Data processing method and device based on passive data acquisition technology

Abstract

The invention provides a passive data acquisition technology-based data processing method and apparatus. The method comprises the steps of obtaining a real-time measurement value of a target monitoring parameter corresponding to a target user based on an intelligent wearable device bound with the target user; determining whether the physical condition of the target user is abnormal or not based on a comparison result of the real-time measurement value of the target monitoring parameter and a standard range corresponding to the target monitoring parameter; the standard range corresponding to the target monitoring parameter is determined based on the basic information of the target user, the disease history and the motion condition in the preset time period; when the physical condition of the target user is abnormal, the emergency processing scheme is determined based on the abnormal state and the emergency processing action is executed, so that the standard range corresponding to the target monitoring parameter can be dynamically adjusted based on the basic information of the target user, the disease history and the motion condition in the preset time period; therefore, the real physical condition of the old people is accurately monitored, and the problem that the abnormal physical condition of the old people cannot be found in time and subjected to emergency treatment is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of health monitoring, and in particular to a data processing method and device based on passive data acquisition technology. Background Art

[0002] As the aging of the population becomes more serious, the size of the elderly group is also getting larger. Due to natural reasons such as age and physiology, the physical functions of the elderly are often poor, and accidents are common. Therefore, the health monitoring problem of the elderly group is becoming increasingly serious.

[0003] Existing human health monitoring equipment often uses universal indicator abnormality judgment standards. However, the indicator abnormality judgment standards are not the same for people of different ages and physical conditions. Therefore, the final monitoring data cannot accurately reflect the actual physical condition of the elderly, which leads to the inability to timely discover and deal with the abnormal physical condition of the elderly. Summary of the invention

[0004] The present invention provides a data processing method and device based on passive data acquisition technology, which is used to solve the problem that the existing technology cannot accurately monitor the real physical condition of the elderly, thereby resulting in the inability to timely discover and emergency treatment of the elderly's abnormal physical condition.

[0005] In one aspect, the present invention provides a data processing method based on passive data collection technology, comprising:

[0006] Acquire a real-time measurement value of a target monitoring parameter corresponding to the target user based on a smart wearable device bound to the target user;

[0007] Determine whether the target user's physical condition is abnormal based on the comparison result of the real-time measurement value of the target monitoring parameter and the standard range corresponding to the target monitoring parameter; the standard range corresponding to the target monitoring parameter is determined based on the target user's basic information, medical history and exercise conditions within a preset time period;

[0008] In the event that the target user's physical condition is abnormal, an emergency treatment plan is determined based on the abnormal state and an emergency treatment action is performed.

[0009] In an optional embodiment of the present application, the step of determining the standard range corresponding to the target monitoring parameter based on the basic information, medical history and exercise information of the target user within a preset time period specifically includes:

[0010] Based on the basic information of the target user, determine the initial range corresponding to the target monitoring parameter;

[0011] Determine the initial range correction amount corresponding to the target monitoring parameter based on the target user's medical history and exercise status within a preset period of time;

[0012] Based on the initial range and the initial range correction amount corresponding to the target monitoring parameter, the standard range corresponding to the target monitoring parameter is determined.

[0013] In an optional embodiment of the present application, the target monitoring parameters include heart rate, blood oxygen saturation and blood pressure; the basic information includes age, height and weight; and the exercise information refers to the amount of exercise.

[0014] In an optional embodiment of the present application, the comparison result based on the real-time measurement value of the target monitoring parameter and the standard range corresponding to the target monitoring parameter to determine whether the target user's physical condition is abnormal specifically includes:

[0015] Determine whether the real-time measurement value of the target monitoring parameter is within the corresponding standard range;

[0016] In the case that there is a first target monitoring parameter whose real-time measurement value is not within the corresponding standard range, it is determined whether there is abnormality in the target user's physical condition based on the number of the first target monitoring parameter and the deviation between the real-time measurement value of the first target monitoring parameter and the corresponding standard range.

