis.

[0253] In the technical solution provided by the embodiments of the present application, when a user first uses the physiological parameter monitoring function, the mobile phone can obtain preset user information. Furthermore, in response to the user's operation, the mobile phone can instruct the smartwatch to collect the parameter value of the preset physiological parameter and obtain and save the parameter value as the reference value of the preset physiological parameter. This facilitates the mobile phone to assess the pre-test probability of coronary heart disease based on the reference value of the preset physiological parameter. It also facilitates the analysis of the real-time parameter value of the preset physiological parameter during subsequent physiological parameter monitoring.

[0254] After the mobile phone turns on the physiological parameter monitoring function, the interaction process between the smart watch and the mobile phone can refer to S407-S416.

[0255] S407. The smart watch collects a first parameter value corresponding to a preset physiological parameter of the user in real time.

[0256] The collection period and output frequency of different preset physiological parameters may be different.

[0257] In some embodiments, the preset physiological parameter includes PWV. Because PWV is affected by factors such as exercise status, PWV is typically measured when the user is not exercising. In some embodiments, the smartwatch can use an accelerometer to determine whether the user is exercising.

[0258] The smartwatch begins timing after the accelerometer determines the user is inactive. When the timer reaches a first preset time, PWV measurement begins. This ensures that the measured PWV value is not affected by physical activity, resulting in greater accuracy. The first preset time can be set to 3, 4, or 5 minutes, for example. PWV measurement requires collecting PPG signals over a period of time, then combining these signals to calculate PWV.

[0259] In some embodiments, the PWV measurement can be obtained using a single-lead ECG sensor and a PPG sensor. Combining the structure shown in FIG3 , it can be seen that the smartwatch is configured with a single-lead ECG sensor and a PPG sensor.

[0260] In one example, after collecting relevant parameters using a single-lead ECG sensor and a PPG sensor, PWV can be calculated using the following formula: PWV = a / t + b. Here, t1 represents the time difference between the R wave (the largest positive peak in the ECG signal) on the ECG sensor and the first subsequent peak P1 on the PPG sensor. a and b can be empirical values; in some embodiments, both a and b can be values ​​obtained through extensive data training.

[0261] Figures 17 and 18 illustrate the principle of measuring PWV using parameters acquired by a single-lead ECG sensor and a PPG sensor. PWTT is the time it takes for the arterial pulse pressure wave to travel between a peripheral site and the aortic valve. Pulse transit time (PTT) is the time it takes for a pressure wave to propagate between two arterial locations. This method can display the time between two points at an arterial location: one acquired from the ECG sensor waveform and the other from the PPG sensor waveform.

[0262] In other embodiments, PWV can be measured using a PPG sensor alone. In one example, after the PPG sensor collects relevant parameters, PWV can be calculated using the following formula: PWV = c / t2 + d. t2 is the time difference between the first peak P1 and the second peak P2 in the PPG sensor waveform. c and d are values ​​obtained through extensive data training. In another example, after the PPG sensor collects relevant parameters, PWV can be calculated through machine learning combined with analysis of the PPG sensor waveform.

[0263] In other embodiments, PWV may be measured by a PPG sensor in other ways.

[0264] In some embodiments, the smartwatch can continuously collect PPG signals through a PPG sensor and output a PWV value based on the PPG signals within a period of time (e.g., a second preset time). The second preset time can be set according to actual conditions. For example, the second preset time can be set to 10 minutes. That is, the smartwatch outputs a PWV value every 10 minutes based on the PPG signals within the 10-minute period. This method can also be referred to as the smartwatch outputting a PWV value within a collection period, where a collection period is 10 minutes. Alternatively, the smartwatch can output a PWV value every 10 minutes.

[0265] Because a smartwatch can only collect PPG signals through its PPG sensor when it's worn on the body, in some cases, the PPG sensor can't collect PPG signals without the watch being worn. Alternatively, if the smartwatch lacks proper contact with the body, the PPG signal collected by the sensor may be of low quality. In these cases, the PWV value calculated from the PPG signal may be inaccurate.

[0266] Furthermore, outputting a PWV value based on a PPG signal requires a continuous PPG signal for a period of time. For example, outputting a PWV value requires a PPG signal for at least 30 seconds.

[0267] In some specific embodiments, the smart watch collects PPG signals in real time through a PPG sensor and outputs a PWV value every 10 minutes (i.e., one collection cycle). Specifically, the smart watch selects a 30-second continuous PPG signal whose signal quality meets the quality requirements from the PPG signals collected within 10 minutes, and outputs a PWV value. The signal quality meeting the quality requirements specifically includes: the user is in a non-exercise state and lasts for more than 3 minutes. Preferably, if there are multiple groups of 30-second continuous PPG signals whose signal quality meets the quality requirements within 10 minutes, the smart watch can select a group of 30-second PPG signals with the best signal quality from them, and use this group of 30-second PPG signals to calculate and output the PWV value.

