Data processing method and device for chest pain user, equipment and storage medium

Abstract

The invention discloses a data processing method and device for a chest pain user, equipment and a storage medium, and the method comprises the steps: obtaining the physical sign information of the user through wearable equipment, and detecting whether the physical sign of the user is abnormal or not according to the physical sign data; if the physical sign of the user is abnormal, detecting whether the heart rate of the user is abnormal or not according to heart rate data in the physical sign information; if yes, acquiring chest pain abnormal characteristics of the user, and generating a medical treatment planning scheme according to the chest pain abnormal characteristics; and determining medical treatment prompt information according to the medical treatment planning scheme. According to the application, a scheme for processing related data of the chest pain user before definite diagnosis and treatment is provided.

Description

Technical Field

[0001] The present invention relates to the technical field of the Internet of Things, and in particular to a data processing method, device, equipment and storage medium for users with chest pain. Background Art

[0002] In real life, the treatment of chest pain patients is very complicated. The cause of chest pain is difficult to determine before arriving at the hospital, and some ambulances and hospitals do not have perfect emergency facilities, which may delay the patient's treatment time and perform unnecessary operations. Therefore, there is an urgent need for a solution to process the relevant data of chest pain users before diagnosis and treatment. Summary of the invention

[0003] The purpose of the present invention is to provide a data processing method, device, equipment and storage medium for users with chest pain, aiming to provide a solution for processing relevant data of users with chest pain before diagnosis and treatment.

[0004] Other features and advantages of the present application will become apparent from the following detailed description, or may be learned in part by the practice of the present application.

[0005] According to one aspect of an embodiment of the present application, a data processing method for a user with chest pain is provided, comprising:

[0006] Acquire the user's physical sign information through a wearable device, and detect whether the user's physical sign is abnormal according to the physical sign data;

[0007] If the user's physical sign is abnormal, detecting whether the user's heart rate is abnormal according to the heart rate data in the physical sign information;

[0008] If abnormal, obtain the abnormal chest pain characteristics of the user, and generate a medical treatment plan based on the abnormal chest pain characteristics;

[0009] Determine medical consultation reminder information according to the medical consultation planning scheme.

[0010] Further, detecting whether the user's physical sign is abnormal according to the physical sign data includes:

[0011] Detecting whether a first heart rate value in the vital sign data belongs to a preset value range, and detecting whether blood oxygen data in the vital sign data is less than a blood oxygen threshold;

[0012] If the first heart rate value does not belong to the preset value range or the blood oxygen data is less than the blood oxygen threshold, it is determined that the user's physical signs are abnormal.

[0013] Further, detecting whether the user's heart rate is abnormal according to the heart rate data in the physical sign information includes:

[0014] The heart rate data within a preset time period is used as the target heart rate data, and the heart rate pulse data and the second heart rate value in the target heart rate data are obtained;

[0015] Detecting whether the heart rate pulse data is less than a pulse threshold, and detecting whether the second heart rate value is less than a heart rate threshold;

[0016] If the heart rate pulse data is less than the pulse threshold, and the second heart rate value is less than the heart rate threshold, it is determined that the user's heart rate is abnormal.

[0017] Furthermore, the abnormal chest pain characteristics include a first chest pain characteristic reported by the user and a second chest pain characteristic diagnosed.

[0018] Furthermore, generating a medical treatment plan according to the abnormal chest pain characteristics includes:

[0019] The danger signal characteristic values ​​of the first chest pain characteristic and the second chest pain characteristic that the user meets are accumulated, and the medical treatment planning plan is determined based on the accumulated result.

[0020] Furthermore, the medical treatment planning plan includes at least one item of hospital, ambulance, route and transportation time.

[0021] Furthermore, before obtaining the user's vital sign information through the wearable device, the method further includes:

[0022] Acquire facial information of the user through the wearable device, and extract key facial areas based on the facial information;

[0023] Checking whether the user exists in a user database based on the facial key area;

[0024] If not present, obtain user information and store the user information in the user database.