[0017] In an optional embodiment of the present application, determining whether the target user's physical condition is abnormal based on the number of the first target monitoring parameter and the deviation between the real-time measurement value of the first target monitoring parameter and the corresponding standard range specifically includes:

[0018] In the case where the number of the first target monitoring parameter is one, determining whether the deviation between the real-time measurement value of the first target monitoring parameter and the corresponding standard range exceeds a preset threshold, and if not, determining that the physical condition of the target user is abnormal;

[0019] When there are multiple first target monitoring parameters, determine whether there is a target deviation that exceeds a preset threshold between the real-time measurement value of the first target monitoring parameter and the corresponding standard range. If not, determine that there is an abnormality in the physical condition of the target user.

[0020] In an optional embodiment of the present application, the determining whether the target user's physical condition is abnormal based on the number of the first target monitoring parameter and the deviation between the real-time measurement value of the first target monitoring parameter and the corresponding standard range further includes:

[0021] When there is a target deviation amount exceeding a preset threshold value in the deviation amount between the real-time measurement value of the first target monitoring parameter and the corresponding standard range, controlling the home camera to collect a hand image of the target user;

[0022] Based on the hand image of the target user, determine whether the smart wearable device of the target user is worn normally, and if so, determine that the smart wearable device has a fault.

[0023] In an optional embodiment of the present application, when the target user has an abnormal physical condition, determining an emergency treatment plan based on the abnormal state and performing an emergency treatment action specifically includes:

[0024] Determining an abnormal state of the target user based on a deviation between a real-time measurement value of the first target monitoring parameter and a corresponding standard range and a full-body image of the target user;

[0025] Determine emergency response plans based on abnormal conditions and execute emergency response actions.

[0026] In a second aspect, the present invention further provides a data processing device based on passive data acquisition technology, comprising:

[0027] A monitoring parameter acquisition module, used to acquire a real-time measurement value of a target monitoring parameter corresponding to the target user based on a smart wearable device bound to the target user;

[0028] A user physical condition determination module, for determining whether the physical condition of the target user is abnormal based on a comparison result of the real-time measurement value of the target monitoring parameter and the standard range corresponding to the target monitoring parameter; the standard range corresponding to the target monitoring parameter is determined based on the basic information, medical history and exercise status of the target user within a preset time period;

[0029] The exception handling module is used to determine an emergency handling plan and perform emergency handling actions based on the abnormal state when the target user's physical condition is abnormal.

[0030] In a third aspect, the present invention further provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the data processing method based on the passive data acquisition technology as described above is implemented.

[0031] In a fourth aspect, the present invention further provides a non-transitory computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the data processing method based on the passive data acquisition technology as described above is implemented.

[0032] The present invention provides a data processing method and device based on passive data acquisition technology, which obtains the real-time measurement value of the target monitoring parameter corresponding to the target user based on the smart wearable device bound to the target user; determines whether the physical condition of the target user is abnormal based on the comparison result of the real-time measurement value of the target monitoring parameter and the standard range corresponding to the target monitoring parameter; the standard range corresponding to the target monitoring parameter is determined based on the basic information, medical history and exercise conditions within a preset time period of the target user; when the physical condition of the target user is abnormal, determines an emergency treatment plan based on the abnormal state and performs an emergency treatment action, and can dynamically adjust the standard range corresponding to the target monitoring parameter based on the basic information, medical history and exercise conditions within a preset time period of the target user, thereby accurately monitoring the real physical condition of the elderly and avoiding the problem that the abnormal physical condition of the elderly cannot be discovered in time and emergency treatment cannot be performed. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0034] Figure 1 A flow chart of a data processing method based on passive data acquisition technology provided by the present invention;

[0035] Figure 2 A schematic diagram of a process for determining a standard range corresponding to a target monitoring parameter provided by the present invention;

[0036] Figure 3 A schematic diagram of a process for determining whether a target user's physical condition is abnormal provided by the present invention;

[0037] Figure 4 A structural block diagram of a data processing device based on passive data acquisition technology provided by the present invention;

[0038] Figure 5 It is a structural schematic diagram of the electronic device provided by the present invention. DETAILED DESCRIPTION

[0039] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the drawings of the present invention. Obviously, the described embodiments are 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.

[0040] The specific implementation process of the data processing method and device based on the passive data collection technology in the embodiment of the present invention will be described below.