[0268] In actual situations, if no PPG signal meeting the quality requirements is collected within 10 consecutive minutes in an acquisition cycle, the PWV value within the 10 minutes may be defaulted.

[0269] In some embodiments, the preset physiological parameter includes heart rate, and the corresponding parameter value may include a heart rate value. The heart rate value can be obtained by continuous monitoring using a PPG sensor. Because heart rate is affected by factors such as exercise status, in some embodiments, measuring the heart rate value generally requires that the user be in a non-exercise state. It should be noted that the specific implementation method of measuring the heart rate value using a PPG sensor can be referred to the description in the relevant art and will not be repeated in the embodiments of this application.

[0270] Heart rate refers to the number of heartbeats per minute, measured in beats per minute. In some embodiments, a smartwatch can continuously collect PPG signals through a PPG sensor, determine and output a heart rate value every minute. At the same time, when coronary heart disease attacks, the heart rate value usually rises and then gradually decreases, and the rate of decrease in the heart rate is relatively slow. Therefore, in some embodiments, a smartwatch can record multiple heart rate values ​​over a period of time and analyze the trend of heart rate changes. Furthermore, the smartwatch can also store the trend of heart rate changes over a period of time. Furthermore, the smartwatch can calculate information such as the heart rate increase amplitude, heart rate increase rate, heart rate decrease amplitude, and heart rate decrease rate during the period at regular intervals, and send this data to the mobile phone. This facilitates the mobile phone to analyze whether the user's heart rate is abnormal based on the above information.

[0271] In other embodiments, the smartwatch can continuously send collected heart rate values ​​to the mobile phone, which can then record multiple heart rate values ​​over a period of time and analyze and store the heart rate change trend. The mobile phone can then calculate information such as the heart rate increase, heart rate increase rate, heart rate decrease, and heart rate decrease rate during that period based on the multiple heart rate values. This information allows the mobile phone to analyze whether the user's heart rate is abnormal.

[0272] When the preset physiological parameters include HRV, HRV can be continuously monitored by a PPG sensor. It should be noted that the specific implementation method of measuring HRV by a PPG sensor can refer to the description in the relevant technology and will not be repeated in the embodiments of this application.

[0273] During a coronary heart disease attack, HRV-related parameters exhibit characteristic manifestations, such as the standard deviation of heartbeat intervals and the percentage of consecutive heartbeat intervals exceeding 50ms. Both the standard deviation of heartbeat intervals and the percentage of consecutive heartbeat intervals exceeding 50ms require continuous PPG sensor monitoring over a period of time. In some embodiments, HRV-related parameters (including the standard deviation of heartbeat intervals and the percentage of consecutive heartbeat intervals exceeding 50ms) are calculated once per minute, recorded, and trended and stored.

[0274] In other embodiments, the preset physiological parameter includes blood pressure. Blood pressure can be calculated based on the PWV value calculated using a PPG sensor. Blood pressure and PWV have a positive correlation, and a conversion formula between blood pressure and PWV values ​​can be derived through data training. After obtaining the PWV value, blood pressure can be calculated using the conversion formula between blood pressure and PWV values.

[0275] Blood pressure includes systolic blood pressure (SBP) and diastolic blood pressure (DBP).

[0276] In some embodiments, the conversion formula between systolic blood pressure and PWV values ​​may include: SBP = a1 * PWV + b1. Where a1 and b1 may be values ​​determined based on big data training. The conversion formula between diastolic blood pressure and PWV values ​​may include: DBP = a2 * PWV + b2. Where a2 and b2 may be values ​​determined based on big data training.

[0277] The above method requires combining PWV values ​​with blood pressure data to determine blood pressure values. Therefore, the blood pressure collection cycle and output frequency should be the same as the PWV collection cycle and output frequency. In some specific embodiments, the smartwatch collects blood pressure data for a 10-minute period, meaning that the smartwatch outputs a blood pressure value every 10 minutes. If the PWV value within a collection cycle is missing, the blood pressure value for that collection cycle is also missing.

[0278] In other embodiments, the smartwatch can also calculate the PWV value based on 30 seconds of continuous PPG signals that meet quality requirements within 10 minutes, and then calculate the blood pressure value based on the PWV value. This can increase the frequency of blood pressure output by the smartwatch, and obtaining more blood pressure values ​​facilitates better analysis of whether the user's blood pressure is abnormal. Specifically, after detecting that the user has entered a non-exercise state for more than 3 minutes, the smartwatch obtains the PPG signal to calculate the PWV value, and thus the blood pressure value.

[0279] During a coronary heart disease attack, blood pressure typically rises and then gradually decreases, with the rate of decrease being relatively slow. Therefore, in some embodiments, a smartwatch can record multiple blood pressure values ​​over a period of time and analyze the changing trends of these values. Furthermore, the smartwatch can also store the changing trends of these values ​​over this period of time. Furthermore, the smartwatch can calculate information such as the magnitude of the blood pressure increase, the rate of increase, the magnitude of the blood pressure decrease, and the rate of decrease at regular intervals within this period of time, and send this data to the mobile phone. This information allows the mobile phone to analyze whether the user's blood pressure is abnormal.