[0025] According to one aspect of an embodiment of the present application, a data processing device for a user with chest pain is provided, comprising:

[0026] A first detection module is configured to obtain the user's physical sign information through a wearable device, and detect whether the user's physical sign is abnormal according to the physical sign data;

[0027] A second detection module is configured to detect whether the user's heart rate is abnormal according to the heart rate data in the physical sign information if the user's physical sign is abnormal;

[0028] A generation module is configured to obtain abnormal chest pain characteristics of the user if abnormal, and generate a medical treatment plan according to the abnormal chest pain characteristics;

[0029] The determination module is configured to determine the medical consultation reminder information according to the medical consultation planning scheme.

[0030] According to one aspect of an embodiment of the present application, an electronic device is provided, comprising: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the electronic device implements the data processing method for users with chest pain as described above.

[0031] According to one aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which computer-readable instructions are stored. When the computer-readable instructions are executed by a processor of a computer, the computer executes the data processing method for users with chest pain as described above.

[0032] According to one aspect of an embodiment of the present application, a computer program product or a computer program is provided, the computer program product or the computer program including computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the data processing method for chest pain users provided in the above-mentioned various optional embodiments.

[0033] In the data processing method, device, equipment and storage medium for chest pain users provided in the embodiments of the present application, the user's physical sign information is obtained through a wearable device, and whether the user's physical sign is abnormal is detected based on the physical sign data. After detecting that the user's physical sign is abnormal, whether the user's heart rate is abnormal is detected based on the heart rate data in the physical sign information. After detecting that the user's heart rate is abnormal, the user's chest pain abnormal characteristics are obtained, and a medical treatment plan is generated based on the chest pain abnormal characteristics, and medical treatment prompt information is determined based on the medical treatment plan. Through the technical solution provided by this application, the relevant data of the chest pain user can be processed before diagnosis and treatment.

[0034] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The drawings herein are incorporated into the specification and constitute a part of the specification, showing embodiments consistent with the present application, and together with the specification, are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0036] Figure 1 A flowchart of a data processing method for chest pain users provided in this application;

[0037] Figure 2 Schematic diagram of a first-order derivative signal of a complete cycle of a pulse wave involved in an embodiment of the present invention;

[0038] Figure 3 is a block diagram of a data processing device for chest pain users involved in the present application;

[0039] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown. DETAILED DESCRIPTION

[0040] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0041] Here, exemplary embodiments will be described in detail, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are only examples of devices and methods consistent with some aspects of the present application as detailed in the attached claims.

[0042] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0043] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0044] It should also be noted that the "multiple" mentioned in this application refers to two or more than two. "And / or" describes the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship.

[0045] Figure 1 FIG. 1 is a flow chart showing a data processing method for a user suffering from chest pain according to an exemplary embodiment. Figure 1 As shown, in an exemplary embodiment, the data processing method for chest pain users may include steps S110 to S140, which are described in detail as follows:

[0046] Step 110, obtaining the user's physical sign information through the wearable device, and detecting whether the user's physical sign is abnormal based on the physical sign data.

[0047] In the embodiment of the present application, the wearable device uses photoplethysmograph (PPG) to measure heart rate and other biometric indicators as the user's vital signs. PPG is a method of shining light into the skin and measuring light scattering caused by blood flow. Photoplethysmograph is a non-invasive detection method for detecting blood volume changes in living tissues by photoelectric means. When a light beam of a certain wavelength is irradiated on the surface of the skin, the light beam is transmitted to the photoelectric receiver by transmission or reflection. In this process, due to the absorption attenuation of the fingertip skin muscle and blood, the detector detects that the light intensity will be weakened. The absorption of light by the skin, muscle tissue, etc. remains constant throughout the blood circulation, while the blood volume in the skin changes pulsatingly under the action of the heart. When the heart contracts, the peripheral blood volume is the largest, the light absorption is also the largest, and the detected light intensity is the smallest; while when the heart is diastolic, on the contrary, the detected light intensity is the largest, so that the light intensity received by the light receiver changes pulsatingly. The solvent pulse blood flow can be obtained by converting this light intensity change signal into an electrical signal to obtain data.