[0041] Figure 1 A flow chart of a data processing method based on passive data acquisition technology provided by an embodiment of the present invention is as follows: Figure 1 As shown, the method may include:

[0042] Step 101: obtaining a real-time measurement value of a target monitoring parameter corresponding to a target user based on a smart wearable device bound to the target user.

[0043] Specifically, it is understandable that the target user can be any elderly user. The elderly user refers to a user who is over 60 years old. The smart wearable device can be a smart bracelet or a smart watch. The target monitoring parameters include heart rate, blood oxygen saturation and blood pressure. Of course, with the continuous iteration of smart wearable devices, the target monitoring parameters are not limited to the above three items. It can also be understood that smart wearable devices are existing conventional products based on passive data acquisition technology, which can monitor the user's physical indicators in real time. The specific monitoring principles of this embodiment of the application are not described in detail. The data processing method based on passive data acquisition technology in the embodiment of the present application focuses on obtaining the real-time measurement values ​​of the target monitoring parameters corresponding to the target user based on the smart wearable device bound to the target user, and accurately evaluating the abnormal physical condition of the target user based on the real-time measurement values ​​of the target monitoring parameters.

[0044] Step 102, based on the comparison result of the real-time measurement value of the target monitoring parameter and the standard range corresponding to the target monitoring parameter, determine whether there is any abnormality in the physical condition of the target user; the standard range corresponding to the target monitoring parameter is determined based on the basic information, medical history and exercise conditions of the target user within a preset time period.

[0045] Specifically, based on the foregoing content, it can be known that the existing human health monitoring equipment often adopts a universal indicator abnormality judgment standard, that is, for people of different ages and different physical conditions, the judgment standard of the indicator abnormality is consistent, but the present application has found through research that for people of different ages and different physical conditions, the values ​​of the target monitoring parameters are not the same. At the same time, for people of the same age, the values ​​of the target monitoring parameters are also different due to differences in physical conditions. Therefore, the monitoring data finally obtained by using the prior art cannot accurately reflect the real physical condition of the elderly, which in turn leads to the inability to timely discover and deal with the abnormal physical condition of the elderly. In response to this problem, the embodiment of the present application determines the standard range corresponding to the target monitoring parameter based on the basic information, medical history and exercise conditions within a preset time period of the target user. Based on this, it can be understood that for the target user, the differences in their basic information, medical history and exercise conditions within a preset time period will lead to differences in the standard range corresponding to the target monitoring parameter, that is, the standard range corresponding to the target monitoring parameter obtained by the embodiment of the present application is dynamically changing. It is worth noting that the basic information includes age, height and weight; the exercise information refers to the amount of exercise.

[0046] More specifically, Figure 2 A schematic diagram of a process for determining a standard range corresponding to a target monitoring parameter provided by the present invention, such as Figure 2 As shown, the steps of determining the standard range corresponding to the target monitoring parameter based on the basic information, medical history and exercise information of the target user within a preset time period specifically include:

[0047] Step 201, based on the basic information of the target user, determine the initial range corresponding to the target monitoring parameter;

[0048] It is understandable that this step is intended to determine the range of target monitoring parameters corresponding to people of the same age, height and weight based on the age, height and weight of the target user. The initial range can be obtained through big data analysis. It is also understandable that the initial range does not take into account the impact of diseases and the user's exercise conditions. However, compared with the prior art, it takes into account the impact of basic information such as age, height and weight on the target monitoring parameters, rather than using a general indicator abnormality judgment standard as in the prior art.