[0280] In other embodiments, the smartwatch can continuously transmit collected blood pressure values ​​to a mobile phone, which then records multiple blood pressure values ​​over a period of time and analyzes and stores blood pressure trends. The mobile phone can then calculate information such as the magnitude of blood pressure increase, rate of increase, magnitude of blood pressure decrease, and rate of blood pressure decrease based on these multiple blood pressure values ​​over that period. This information allows the mobile phone to determine whether the user's blood pressure is abnormal.

[0281] In addition, the preset physiological parameters may also include respiratory rate, and the corresponding parameter value may include a respiratory rate value. The respiratory rate value can also be obtained by monitoring with a PPG sensor. In one example, the respiratory rate value can be calculated by using a machine learning model based on the HRV and amplitude of the PPG signal measured by the PPG. The machine learning model is trained and determined using collected sample data. Similar to heart rate monitoring, the respiratory rate value can be continuously and passively monitored, and a respiratory rate value is output every 1 minute.

[0282] When the preset physiological parameters include multiple items such as PWV, heart rate, HRV, blood pressure and respiratory rate, the smart watch can respectively use the methods in the above embodiments to collect corresponding parameter values.

[0283] S408. The smart watch sends a first parameter value corresponding to a preset physiological parameter to the mobile phone.

[0284] Correspondingly, the mobile phone can receive the first parameter value sent by the smart watch. This step may correspond to S301 in the process shown in FIG12 , that is, the mobile phone obtains the first parameter value corresponding to the preset physiological parameter.

[0285] The collection cycle and output frequency of each preset physiological parameter may be different. In some embodiments, after obtaining a first parameter value corresponding to a preset physiological parameter, the smartwatch can send the first parameter value corresponding to the preset physiological parameter to the mobile phone. For example, if the smartwatch outputs a heart rate value and respiratory rate value every minute, the smartwatch will send the heart rate value and respiratory rate value to the mobile phone once every minute. If the smartwatch outputs a PWV value and blood pressure value every 10 minutes, the smartwatch will send the PWV value and blood pressure value to the mobile phone once every 10 minutes. Furthermore, based on the heart rate values ​​within 10 minutes, the mobile phone can determine information such as the heart rate increase rate, heart rate increase amplitude, heart rate decrease amplitude, and heart rate decrease rate within 10 minutes. Respiratory rate is similar to heart rate. In addition, the mobile phone can also record, analyze, and store blood pressure values ​​over a period of time (such as 30 minutes or 1 hour) to obtain parameter values ​​such as the blood pressure increase amplitude and the blood pressure decrease ratio per minute.

[0286] In other embodiments, the smartwatch may also send the parameter values ​​of all preset physiological parameters to the mobile phone after completing a new acquisition of all preset physiological parameters. For example, the smartwatch outputs a heart rate and respiratory rate value every minute, and a PWV value and blood pressure value every 10 minutes. This means that it takes at least 10 minutes for the smartwatch to obtain new parameter values ​​for all preset physiological parameters. In this embodiment, the smartwatch may send the parameter values ​​corresponding to the preset physiological parameters to the mobile phone every 10 minutes, with each transmission including the parameter values ​​corresponding to all preset physiological parameters. During these 10 minutes, the smartwatch may record information such as the heart rate rise rate, heart rate rise amplitude, heart rate fall amplitude, and heart rate fall rate of the heart rate value. Furthermore, when the smartwatch sends the parameter values ​​corresponding to the preset physiological parameters to the mobile phone, it also transmits information such as the heart rate rise rate, heart rate rise amplitude, heart rate fall amplitude, and heart rate fall rate during the 10-minute period to the mobile phone. Respiratory rate is similar to heart rate.

[0287] S409. Obtain reference values ​​corresponding to preset physiological parameters and preset user information.

[0288] S410. Analyze the reference value corresponding to the preset physiological parameter, the preset user information, and the first parameter value to obtain analysis result 1.

[0289] S411. Determine whether analysis result 1 meets preset condition 1.

[0290] S412. Issue prompt message 1.

[0291] S413. Obtain the perception information of the target part input by the user.

[0292] S414. Analyze the reference value corresponding to the preset physiological parameter, the preset user information, the perception information of the target part, and the first parameter value to obtain analysis result 2.

[0293] S415. Determine whether analysis result 2 meets preset condition 2.

[0294] When analysis result 2 meets preset condition 2, S416 may be executed.

[0295] S416. Issue prompt message 2, which is used to prompt the user to perform a preset test.

[0296] When the analysis result 2 does not meet the preset condition 2, S417 may be executed.

[0297] S417. Issue health reminder information.

[0298] S418. In response to the start-up operation of the ECG detection function, perform single-lead ECG detection.

[0299] S419. Obtain a first detection result of a single-lead electrocardiogram (ECG) test.

[0300] S420. If the first test result is normal, perform a multi-lead ECG test.