[0048] The wearable device is provided with an optical heart rate sensor, which is provided with a light transmitter, an accelerometer and a corresponding algorithm.

[0049] Specifically, the light emitter is usually composed of at least two light emitting diodes (LEDs), which shine light waves into the skin. These components, the photodiode and the analog front end (AFE), capture the light refracted by the wearer and convert these analog signals into digital signals for calculating heart rate data that can be applied practically;

[0050] The accelerometer measures motion and is used in conjunction with the light signal as input to the PPG algorithm.

[0051] Algorithms process signals from the AFE and accelerometer and then overlay the processed signals onto the PPG waveform, thereby generating continuous, motion-tolerant heart rate data and other biometric data.

[0052] Detect whether the user's physical signs are abnormal based on the acquired physical sign data.

[0053] Step 120: If the user's physical sign is abnormal, detect whether the user's heart rate is abnormal based on the heart rate data in the physical sign information.

[0054] In the embodiment of the present application, if it is detected that the user's physical signs are abnormal, it is further detected whether the user's heart rate is abnormal based on the heart rate data in the physical sign information.

[0055] Step 130: If abnormal, obtain the abnormal chest pain characteristics of the user, and generate a medical treatment plan based on the abnormal chest pain characteristics.

[0056] In an embodiment of the present application, if an abnormal heart rate of the user is detected, the abnormal chest pain characteristics of the user are obtained, and a medical treatment plan is generated based on the abnormal chest pain characteristics. The medical treatment plan records relevant plans for medical treatment, such as the hospital to be treated, the route to the hospital, etc.

[0057] Step 140, determining medical consultation reminder information according to the medical consultation planning scheme.

[0058] In the embodiment of the present application, after the user arrives at the hospital, the data is refreshed and the user is determined to need super emergency treatment based on the time of arrival of the user.

[0059] The corresponding treatment analysis index is determined according to the user's treatment time. If a basic treatment time is set, the quotient between the user's instructions and the basic treatment time is used as the treatment analysis index. When the treatment analysis index corresponding to the time when the user first receives treatment is greater than 1, a "urgent consultation required" medical reminder message will be generated and displayed in the emergency and thoracic specialist clinics; when the user's treatment analysis index is greater than 0.5 and less than 1, a "consultation required" medical reminder message will be generated and displayed in the emergency room and thoracic department; when the user's treatment analysis index is greater than 0 and less than 0.5, a "urgent treatment required" medical reminder message will be generated and displayed in the emergency room.

[0060] In an exemplary embodiment of the present application, the detecting whether the user's physical sign is abnormal according to the physical sign data includes the following steps, which are described in detail as follows:

[0061] Detecting whether a first heart rate value in the vital sign data belongs to a preset value range, and detecting whether blood oxygen data in the vital sign data is less than a blood oxygen threshold;

[0062] If the first heart rate value does not belong to the preset value range or the blood oxygen data is less than the blood oxygen threshold, it is determined that the user's physical signs are abnormal.

[0063] In the embodiment of the present application, the LED light on the wearable device is directed to the skin, and the light reflected back through the skin tissue is received by the photosensitive sensor and converted into an electrical signal, which is then converted into a digital signal through AD. Through the illumination of the flash, a light beam with a wavelength range (green light (500nm) to yellow light (600nm) that enters the skin tissue is mostly absorbed by red blood cells) is irradiated to the surface of the user's fingertips and collected at a frequency of one minute. The contraction and expansion of blood vessels will affect the transmission of light, thereby reflecting the user's heart rate information.