[0049] Step 202, determining an initial range correction amount corresponding to a target monitoring parameter based on the target user's medical history and exercise conditions within a preset period of time;

[0050] On the basis of step 201, the present application has found through research that the user's injury and exercise conditions will also affect the value of the target monitoring parameter. Specifically, for patients with hypertension, the range of change of their heart rate is usually smaller than that of people who do not suffer from hypertension. For example, the range of change of the heart rate of patients with hypertension is 70-90bpm, while the range of change of the heart rate of people who do not suffer from hypertension is 60-100bpm; for patients with diabetes, the range of change of their blood oxygen saturation is usually larger than that of people who do not suffer from diabetes. For example, the range of change of the blood oxygen saturation of patients with diabetes is 92-100%, while the range of change of the blood oxygen saturation of people who do not suffer from diabetes is 95-100%. At the same time, the exercise conditions of the target user will also affect parameters such as heart rate, blood oxygen saturation and blood pressure. Based on this, after the embodiment of the present application determines the initial range corresponding to the target monitoring parameter, it further determines the initial range correction amount corresponding to the target monitoring parameter based on the target user's medical history and the exercise conditions within the preset time period.

[0051] It is understandable that the preset time period is a period of preset length before the current moment. Considering that the intensity of the exercise and the time interval after the exercise will affect the value of the target monitoring parameter, the preset length can be dynamically adjusted according to the intensity of the exercise and the time interval after the exercise. Based on step 201, the embodiment of the present application can further obtain the fluctuation range of the target monitoring parameter corresponding to different medical histories and exercise conditions through big data analysis, and then determine the initial range correction amount corresponding to the target monitoring parameter based on the target user's medical history and the exercise conditions within the preset time period. It can also be understood that the initial range correction amount can be a positive value or a negative value. The exercise conditions within the preset time period are also obtained through the smart wearable device.

[0052] Step 203: Determine a standard range corresponding to the target monitoring parameter based on the initial range corresponding to the target monitoring parameter and the initial range correction amount.

[0053] After determining the initial range and initial range correction corresponding to the target monitoring parameter, the standard range corresponding to the target monitoring parameter can be determined. Specifically, the standard range can be obtained by summing the initial range and the initial range correction. It is worth noting that the initial range correction is a correction for the boundary value (including the upper boundary value and the boundary value) of the initial range, so it may include one or two.

[0054] Based on the above means, the embodiment of the present application can maximize the accuracy of the standard range corresponding to the target monitoring parameter, thereby ensuring the accuracy of the subsequent judgment results of abnormal physical condition. Figure 3 A flow chart of determining whether the target user's physical condition is abnormal provided by the present invention, such as Figure 3As shown, the comparison result of the real-time measurement value of the target monitoring parameter and the standard range corresponding to the target monitoring parameter is used to determine whether the target user's physical condition is abnormal, specifically including:

[0055] Step 1021, determining whether the real-time measurement value of the target monitoring parameter is within the corresponding standard range;

[0056] Step 1022, in the case where there is a first target monitoring parameter whose real-time measurement value is not within the corresponding standard range, determine whether there is an abnormality in the target user's physical condition based on the number of the first target monitoring parameter and the deviation between the real-time measurement value of the first target monitoring parameter and the corresponding standard range.

[0057] It is worth noting that the traditional health monitoring method determines that the physical condition is abnormal when it determines that the real-time measurement value of the target monitoring parameter is not within the corresponding standard range. However, the present application has found through research that the situations that lead to this situation also include the failure of the smart wearable device or improper wearing, and the deviation between the real-time measurement value of the target monitoring parameter and the corresponding standard range can accurately reflect the abnormal cause of the target monitoring parameter. Therefore, in the case of a first target monitoring parameter whose real-time measurement value is not within the corresponding standard range, the embodiment of the present application further determines whether the physical condition of the target user is abnormal based on the number of the first target monitoring parameter and the deviation between the real-time measurement value of the first target monitoring parameter and the corresponding standard range. Specifically, the determination of whether the physical condition of the target user is abnormal based on the number of the first target monitoring parameter and the deviation between the real-time measurement value of the first target monitoring parameter and the corresponding standard range specifically includes:

[0058] In the case where the number of the first target monitoring parameter is one, determining whether the deviation between the real-time measurement value of the first target monitoring parameter and the corresponding standard range exceeds a preset threshold, and if not, determining that the physical condition of the target user is abnormal;

[0059] When there are multiple first target monitoring parameters, determine whether there is a target deviation that exceeds a preset threshold between the real-time measurement value of the first target monitoring parameter and the corresponding standard range. If not, determine that there is an abnormality in the physical condition of the target user.