[0301] For the specific implementation process of the above S409-S420, please refer to the description of S302-S313, which will not be repeated here.

[0302] In the technical solution provided in the embodiments of this application, a smartwatch monitors and collects the values ​​of certain physiological parameters of the user in real time and sends these values ​​to the mobile phone. The mobile phone can then use these values ​​to analyze in real time whether the user's preset physiological parameters are abnormal. Furthermore, if certain conditions are met, the mobile phone will issue a prompt message to prompt the user to perform an electrocardiogram (ECG) test. This prevents the user from missing an ECG test due to not feeling or ignoring chest pain symptoms.

[0303] Figure 19 illustrates the complete flow of data processing methods in some embodiments. During real-time monitoring of a user's physiological parameters by a mobile phone, the mobile phone may obtain preset user information, a reference value of the preset physiological parameter, and a first parameter value of the preset physiological parameter collected in real time, and input these three pieces of information into a preset prompt model 1. Preset prompt model 1 may output result 1. The mobile phone then determines whether output result 1 is greater than a preset threshold 1.

[0304] If the output result 1 is less than or equal to the preset threshold 1, it indicates that the first parameter value is normal. In this case, the system can return to re-acquire the parameter value of the preset physiological parameter and input it into the preset prompt model 1 together with the preset user information and the reference value of the preset physiological parameter, and then analyze the re-acquired parameter value.

[0305] If output result 1 is greater than a preset threshold value 1, it indicates that the preset physiological parameter is abnormal. In this case, the mobile phone may issue a prompt message 1. Prompt message 1 can be used to prompt the user to enter the preset data. For example, if the preset data is chest pain information, the user can enter the chest pain information based on prompt message 1. The mobile phone can then obtain the user's chest pain information.

[0306] The mobile phone can then input the preset user information, the reference value of the preset physiological parameter, and the first parameter value of the preset physiological parameter collected in real time, along with the chest pain information, into the preset prompt model 2. The preset prompt model 2 can output a result 2. The mobile phone can then determine whether the output result 2 is greater than a preset threshold 2.

[0307] If output result 2 is less than the preset threshold 2, it indicates that based on the preset user information, the reference value of the preset physiological parameter, the first parameter value, and the chest pain information, there is no correlation between the abnormality of the preset physiological parameter and the chest area, that is, there is no abnormality in the chest area. In this case, the mobile phone can issue some health reminder information. In some embodiments, output result 2 being less than the preset threshold 2 can also indicate that the user is less likely to have a coronary heart disease attack.

[0308] If the output result 2 is greater than the preset threshold 2 and less than or equal to the preset threshold 3, the mobile phone may send a prompt message 2. The prompt message 2 may be used to prompt the user to perform an electrocardiogram test in a timely manner.

[0309] If the output result 2 is greater than the preset threshold value 3, it indicates that based on the preset user information, the reference value of the preset physiological parameter, the first parameter value and the chest pain information, it is determined that the abnormality of the user's preset physiological parameter may be associated with the chest area. In some embodiments, the output result 2 is greater than the preset threshold value 3, indicating that the user has a high possibility of a coronary heart disease attack. At this time, the mobile phone can send a prompt message 3. Among them, the prompt message 3 can be used to prompt that the target area (i.e., the chest area) is abnormal. Furthermore, the prompt message 3 can be used to suggest that the user go to the hospital for treatment as soon as possible. In other embodiments, the output result 2 is greater than the preset threshold value 3, and the mobile phone can send prompt messages 2 and 3 at the same time for the user to choose a response method.

[0310] When the user chooses to perform an ECG test according to prompt information 2, the mobile phone can first perform a single-lead ECG test. Then, the mobile phone can obtain the test results of the single-lead ECG test. If the test results of the single-lead ECG test are normal, a six-lead ECG test (such as a six-limb lead ECG test) can be performed. The mobile phone can obtain the test results of the six-lead ECG test. If the test results of the six-lead ECG test are normal, you can enter the twelve-lead ECG test. If the test results of the twelve-lead ECG test are normal, a health reminder message will be issued. It should be noted that the twelve-lead ECG test includes ECG tests of six limb leads and six precordial leads.

[0311] If the test result of the single-lead ECG test, the six-lead ECG test, or the twelve-lead ECG test is abnormal, a prompt message 4 may be issued. This prompt message 4 may be used to inform the user that the ECG test result is abnormal. Furthermore, the prompt message 4 may also prompt the user to go to the hospital for treatment as soon as possible.

[0312] Next, referring to FIG. 20 to FIG. 22 , the interaction process between the user and the mobile phone or smart watch when the user chooses to perform an ECG test through the smart watch is explained.

[0313] FIG20 illustrates a schematic diagram of the mobile phone interface during a single-lead ECG test using a smartwatch. The guidance interface 50 shown in FIG20 uses text and images to prompt the user on the single-lead ECG test method. The guidance interface 50 also displays a prompt: "Please ensure: the detection electrode on the inside of the smartwatch strap is in good contact with one hand, and the other hand is in contact with the detection electrode on the outside of the strap." The guidance interface 50 also includes a measurement control 51. After the user wears the smartwatch according to the instructions in the guidance interface, they can trigger the measurement control 51 in the guidance interface 50.