[0064] Whether the first heart rate value in the vital sign data belongs to the first preset value range, and whether the blood oxygen data in the vital sign data belongs to the second preset value range. The first preset value range can be set to 60 to 100. When the user's heart rate value is measured to be between 60-100, it is determined that the user's heart rate is within the normal range, and the user is in asymptomatic mode or healthy.

[0065] The red light with a wavelength range of 660nm and the near-infrared light with a wavelength of 940nm are used as the input light source to penetrate into the user's skin, thereby obtaining the user's blood oxygen data and detecting whether the user's blood oxygen data is less than the blood oxygen threshold, which can be set to 80%. When the blood oxygen value is greater than or equal to the blood oxygen threshold, the lung function is healthy and the user is in asymptomatic mode or healthy mode.

[0066] When the first heart rate value does not belong to the preset value range or the blood oxygen data is less than the blood oxygen threshold, it is determined that the user's physical signs are abnormal.

[0067] When the test is completed, the measured data is uploaded to the hospital's cloud server for real-time synchronization. When in an abnormal stage, it helps users to alert the hospital. After the alarm, the user's medical history and other data in the hospital database are extracted to conduct convenient treatment analysis for the user.

[0068] In an exemplary embodiment of the present application, the detecting whether the user's heart rate is abnormal according to the heart rate data in the physical sign information includes the following steps, which are described in detail as follows:

[0069] The heart rate data within a preset time period is used as the target heart rate data, and the heart rate pulse data and the second heart rate value in the target heart rate data are obtained;

[0070] Detecting whether the heart rate pulse data is less than a pulse threshold, and detecting whether the second heart rate value is less than a heart rate threshold;

[0071] If the heart rate pulse data is less than the pulse threshold, and the second heart rate value is less than the heart rate threshold, it is determined that the user's heart rate is abnormal.

[0072] In the embodiment of the present application, the second heart rate data of the user is analyzed by the PLUS101 chip, such as Figure 2 As shown in the figure, in the first-order derivative signal of a complete cycle of the pulse wave, there are four characteristic points A, B, C, and D. A is the start time of the cycle. B is the peak value in the cycle. Point B is the main peak and maximum value point of the PPG signal, and it is also a maximum value point. In the first-order derivative signal of the PPG signal, it corresponds to a zero-crossing point N from positive to negative. C is the minimum value point between the B and D signals, and D is the second peak value after the B order of a signal cycle.

[0073] Xl(n) is the first-order difference sequence of the PPG signal sequence. When Xl(nN)>0 and Sd(nN+1)<0, nN is the maximum point of Xl(n).

[0074] Point B is determined to be heart rate pulse data, the pulse threshold can be set to 5, the preset time period can be set to 1 minute, and the heart rate threshold is set to 60. It is detected whether the heart rate pulse data is less than the pulse threshold, and whether the second heart rate value is less than the heart rate threshold. When the heart rate pulse data is less than the pulse threshold, and the second heart rate value is less than the heart rate threshold, it is determined that the user's heart rate is abnormal.

[0075] In an exemplary embodiment of the present application, the abnormal chest pain characteristics include a first chest pain characteristic reported by the user and a diagnosed second chest pain characteristic.

[0076] In the embodiment of the present application, the abnormal chest pain characteristics include a first chest pain characteristic that can be clearly identified by the user, and its corresponding danger signal characteristic value is 1, and also include a second chest pain characteristic that cannot be clearly identified by the user and requires initial treatment and analysis to obtain, and its corresponding danger signal characteristic value is 2.

[0077] The first chest pain characteristics include: stable chest pain, chest pain accompanied by back pain and abdominal pain, chest pain aggravated by breathing, coughing, changing body position, and swallowing, accompanied by tachycardia and severe dyspnea.