[0060] The preset threshold is determined based on a preliminary test, that is, the measurement value of the corresponding target monitoring parameter is obtained by conducting tests for abnormal physical condition, abnormal wearing of the smart wearable device, and faulty smart wearable device, and the preset threshold is determined based on the deviation between the measurement value of the target monitoring parameter and the corresponding standard range. If the deviation between the real-time measurement value of the target monitoring parameter and the corresponding standard range exceeds the preset threshold, it may be caused by the abnormal wearing of the smart wearable device or the faulty smart wearable device, otherwise it indicates that the target user's physical condition is abnormal.

[0061] Based on this, the embodiment of the present application determines whether the target user's physical condition is abnormal based on the number of the first target monitoring parameter and the deviation between the real-time measurement value of the first target monitoring parameter and the corresponding standard range, and also includes:

[0062] When there is a target deviation amount exceeding a preset threshold value in the deviation amount between the real-time measurement value of the first target monitoring parameter and the corresponding standard range, controlling the home camera to collect a hand image of the target user;

[0063] Based on the hand image of the target user, determine whether the smart wearable device of the target user is worn normally, and if so, determine that the smart wearable device has a fault.

[0064] It is worth noting that, since the target deviation exists when the smart wearable device is not worn normally and when the smart wearable device has a fault, it is impossible to determine the specific reason for the abnormal parameter value. In response to this problem, the embodiment of the present application further combines the active acquisition technology to realize the judgment of the abnormal parameter value. Specifically, in the embodiment of the present application, when there is a target deviation exceeding the preset threshold value in the deviation between the real-time measurement value of the first target monitoring parameter and the corresponding standard range, the home camera is controlled to collect the hand image of the target user, and based on the hand image of the target user, it is determined whether the smart wearable device of the target user is worn normally, and if so, it is determined that the smart wearable device has a fault. It can be understood that if not, it means that the smart wearable device of the target user is not worn normally. The embodiment of the present application can track the target user through the home camera to collect images, and the collected images are used to determine the user identity and whether the smart wearable device is worn normally. By combining passive data acquisition and active data acquisition, the embodiment of the present application can maximize the accuracy of the monitoring results of abnormal physical conditions of the elderly.

[0065] Step S103: when the target user's physical condition is abnormal, an emergency treatment plan is determined based on the abnormal state and an emergency treatment action is performed.

[0066] Specifically, when the target user's physical condition is abnormal, determining an emergency treatment plan based on the abnormal state and performing an emergency treatment action specifically includes:

[0067] Determining an abnormal state of the target user based on a deviation between a real-time measurement value of the first target monitoring parameter and a corresponding standard range and a full-body image of the target user;

[0068] Determine emergency response plans based on abnormal conditions and execute emergency response actions.

[0069] Through research, the present application has found that the greater the deviation between the real-time measurement value of the first target monitoring parameter and the corresponding standard range, the more serious the abnormal state is, but it is not possible to accurately judge how serious it is and what measures need to be taken. In response to this problem, the embodiment of the present application further combines the full-body image of the target user to determine the abnormal state of the target user. Specifically, the expression and action of the target user are determined through the full-body image of the target user, and based on the expression and action of the target user, it is judged whether the target user is in pain, whether he has fallen, whether he is unconscious, etc., and then it is accurately determined whether the abnormal state is serious, and then the emergency treatment plan is determined and the emergency treatment action is executed. The emergency treatment plan can be, for example, notifying the target user, notifying family members, directly calling an emergency number, etc. The embodiments of the present application are not exhaustive here.

[0070] The solution provided by the present invention obtains the real-time measurement value of the target monitoring parameter corresponding to the target user based on the smart wearable device bound to the target user; determines whether the physical condition of the target user is abnormal based on the comparison result of the real-time measurement value of the target monitoring parameter and the standard range corresponding to the target monitoring parameter; the standard range corresponding to the target monitoring parameter is determined based on the basic information, medical history and exercise conditions within a preset time period of the target user; in the case that the physical condition of the target user is abnormal, an emergency treatment plan is determined based on the abnormal state and an emergency treatment action is performed, and the standard range corresponding to the target monitoring parameter can be dynamically adjusted based on the basic information, medical history and exercise conditions within a preset time period of the target user, thereby accurately monitoring the real physical condition of the elderly and avoiding the problem that the abnormal physical condition of the elderly cannot be discovered in time and emergency treatment cannot be performed.