[0314] In response to the user triggering the measurement control 51, the mobile phone can notify the smartwatch to start single-lead ECG detection. At the same time, the mobile phone can also display a measurement progress prompt interface 52 to inform the user of the total time required for the current measurement and the time measured; for example, "Total estimated time 30s, measured 15s."

[0315] After the measurement is completed, the mobile phone can determine whether the measurement result is abnormal. If the measurement result is abnormal, the mobile phone can display a result page 53. The result page 53 can specifically include a suggestion message 54: "Your test result is abnormal. It is recommended to go to the hospital for treatment as soon as possible."

[0316] If the test result of the single-lead ECG test is normal, the mobile phone may display a result page 55. The result page 55 may specifically include a test result 56: "Your test result is normal."

[0317] Furthermore, if the result of the single-lead ECG test is normal, the mobile phone can further prompt the user to proceed to the next test, such as a multi-lead ECG test. In some embodiments, the result interface 55 can also include a control for entering the next test.

[0318] FIG21 shows a schematic diagram of the mobile phone interface during a multi-lead ECG test using a smartwatch. The guidance interface 60 shown in FIG21 uses text and images to prompt the user on the multi-lead ECG test method. The guidance interface 60 also displays a prompt: "Please ensure: The detection electrodes on the inside of the smartwatch strap are in good contact with the skin of the lower limbs, and that both hands are in contact with the two detection electrodes on the outside of the strap." The guidance interface 60 also includes a measurement control 61. After the user wears the smartwatch according to the information in the guidance interface, they can trigger the measurement control 61 in the guidance interface 60.

[0319] In response to the user triggering the measurement control 61, the mobile phone can notify the smartwatch to start multi-lead ECG testing. At the same time, the mobile phone can also display a measurement progress prompt interface 62 to inform the user of the total time required for the current measurement and the time elapsed; for example, "Total estimated time 30 seconds, 15 seconds measured."

[0320] After the measurement is completed, the mobile phone can determine whether the measurement result is abnormal. If the measurement result is abnormal, the mobile phone can display a result page 63. The result page 63 can specifically include a suggestion message 64: "Your test result is abnormal. It is recommended to go to the hospital for treatment as soon as possible."

[0321] If the test result of the multi-lead ECG test is normal, the mobile phone may display a result page 65. The result page 65 may specifically include a test result 66: "Your test result is normal."

[0322] Furthermore, if the results of this multi-lead ECG test are normal, the mobile phone may prompt the user to proceed to the next test, such as the next multi-lead ECG test. In some embodiments, the above-mentioned result interface 65 may also include a control for entering the next test. As can be seen from the description of Figures 6-8, Figure 21 specifically illustrates the interactive process of testing six limb leads; the next multi-lead ECG test may be testing six precordial leads.

[0323] Figure 22 shows a schematic diagram of the mobile phone interface during a multi-lead ECG test using a smartwatch. The guidance interface 70 shown in Figure 22 uses text and images to prompt the user on the multi-lead ECG test method. The guidance interface 70 also displays a prompt: "Please ensure: The six detection electrodes on the inside of the smartwatch strap are in good contact with the six equivalent locations on the chest." The guidance interface 70 also includes a measurement control 71. After the user wears the smartwatch according to the instructions in the guidance interface, they can trigger the measurement control 71 in the guidance interface 70.

[0324] In response to the user triggering the measurement control 71, the mobile phone can notify the smartwatch to start multi-lead ECG testing. At the same time, the mobile phone can also display a measurement progress prompt interface 72 to inform the user of the total time required for the current measurement and the time measured; for example, "Total estimated time 30s, measured 15s."

[0325] After the measurement is completed, the mobile phone can determine whether the measurement result is abnormal. If the measurement result is abnormal, the mobile phone can display a result page 73. The result page 73 can specifically include a suggestion message 74: "Your test result is abnormal. It is recommended to go to the hospital for treatment as soon as possible."

[0326] If the test results of this multi-lead ECG test are still normal, the mobile phone can display the result page 75. The result page 75 may specifically include the test result 76: "Your test results are normal." In an embodiment where the mobile phone prompts the user to perform an ECG test through the physiological parameter monitoring function, if the test results of all ECG tests are normal, the mobile phone can also display health reminder information on the result page 75. Exemplarily, the health reminder information may specifically include: 1. Pay attention to the symptoms in the precordial area. If there are obvious symptoms of discomfort, it is recommended to seek medical attention in time. 2. Eat a healthy diet, exercise moderately, and avoid strenuous activities and emotional excitement. 3. This device will continue to monitor changes in relevant physiological parameters; if the symptoms worsen, you can perform an ECG measurement again or go directly to the doctor.