[0078] Secondary chest pain characteristics include: severe pain, sudden onset, tearing, sharp nature of the pain, new aortic regurgitation murmur, pericardial rub, other clinical signs of Marfan syndrome, known history of aortic valve disease, known history of thoracic aortic aneurysm, recent history of myocardial infarction, and recent history of cardiovascular surgery.

[0079] In an exemplary embodiment of the present application, generating a medical treatment plan according to the abnormal chest pain characteristics includes the following steps, which are described in detail as follows:

[0080] The danger signal characteristic values ​​of the first chest pain characteristic and the second chest pain characteristic that the user meets are accumulated, and the medical treatment planning plan is determined based on the accumulated result.

[0081] In the embodiment of the present application, the danger signal characteristic values ​​corresponding to the first chest pain characteristic and the second chest pain characteristic that the user meets are accumulated, and then the medical treatment plan is determined based on the accumulated results.

[0082] In an exemplary embodiment of the present application, the medical treatment planning plan includes at least one item of a hospital, an ambulance, a route, and a transportation time.

[0083] In the embodiment of the present application, the hospital planning is to call the user's heart rate information in the hospital database, and then analyze the user's data. When the result of the accumulated dangerous information characteristic value exceeds the dangerous threshold, it is analyzed whether the user needs to go to a hospital with PCI treatment or a hospital without PCI for treatment. When the result of the accumulated dangerous information characteristic value is greater than 2, the user is sent to a hospital that can perform PCI treatment for treatment.

[0084] In the planning of ambulances, when the danger signal characteristic value signal is equal to 1, an ordinary ambulance is called; when the danger signal characteristic value signal is greater than 1, an advanced ambulance with special equipment is called.

[0085] The route planning is based on the analysis of the hospitals identified above, and data analysis is performed to determine the best route for users to go to the hospital.

[0086] The hospital's location information and the patient's location information are called up to plan the patient's path based on the patient's "first pre-hospital medical treatment time and extent" and the DIDO of the transfer hospital.

[0087] Based on traffic information, calculations are performed to find the path that the vehicle can travel efficiently. Multiple route nodes are set from the time the user gets on the car to the hospital. The user node calculation is:

[0088] L=(T1-......-T0) / (S0-......-S1)

[0089] Among them, T1 is the location of the target hospital, T0 is the initial location of the user (there are multiple location nodes along the path, and the path distance is calculated according to different nodes), S0 is the maximum treatment time, and S1 is the user's usage time.

[0090] Priority sorting: shortest path > medium distance path > long distance path. The larger the L value, the higher the priority of the route. Through intelligent comparison and analysis, the fastest path is selected for display.

[0091] For example:

[0092] L1 = ("T1"; "1500M" - "T1.1; 200M" - "T1.2"; "100M" - "T0"; "0M") / ("S0"; "6MIN" - "S1."1"; 2MIN" - "S1.2"; "1MIN" - "S1"; "0MIN") = 400 (the shortest path);

[0093] L1.1=("T1";"1500M"-"T1.1;400M"-"T1.2";"300M"-"T0";"0M") / ("S0";"15MIN"-"S1.1";"4MIN"-"S1.2";"3MIN"-"S1";"0MIN")=100.

[0094] Among them, L1 is the shortest path.

[0095] In planning the delivery time, if a short route on the map is chosen, the vehicle may be caught in a traffic jam and the vehicle may not reach the destination as quickly as possible. Therefore, by adding traffic information to the route to calculate the route, even if the vehicle's route is long, it can avoid congestion as much as possible, so that the vehicle can reach the destination as early as possible.

[0096] In an exemplary embodiment of the present application, before obtaining the user's vital sign information through the wearable device, the method further includes:

[0097] Acquire facial information of the user through the wearable device, and extract key facial areas based on the facial information;

[0098] Checking whether the user exists in a user database based on the facial key area;

[0099] If not present, obtain user information and store the user information in the user database.

[0100] In an embodiment of the present application, a user's underlying diseases are recorded by identifying the user's facial information and storing the user's personal information.