[0071] Figure 4 A structural block diagram of a data processing device based on passive data acquisition technology is provided for an embodiment of the present invention, such as Figure 4 As shown, the system includes:

[0072] A monitoring parameter acquisition module 301 is used to acquire a real-time measurement value of a target monitoring parameter corresponding to the target user based on a smart wearable device bound to the target user;

[0073] A user physical condition determination module 302 is used to determine whether the physical condition of the target user is abnormal based on the comparison result of the real-time measurement value of the target monitoring parameter and the standard range corresponding to the target monitoring parameter; the standard range corresponding to the target monitoring parameter is determined based on the basic information, medical history and exercise status of the target user within a preset time period;

[0074] The abnormality handling module 303 is used to determine an emergency handling plan and execute an emergency handling action based on the abnormal state when the target user's physical condition is abnormal.

[0075] The solution provided by the present invention obtains the real-time measurement value of the target monitoring parameter corresponding to the target user based on the smart wearable device bound to the target user through the monitoring parameter acquisition module 301; the user physical condition determination module 302 determines whether there is an abnormality in the physical condition of the target user based on the comparison result of the real-time measurement value of the target monitoring parameter and the standard range corresponding to the target monitoring parameter; the standard range corresponding to the target monitoring parameter is determined based on the basic information, medical history and exercise conditions within a preset time period of the target user; the abnormality handling module 303 determines an emergency handling plan and performs an emergency handling action based on the abnormal state when the physical condition of the target user is abnormal, and can dynamically adjust the standard range corresponding to the target monitoring parameter based on the basic information, medical history and exercise conditions within a preset time period of the target user, thereby accurately monitoring the real physical condition of the elderly and avoiding the problem that the abnormal physical condition of the elderly cannot be discovered in time and emergency handling cannot be performed.

[0076] In an optional embodiment of the present application, the data processing device based on the passive data collection technology further includes a standard range determination module, and the standard range determination module is used to perform the following operations:

[0077] Based on the basic information of the target user, determine the initial range corresponding to the target monitoring parameter;

[0078] Determine the initial range correction amount corresponding to the target monitoring parameter based on the target user's medical history and exercise status within a preset period of time;

[0079] Based on the initial range and the initial range correction amount corresponding to the target monitoring parameter, the standard range corresponding to the target monitoring parameter is determined.

[0080] In an optional embodiment of the present application, the target monitoring parameters include heart rate, blood oxygen saturation and blood pressure; the basic information includes age, height and weight; and the exercise information refers to the amount of exercise.

[0081] In an optional embodiment of the present application, the comparison result based on the real-time measurement value of the target monitoring parameter and the standard range corresponding to the target monitoring parameter to determine whether the target user's physical condition is abnormal specifically includes:

[0082] Determine whether the real-time measurement value of the target monitoring parameter is within the corresponding standard range;

[0083] In the case that there is a first target monitoring parameter whose real-time measurement value is not within the corresponding standard range, it is determined whether there is abnormality in the target user's physical condition based on the number of the first target monitoring parameter and the deviation between the real-time measurement value of the first target monitoring parameter and the corresponding standard range.

[0084] In an optional embodiment of the present application, determining whether the target user's physical condition is abnormal based on the number of the first target monitoring parameter and the deviation between the real-time measurement value of the first target monitoring parameter and the corresponding standard range specifically includes:

[0085] In the case where the number of the first target monitoring parameter is one, determining whether the deviation between the real-time measurement value of the first target monitoring parameter and the corresponding standard range exceeds a preset threshold, and if not, determining that the physical condition of the target user is abnormal;

[0086] When there are multiple first target monitoring parameters, determine whether there is a target deviation that exceeds a preset threshold between the real-time measurement value of the first target monitoring parameter and the corresponding standard range. If not, determine that there is an abnormality in the physical condition of the target user.