[0327] After completing the twelve-lead ECG test shown in Figures 21 and 22, the mobile phone can obtain the ECG waveforms obtained by the twelve-lead ECG test. The mobile phone can use relevant algorithms to determine whether the ECG waveform is abnormal. Furthermore, the mobile phone can also interpret the ECG waveform obtained by the ECG test through algorithms, and judge whether coronary heart disease or myocardial infarction has occurred by identifying typical manifestations of coronary heart disease or myocardial infarction such as ST segment elevation / depression and pathological Q waves. Alternatively, the mobile phone can also transmit the ECG waveforms of the twelve-lead ECG test to an institution with ECG interpretation capabilities such as an Internet hospital for interpretation, and then obtain the interpretation results. Finally, the mobile phone gives relevant suggestions to the user based on the final interpretation results, such as seeking medical treatment as soon as possible.

[0328] In the above embodiment, the user triggers the ECG detection process on the mobile phone. In other embodiments, the smart watch may also display guidance information to guide the user into the ECG detection process. As shown in Figure 23, after the user chooses to start the ECG detection function, the smart watch may display an interface 80. The interface includes a measurement control 81. In addition, the smart watch starts the ECG detection after detecting the user's triggering operation on the measurement control 81 (which can be a touch operation or a button operation). At the same time, the smart watch can display an interface 82 during the ECG detection process. It should be noted that the process of the smart watch performing the ECG detection function in response to the user's triggering operation on the smart watch also requires the user to contact the corresponding detection electrodes of the smart watch with the body parts corresponding to each detection electrode before it can be performed.

[0329] After completing an ECG test, the smartwatch can display a message on the smartwatch's display indicating the test is complete. In one example, the smartwatch can directly display the ECG test results on the smartwatch's display. In another example, the smartwatch can also display guidance for viewing the test results; this guidance directs the user to view the test results on their phone.

[0330] It should be noted that in an embodiment of the present application, the mobile phone can monitor the user's preset physiological parameters in real time using the method shown in FIG12 , and when the parameter values ​​corresponding to the preset physiological parameters meet certain conditions, the user is prompted to perform a chest pain symptom assessment. Furthermore, when the user selects chest pain information that matches their situation on the chest pain symptom assessment interface 44 shown in FIG15 and triggers the confirmation option 45 , the mobile phone can enter a single-lead ECG test and display the guidance interface 50 shown in FIG20 . Furthermore, if the test results are normal, the mobile phone can sequentially guide the user to perform the multi-lead ECG test shown in FIG21 and FIG22 .

[0331] In addition, the user can also actively choose to perform an ECG test through the smart watch at any time. Specifically, the user can choose to start the single-lead ECG test function on the preset application of the mobile phone. The mobile phone can also display the guidance interface 50 shown in Figure 20 to guide the user to perform a single-lead ECG test. Similarly, the user can also choose to start the multi-lead ECG test function of six limb leads on the preset application of the mobile phone. The mobile phone can also display the guidance interface 60 shown in Figure 21 to guide the user to perform a lead ECG test of six limb leads. The user can also choose to start the multi-lead ECG test function of six precordial leads on the preset application of the mobile phone. The mobile phone can also display the guidance interface 70 shown in Figure 22 to guide the user to perform a multi-lead ECG test of six precordial leads.

[0332] Alternatively, when the user actively selects to perform an ECG test on the smartwatch, they can also select to activate the corresponding ECG test function on the smartwatch. The smartwatch can display interface 80 as shown in Figure 23, which includes a measurement control 81. Furthermore, upon detecting that the user has triggered measurement control 81, the smartwatch displays interface 82.

[0333] Other embodiments of the present application provide an electronic device. The electronic device may include a memory and one or more processors. The memory is coupled to the processors. The memory is further configured to store computer program code, which includes computer instructions. When the processor executes the computer instructions, the electronic device may perform the functions or steps performed by the mobile phone in the above-described method embodiments. The structure of the electronic device may refer to the structure of electronic device 100 shown in FIG2 .

[0334] Other embodiments of the present application provide a wearable device. The wearable device may include a PPG sensor, a memory, and one or more processors. The PPG sensor and the memory are each coupled to the processor. The PPG sensor is configured to acquire parameter values ​​of preset physiological parameters. The memory is further configured to store computer program code, which includes computer instructions. When the processor executes the computer instructions, the wearable device may perform the various functions or steps performed by the smartwatch in the above-described method embodiments. The structure of the electronic device may refer to the structure of the wearable device 200 shown in FIG. 3 .

[0335] In some other embodiments, the wearable device may further include an ECG sensor, the ECG sensor being configured to detect electrocardiogram (ECG), and the ECG sensor being coupled to the processor.

[0336] In other embodiments of the present application, a communication system is provided, which includes an electronic device and a wearable device. A connection can be established between the electronic device and the wearable device, and the electronic device can obtain parameter values ​​corresponding to preset physiological parameters collected by the wearable device through the connection.