[0101] When the patient feels irregular heartbeat, difficulty breathing or other symptoms, the photoelectric solvent pulse recording method is used to monitor the patient's heart rate through the mobile phone and smart watch at the same time. After the user's authorization, the individual's registered information is stored in the hospital's user database.

[0102] The user's facial information is obtained by capturing a portrait through the front camera of the wearable device. The facial information can be captured in real time or stored by the user in the wearable device. The key areas in the facial information are extracted. The key areas include the area between the eyebrows, the nose and cheeks, and the jaw area. The key areas of the user are compared with the key areas of the users in the user database to obtain the contrast scores corresponding to each key area. The contrast scores of each key area are summed, and based on the summed structure, it is determined whether the user exists in the user database. Specifically, when the contrast score between the user and the user in the user database is greater than the contrast threshold, it can be determined that the user exists in the user database.

[0103] In an exemplary embodiment of the present application, after receiving the patient, the medical staff urgently collects the stored relevant data of the user, confirms the result of the accumulation of the user's dangerous information characteristic value, obtains the user's ECG electrocardiogram, and analyzes the patient's cause of disease through the PLUS101 chip. If the user is judged to have ST-segment elevation myocardial infarction, the drug injection should be performed immediately, and the early MONA+ticagrelor 180mg / clopidogrel 300mg / 600mg should be injected. If there is no improvement, PCI treatment is performed.

[0104] Patients with symptoms lasting <12 hours were eligible for primary PCI.

[0105] When the user's symptoms last between 12 hours and 24 hours, there is still evidence of ischemia, cardiogenic shock or severe acute heart failure, and thrombolysis is contraindicated or fails.

[0106] The conditions for thrombolytic therapy are: FMC-D>90min / / (time of first FMC treatment; D hospital gate)

[0107] The conditions for transferring from a non-PCI hospital to a PCI hospital are: FMC-D ≤ 90 minutes, DIDO (Door in-Door out) ≤ 30 minutes

[0108] The technical solution provided by the present application can achieve rapid treatment and efficient collaborative work for users with chest pain. By monitoring the symptoms, physiological indicators, and vital signs of users with chest pain, data is transmitted to the medical treatment system in real time. Based on the received data, the medical treatment system automatically analyzes the severity of the user's condition and generates a corresponding treatment plan. At the same time, the medical treatment system can communicate in real time with emergency vehicles, hospital emergency departments and other relevant departments to ensure that users with chest pain can receive rapid treatment. The present application provides a fast and efficient data processing method for users with chest pain, which can greatly shorten the treatment time for users with chest pain and improve the treatment effect.

[0109] In an exemplary embodiment of the present application, see Figure 3 , Figure 3 A data processing device for a user with chest pain is shown according to an exemplary embodiment, comprising:

[0110] The first detection module 310 is configured to obtain the user's physical sign information through the wearable device, and detect whether the user's physical sign is abnormal according to the physical sign data;

[0111] The second detection module 320 is configured to detect whether the user's heart rate is abnormal according to the heart rate data in the physical sign information if the user's physical sign is abnormal;

[0112] The generating module 330 is configured to obtain the abnormal chest pain characteristics of the user if abnormal, and generate a medical treatment plan according to the abnormal chest pain characteristics;

[0113] The determination module 340 is configured to determine the medical consultation reminder information according to the medical consultation planning scheme.

[0114] In an exemplary embodiment of the present application, the first detection module 310 includes:

[0115] A first detection submodule is configured to detect whether a first heart rate value in the vital sign data belongs to a preset value range, and detect whether blood oxygen data in the vital sign data is less than a blood oxygen threshold;

[0116] The first determination submodule is configured to determine that the user's physical signs are abnormal if the first heart rate value does not belong to a preset value range or the blood oxygen data is less than the blood oxygen threshold.