[0087] In an optional embodiment of the present application, the determining whether the target user's physical condition is abnormal based on the number of the first target monitoring parameter and the deviation between the real-time measurement value of the first target monitoring parameter and the corresponding standard range further includes:

[0088] When there is a target deviation amount exceeding a preset threshold value in the deviation amount between the real-time measurement value of the first target monitoring parameter and the corresponding standard range, controlling the home camera to collect a hand image of the target user;

[0089] Based on the hand image of the target user, determine whether the smart wearable device of the target user is worn normally, and if so, determine that the smart wearable device has a fault.

[0090] In an optional embodiment of the present application, when the target user has an abnormal physical condition, determining an emergency treatment plan based on the abnormal state and performing an emergency treatment action specifically includes:

[0091] Determining an abnormal state of the target user based on a deviation between a real-time measurement value of the first target monitoring parameter and a corresponding standard range and a full-body image of the target user;

[0092] Determine emergency response plans based on abnormal conditions and execute emergency response actions.

[0093] Figure 5 An example of a physical structure diagram of an electronic device is shown in FIG. Figure 5 As shown, the electronic device may include: a processor 401, a communication interface 402, a memory 403 and a communication bus 404, wherein the processor 401, the communication interface 402 and the memory 403 communicate with each other through the communication bus 404. The processor 401 may call the logic instructions in the memory 403 to execute a data processing method based on passive data acquisition technology, the method comprising: obtaining a real-time measurement value of a target monitoring parameter corresponding to the target user based on a smart wearable device bound to the target user; determining whether the target user's physical condition is abnormal based on a comparison result of the real-time measurement value of the target monitoring parameter and the standard range corresponding to the target monitoring parameter; the standard range corresponding to the target monitoring parameter is determined based on the target user's basic information, medical history and exercise conditions within a preset time period; in the case of an abnormal physical condition of the target user, determining an emergency treatment plan based on the abnormal state and executing an emergency treatment action.

[0094] In addition, the logic instructions in the above-mentioned memory 403 can be implemented in the form of a software functional unit and can be stored in a computer-readable storage medium when it is sold or used as an independent product. Based on such an understanding, the technical solution of the present invention can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. 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.

[0095] On the other hand, the present invention also provides a computer program product, which includes a computer program, which can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the data processing method based on passive data acquisition technology provided by the above methods, the method including: obtaining the real-time measurement value of the target monitoring parameter corresponding to the target user based on the smart wearable device bound to the target user; determining whether there is any abnormality in the physical condition of the target user based on the comparison result of the real-time measurement value of the target monitoring parameter and the standard range corresponding to the target monitoring parameter; the standard range corresponding to the target monitoring parameter is determined based on the basic information, medical history and exercise conditions of the target user within a preset time period; in the case that there is an abnormality in the physical condition of the target user, determining an emergency treatment plan based on the abnormal state and performing emergency treatment actions.

[0096] On the other hand, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, is implemented to execute the data processing method based on passive data acquisition technology provided by the above-mentioned methods, the method comprising: obtaining the real-time measurement value of the target monitoring parameter corresponding to the target user based on a smart wearable device bound to the target user; determining whether there is any abnormality in the physical condition of the target user based on a comparison result of the real-time measurement value of the target monitoring parameter with the standard range corresponding to the target monitoring parameter; the standard range corresponding to the target monitoring parameter is determined based on the basic information, medical history and exercise conditions of the target user within a preset time period; in the event that there is an abnormality in the physical condition of the target user, determining an emergency treatment plan based on the abnormal state and performing an emergency treatment action.

[0097] The device embodiments described above are merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative labor.

[0098] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the data processing method based on the passive data acquisition technology described in each embodiment or some parts of the embodiment.

[0099] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A data processing method based on passive data acquisition technology, characterized in that: include: Acquire a real-time measurement value of a target monitoring parameter corresponding to the target user based on a smart wearable device bound to the target user; Determine whether the target user's physical condition is abnormal based on the comparison result of the real-time measurement value of the target monitoring parameter and the standard range corresponding to the target monitoring parameter; the standard range corresponding to the target monitoring parameter is determined based on the target user's basic information, medical history and exercise conditions within a preset time period; In the event that the target user's physical condition is abnormal, an emergency treatment plan is determined based on the abnormal state and an emergency treatment action is performed.