[0337] An embodiment of the present application also provides a chip system, as shown in Figure 24, the chip system 2300 includes at least one processor 2301 and at least one interface circuit 2302. The processor 2301 and the interface circuit 2302 can be interconnected via lines. For example, the interface circuit 2302 can be used to receive signals from other devices (such as a computer's memory). For another example, the interface circuit 2302 can be used to send signals to other devices (such as the processor 2301). Exemplarily, the interface circuit 2302 can read instructions stored in the memory and send the instructions to the processor 2301. When the instruction is executed by the processor 2301, the computer can execute the various steps in the above embodiment. Of course, the chip system can also include other discrete devices, and the embodiment of the present application does not specifically limit this.

[0338] An embodiment of the present application also provides a computer-readable storage medium, which includes computer instructions. When the computer instructions are executed on the above-mentioned electronic device (such as a mobile phone), the electronic device executes the various functions or steps executed by the mobile phone in the above-mentioned method embodiment.

[0339] The present application also provides a computer program product, which, when executed on a computer, enables the computer to execute the functions or steps executed by the mobile phone in the above method embodiment.

[0340] Through the description of the above implementation methods, technical personnel in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0341] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0342] Units described as separate components may or may not be physically separate, and components shown as units may be one physical unit or multiple physical units, that is, they may be located in one place or distributed in multiple places. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0343] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0344] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a readable storage medium. Based on this understanding, the technical solution of the embodiment of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a device (which can be a single-chip microcomputer, chip, etc.) or a processor (processor) to execute all or part of the steps of the various embodiments of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0345] The above content is only a specific embodiment of this application, but the scope of protection of this application is not limited to this. Any changes or replacements within the technical scope disclosed in this application should be included in the scope of protection of this application. Therefore, the scope of protection of this application should be based on the scope of protection of the claims.

Claims

1. A data processing method, characterized in that: The method is applied to an electronic device; the electronic device establishes a connection with a wearable device; the method comprises: When the wearable device is worn on a body part of a user, a first parameter value corresponding to a preset physiological parameter collected from the user by the wearable device is obtained based on the connection; the preset physiological parameter includes at least one of the following: pulse wave velocity PWV, heart rate, heart rate variability HRV, blood pressure, and respiratory rate; Analyze the first parameter value to obtain a first analysis result; The first analysis result indicates that the preset physiological parameter of the user is abnormal, and a first prompt message is issued, wherein the first prompt message is used to prompt the user to cooperate in entering preset data so as to perform a new analysis on the preset physiological parameter.

2. The method according to claim 1, characterized in that The preset data includes the perception information of the target body part of the user; After sending the first prompt information, the method further includes: Acquiring the perception information of the target body part input by the user; Analyzing the sensed information of the target body part and the first parameter value to obtain a second analysis result; The second analysis result indicates that the target body part of the user is abnormal, and a second prompt message is issued; the second prompt message is used to prompt the user to perform a preset test through the wearable device.

3. The method according to claim 2, characterized in that The analyzing the sensed information of the target body part and the first parameter value to obtain a second analysis result includes: Inputting the perception information of the target body part and the first parameter value into a first preset prompt model; the first preset prompt model is determined through training; Obtaining a first output result of the first preset prompt model; the first output result is used to characterize the probability that the target body part of the user is abnormal; the second analysis result includes the first output result; The second analysis result indicates that the target body part of the user is abnormal, and a second prompt message is issued, including: The first output result is greater than a first preset threshold and less than or equal to a second preset threshold, and the second prompt information is issued; wherein the second preset threshold is greater than the first preset threshold.

4. The method according to claim 3, characterized in that The method further comprises: The first output result is greater than the second preset threshold, and a third prompt message is issued; the third prompt message is used to prompt the user that the target body part is abnormal, and the urgency corresponding to the third prompt message is higher than the urgency corresponding to the second prompt message.

5. The method according to any one of claims 1 to 4, characterized in that The step of analyzing the first parameter value to obtain a first analysis result includes: Inputting the first parameter value into a second preset prompt model; the second preset prompt model is determined through training; Obtaining a second output result of the second preset prompt model; the second output result is used to characterize the probability that the preset physiological parameter of the user is abnormal; the first analysis result includes the second output result; The first analysis result indicates that the preset physiological parameter of the user is abnormal, and includes: the second output The result is greater than a third preset threshold.

6. The method according to any one of claims 1 to 4, characterized in that The electronic device stores reference values ​​corresponding to the preset physiological parameters and preset user information; The step of analyzing the first parameter value to obtain a first analysis result includes: The reference value, the preset user information, and the first parameter value are analyzed to obtain a first analysis result.

7. The method according to claim 6, characterized in that The analyzing the reference value, the preset user information, and the first parameter value to obtain a first analysis result includes: Determine the normal indicator range corresponding to the preset physiological parameter by combining the reference value and the preset user information; Determining whether the first parameter value corresponding to the preset physiological parameter exceeds the corresponding normal indicator range; The first analysis result indicates that the preset physiological parameter of the user is abnormal, including: At least the first parameter value corresponding to the preset physiological parameter of the preset item exceeds the corresponding normal indicator range.