[0117] In an exemplary embodiment of the present application, the second detection module 320 includes:

[0118] An acquisition submodule is configured to use the heart rate data within a preset time period as target heart rate data, and acquire the heart rate pulse data and the second heart rate value in the target heart rate data;

[0119] a second detection submodule, configured to detect whether the heart rate pulse data is less than a pulse threshold, and to detect whether the second heart rate value is less than a heart rate threshold;

[0120] The second determination submodule is configured to determine that the user's heart rate is abnormal if the heart rate pulse data is less than the pulse threshold and the second heart rate value is less than the heart rate threshold.

[0121] In an exemplary embodiment of the present application, the abnormal chest pain characteristics include a first chest pain characteristic reported by the user and a diagnosed second chest pain characteristic.

[0122] In an exemplary embodiment of the present application, the generating module 330 includes:

[0123] The accumulation submodule is configured to accumulate the danger signal characteristic values ​​of the first chest pain characteristic and the second chest pain characteristic that the user meets, and determine the medical treatment planning plan based on the accumulation result.

[0124] In an exemplary embodiment of the present application, the medical treatment planning plan includes at least one item of hospital, ambulance, route, and transportation time.

[0125] In an exemplary embodiment of the present application, the data processing device for a user with chest pain further includes:

[0126] An acquisition module, configured to acquire facial information of a user through a wearable device, and extract key facial areas based on the facial information;

[0127] A checking module, configured to check whether the user exists in a user database based on the facial key area;

[0128] The storage module is configured to obtain user information if it does not exist, and store the user information in the user database.

[0129] It should be noted that the device provided in the above embodiment and the method provided in the above embodiment belong to the same concept, wherein the specific manner in which each module and unit performs the operation has been described in detail in the method embodiment and will not be repeated here.

[0130] An embodiment of the present application also provides an electronic device, comprising: one or more processors; a storage device for storing one or more programs, and when the one or more programs are executed by the one or more processors, the electronic device implements the data processing method for chest pain users provided in the above-mentioned embodiments.

[0131] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing an electronic device of an embodiment of the present application is shown.

[0132] It should be noted that Figure 4 The computer system 400 of the electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0133] like Figure 4As shown, the computer system 400 includes a central processing unit (CPU) 401, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 402 or the program loaded from the storage part 408 to the random access memory (RAM) 403, such as executing the method described in the above embodiment. In the RAM 403, various programs and data required for system operation are also stored. The CPU 401, ROM 402 and RAM 403 are connected to each other through a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0134] The following components are connected to the I / O interface 405: an input section 406 including a keyboard, a mouse, etc.; an output section 407 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the I / O interface 405 as needed. A removable medium 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 410 as needed so that a computer program read therefrom is installed into the storage section 408 as needed.

[0135] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication section 409, and / or installed from a removable medium 411. When the computer program is executed by a central processing unit (CPU) 401, various functions defined in the system of the present application are executed.

[0136] It should be noted that the computer-readable medium shown in the embodiment of the present application can be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium can be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, a computer-readable storage medium can be any tangible medium containing or storing a program, which can be used by an instruction execution system, device or device or used in combination with it. In the present application, a computer-readable signal medium can include a data signal propagated in a baseband or as a part of a carrier wave, wherein a computer-readable computer program is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, which may send, propagate, or transmit programs for use by or in conjunction with an instruction execution system, apparatus, or device. The computer program contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0137] The flowchart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present application. Wherein, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0138] The units involved in the embodiments described in this application may be implemented by software or hardware, and the units described may also be set in a processor. The names of these units do not, in some cases, constitute limitations on the units themselves.

[0139] Another aspect of the present application further provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, the method described above is implemented. The computer-readable storage medium may be included in the electronic device described in the above embodiment, or may exist independently without being assembled into the electronic device.

[0140] Another aspect of the present application also provides a computer program product or a computer program, which includes a computer instruction stored in a computer-readable storage medium. A processor of a computer device reads the computer instruction from the computer-readable storage medium, and the processor executes the computer instruction, so that the computer device executes the method provided in each of the above embodiments.