2. The data processing method based on passive data acquisition technology according to claim 1 is characterized in that: The step of determining the standard range corresponding to the target monitoring parameter based on the target user's basic information, medical history, and exercise information within a preset period of time specifically includes: Based on the basic information of the target user, determine the initial range corresponding to the target monitoring parameter; Determine the initial range correction amount corresponding to the target monitoring parameter based on the target user's medical history and exercise status within a preset period of time; Based on the initial range and the initial range correction amount corresponding to the target monitoring parameter, the standard range corresponding to the target monitoring parameter is determined.

3. The data processing method based on passive data acquisition technology according to claim 2 is characterized in that: The target monitoring parameters include heart rate, blood oxygen saturation and blood pressure; the basic information includes age, height and weight; and the exercise information refers to the amount of exercise.

4. The data processing method based on passive data acquisition technology according to claim 3 is characterized in that: The comparison result of the real-time measurement value of the target monitoring parameter with the standard range corresponding to the target monitoring parameter to determine whether the target user's physical condition is abnormal specifically includes: Determine whether the real-time measurement value of the target monitoring parameter is within the corresponding standard range; In the case that there is a first target monitoring parameter whose real-time measurement value is not within the corresponding standard range, it is determined whether there is abnormality in the target user's physical condition based on the number of the first target monitoring parameter and the deviation between the real-time measurement value of the first target monitoring parameter and the corresponding standard range.

5. The data processing method based on passive data acquisition technology according to claim 4 is characterized in that: The determining whether the target user's physical condition is abnormal based on the quantity of the first target monitoring parameter and the deviation between the real-time measurement value of the first target monitoring parameter and the corresponding standard range specifically includes: In the case where the number of the first target monitoring parameter is one, determining whether the deviation between the real-time measurement value of the first target monitoring parameter and the corresponding standard range exceeds a preset threshold, and if not, determining that the physical condition of the target user is abnormal; When there are multiple first target monitoring parameters, determine whether there is a target deviation that exceeds a preset threshold between the real-time measurement value of the first target monitoring parameter and the corresponding standard range. If not, determine that there is an abnormality in the physical condition of the target user.

6. The data processing method based on passive data acquisition technology according to claim 5 is characterized in that: The determining whether the target user's physical condition is abnormal based on the number of the first target monitoring parameter and the deviation between the real-time measurement value of the first target monitoring parameter and the corresponding standard range also includes: When there is a target deviation amount exceeding a preset threshold value in the deviation amount between the real-time measurement value of the first target monitoring parameter and the corresponding standard range, controlling the home camera to collect a hand image of the target user; Based on the hand image of the target user, determine whether the smart wearable device of the target user is worn normally, and if so, determine that the smart wearable device has a fault.

7. The data processing method based on passive data acquisition technology according to claim 6 is characterized in that: When the target user's physical condition is abnormal, determining an emergency treatment plan based on the abnormal state and executing an emergency treatment action specifically includes: Determining an abnormal state of the target user based on a deviation between a real-time measurement value of the first target monitoring parameter and a corresponding standard range and a full-body image of the target user; Determine emergency response plans based on abnormal conditions and execute emergency response actions.

8. A data processing device based on passive data acquisition technology, characterized in that: include: A monitoring parameter acquisition module, used to acquire a real-time measurement value of a target monitoring parameter corresponding to the target user based on a smart wearable device bound to the target user; A user physical condition determination module, for determining whether the physical condition of the target user is abnormal based on a comparison result of the real-time measurement value of the target monitoring parameter and the standard range corresponding to the target monitoring parameter; the standard range corresponding to the target monitoring parameter is determined based on the basic information, medical history and exercise status of the target user within a preset time period; The exception handling module is used to determine an emergency handling plan and perform emergency handling actions based on the abnormal state when the target user's physical condition is abnormal.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the data processing method based on passive data acquisition technology as described in any one of claims 1 to 7 is implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the data processing method based on passive data acquisition technology as described in any one of claims 1 to 7 is implemented.

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