8. The method according to claim 7, characterized in that Different preset physiological parameters correspond to different value output frequencies; analyzing the first parameter value to obtain a first analysis result includes: Analyzing the first parameter values ​​obtained in the same cycle to obtain a first analysis result; the electronic device obtains the parameter value corresponding to each of the preset physiological parameters in the same cycle; The method further includes: when it is detected that a first parameter value corresponding to a first preset physiological parameter exceeds the corresponding normal indicator range, immediately acquiring a third parameter value corresponding to a second preset physiological parameter through the wearable device; the first preset physiological parameter includes one or more of the preset physiological parameters, and the second preset physiological parameter includes other physiological parameters except the first preset physiological parameter; Analyze the reference value, the preset user information, the first parameter value corresponding to the first preset physiological parameter, and the third parameter value to obtain a third analysis result; The third analysis result indicates that the preset physiological parameter of the user is abnormal, and the first prompt information is issued.

9. The method according to any one of claims 2 to 4, characterized in that: After sending the second prompt information, the method further includes: In response to the start-up operation of the ECG detection function, single-lead ECG detection is performed; Obtaining a first detection result of the single-lead electrocardiogram detection; If the first detection result is normal, a multi-lead ECG detection is performed.

10. The method according to claim 9, characterized in that The multi-lead ECG detection includes: Performing a first multi-lead ECG test; the multi-lead ECG test includes the first multi-lead ECG test; Obtaining a second detection result of the first multi-lead electrocardiogram detection; If the second detection result is normal, performing a second multi-lead ECG detection; the multi-lead ECG detection includes the second multi-lead ECG detection; Obtaining a third test result of the second multi-lead ECG test; If the third test result is normal, a health reminder message is issued.

11. The method according to claim 10, characterized in that The method further comprises: If the first detection result is abnormal, or the second detection result is abnormal, or the third detection result, a fourth prompt message is issued; the fourth prompt message is used to prompt that the detection result of the electrocardiogram detection is abnormal; the urgency corresponding to the fourth prompt message is higher than the urgency corresponding to the first prompt message.

12. The method according to any one of claims 2 to 4, characterized in that: The electronic device stores reference values ​​corresponding to the preset physiological parameters and preset user information; The analyzing the sensed information of the target body part and the first parameter value to obtain a second analysis result includes: The reference value, the preset user information, the perception information of the target body part and the first parameter value are analyzed to obtain a second analysis result.

13. A data processing method, characterized in that: The method is applied to a wearable device, and the wearable device establishes a connection with an electronic device; the method comprises: When the wearable device is worn on a body part of a user, collecting a first parameter value corresponding to a preset physiological parameter of the user; The first parameter value is sent to the electronic device through the connection; the first parameter value is used by the electronic device to analyze the first parameter value to obtain a first analysis result; and when the first analysis result indicates that the preset physiological parameter of the user is abnormal, a first prompt message is issued, and the first prompt message is used to prompt the user to cooperate in entering preset data to perform a new analysis on the preset physiological parameter.

14. A data processing method, characterized in that: The method is applied to a wearable device; the method comprises: When the wearable device is worn on a body part of a user, a first parameter value corresponding to a preset physiological parameter of the user is collected; the preset physiological parameter includes at least one of the following: pulse wave velocity PWV, heart rate, heart rate variability HRV, blood pressure, and respiratory rate; Obtaining reference values ​​corresponding to the preset physiological parameters and preset user information; Analyze the first parameter value to obtain a first analysis result; The first analysis result indicates that the preset physiological parameter of the user is abnormal, and a first prompt message is issued, wherein the first prompt message is used to prompt the user to cooperate in entering preset data so as to perform a new analysis on the preset physiological parameter.

15. An electronic device, characterized in that: The electronic device comprises: a processor and a memory; the memory is coupled to the processor; the memory stores computer program code, the computer program code comprises computer instructions, and when the computer instructions are executed by the processor, the electronic device executes the method as described in any one of claims 1 to 12, or the method as described in claim 14.

16. A wearable device, characterized in that: The wearable device comprises: a photoplethysmography (PPG) sensor, a processor and a memory; the PPG sensor and the memory are respectively coupled to the processor; The PPG sensor is used to collect parameter values ​​corresponding to preset physiological parameters; the memory stores computer program code, and the computer program code includes computer instructions. When the computer instructions are executed by the processor, the wearable device executes the method as claimed in claim 13.

17. The wearable device according to claim 16, characterized in that: The wearable device also includes an electrocardiogram (ECG) sensor, which is coupled to the processor; the ECG sensor is used for performing electrocardiogram (ECG) detection.

18. A communication system, characterized in that: The communication system comprises the electronic device as claimed in claim 15 and the wearable device as claimed in claim 16 or 17; the electronic device establishes a connection with the wearable device.

19. A computer-readable storage medium, characterized in that: The method comprises computer instructions, which, when executed on an electronic device, cause the electronic device to execute the method according to any one of claims 1 to 12, or the method according to claim 14.

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