[0141] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above and that the present invention can be implemented in other specific forms without departing from the spirit or essential features of the present invention. Therefore, the embodiments should be considered exemplary and non-restrictive in all respects, and the scope of the present invention is defined by the appended claims rather than the above description, and it is intended that all variations that fall within the meaning and scope of the equivalent elements of the claims be included in the present invention.

Claims

1. A data processing method for chest pain users, characterized in that: include: Acquire the user's physical sign information through a wearable device, and detect whether the user's physical sign is abnormal according to the physical sign data; If the user's physical sign is abnormal, detecting whether the user's heart rate is abnormal according to the heart rate data in the physical sign information; If abnormal, obtain the abnormal chest pain characteristics of the user, and generate a medical treatment plan based on the abnormal chest pain characteristics; Determine medical consultation reminder information according to the medical consultation planning scheme.

2. The data processing method for chest pain users according to claim 1, characterized in that: The detecting whether the user's physical sign is abnormal according to the physical sign data includes: Detecting whether a first heart rate value in the vital sign data belongs to a preset value range, and detecting whether blood oxygen data in the vital sign data is less than a blood oxygen threshold; If the first heart rate value does not belong to the preset value range or the blood oxygen data is less than the blood oxygen threshold, it is determined that the user's physical signs are abnormal.

3. The data processing method for chest pain users according to claim 1, characterized in that: The detecting whether the user's heart rate is abnormal according to the heart rate data in the physical sign information includes: The heart rate data within a preset time period is used as the target heart rate data, and the heart rate pulse data and the second heart rate value in the target heart rate data are obtained; Detecting whether the heart rate pulse data is less than a pulse threshold, and detecting whether the second heart rate value is less than a heart rate threshold; If the heart rate pulse data is less than the pulse threshold, and the second heart rate value is less than the heart rate threshold, it is determined that the user's heart rate is abnormal.

4. The data processing method for chest pain users according to claim 1, characterized in that: The abnormal chest pain characteristics include a first chest pain characteristic reported by a user and a second chest pain characteristic diagnosed.

5. The data processing method for chest pain users according to claim 4, characterized in that: Generating a medical treatment plan according to the abnormal chest pain characteristics includes: The danger signal characteristic values ​​of the first chest pain characteristic and the second chest pain characteristic that the user meets are accumulated, and the medical treatment planning plan is determined based on the accumulated result.

6. The data processing method for chest pain users according to claim 1, characterized in that: The medical treatment planning plan includes at least one item of hospital, ambulance, route and transportation time.

7. The data processing method for chest pain users according to any one of claims 1 to 6, characterized in that: Before obtaining the user's vital sign information through the wearable device, the method further includes: Acquire facial information of the user through the wearable device, and extract key facial areas based on the facial information; Checking whether the user exists in a user database based on the facial key area; If not present, obtain user information and store the user information in the user database.

8. A data processing device for users with chest pain, characterized in that: include: A first detection module is configured to obtain the user's physical sign information through a wearable device, and detect whether the user's physical sign is abnormal according to the physical sign data; A second detection module is configured to detect whether the user's heart rate is abnormal according to the heart rate data in the physical sign information if the user's physical sign is abnormal; A generation module is configured to obtain abnormal chest pain characteristics of the user if abnormal, and generate a medical treatment plan according to the abnormal chest pain characteristics; The determination module is configured to determine the medical consultation reminder information according to the medical consultation planning scheme.

9. An electronic device, characterized in that: include: one or more processors; A storage device for storing one or more programs, when the one or more programs are executed by the one or more processors, enables the electronic device to implement the data processing method for chest pain users as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: Computer-readable instructions are stored thereon, and when the computer-readable instructions are executed by a processor of a computer, the computer is caused to execute the data processing method for users with chest pain according to any one of claims 1 to 7.

Images