CN113066589B - Collected data analysis method, device, electronic equipment and storage medium - Google Patents
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Abstract
The embodiment of the invention discloses a method, a device, electronic equipment and a storage medium for analyzing acquired data. The method comprises the following steps: acquiring acquisition data of a target user; wherein the acquired data includes video data and physiological data; determining video weights corresponding to the video data and physiological weights corresponding to the physiological data; a physiological state of the target user is determined based on the video data, the video weights, the physiological data, and the physiological weights, and a target intervention proposal for the target user is generated based on the physiological state. According to the technical scheme disclosed by the embodiment of the invention, the data of the user is efficiently analyzed, the service proposal is intelligently pushed, the medicine intake and the chronic disease treatment of the user are remotely intervened, the service efficiency can be greatly improved, and the social resources are saved.
Description
Technical Field
The embodiment of the invention relates to the technical field of software testing, in particular to a method and a device for analyzing acquired data, electronic equipment and a storage medium.
Background
The old people suffer from chronic diseases in a higher proportion, most chronic disease old patients need to continuously seek medical examination and pharmaceutical intervention, and various inconveniences exist when the old people seek medical treatment to seek medical treatment, meanwhile, the medical treatment efficiency of the hospital is generally not high, once the treatment after symptoms appear is not very timely, meanwhile, the old people cannot check the frequency at home because of insufficient checking frequency, the accuracy of reading self-service household checking equipment is not enough, and the like, and the conditions such as untimely and the like can lead the old people to possibly not find the disease change of the old people in time, even can not intervene through a therapeutic means in time, and the disease state is delayed. According to the prior art means, doctors only have two channels to communicate with old chronic patients, or communicate with patients face to face through off-line outpatient service and diagnose and communicate with inspection and examination sheets, or communicate with old people through video or voice on pure lines, and the doctor cannot be assisted in accurately judging the state of the old people, so that maintenance work for walking health cannot be performed.
Disclosure of Invention
The invention provides a collected data analysis method, a device, electronic equipment and a storage medium, which are used for efficiently analyzing data of users and intelligently pushing service suggestions, so that service efficiency can be greatly improved, and social resources can be saved.
In a first aspect, an embodiment of the present invention provides a method for analyzing collected data, where the method includes:
acquiring acquisition data of a target user; wherein the acquired data includes video data and physiological data;
Determining video weights corresponding to the video data and physiological weights corresponding to the physiological data;
A physiological state of the target user is determined based on the video data, the video weights, the physiological data, and the physiological weights, and a target intervention proposal for the target user is generated based on the physiological state.
In a second aspect, an embodiment of the present invention further provides an apparatus for analyzing acquired data, including:
The acquisition data acquisition module is used for acquiring acquisition data of a target user; wherein the acquired data includes video data and physiological data;
The weight determining module is used for determining the video weight corresponding to the video data and the physiological weight corresponding to the physiological data;
A target intervention proposal generation module for determining a physiological state of the target user based on the video data, the video weight, the physiological data, and the physiological weight, and generating a target intervention proposal of the target user based on the physiological state.
In a third aspect, an embodiment of the present invention further provides an acquired data analysis system, which is applied to the acquired data analysis method described in any one of the foregoing embodiments, where the system includes: a data acquisition subsystem, a data analysis subsystem and an intervention subsystem; wherein:
The data acquisition subsystem is used for acquiring acquisition data of a target user, wherein the acquisition data comprises video data and physiological data;
the data analysis subsystem is used for receiving video data and physiological data of a target user; determining a video weight corresponding to the video data and a physiological weight corresponding to the physiological data; and determining a physiological state of the target user based on the video data, the video weight, the physiological data, and the physiological weight, and generating a target intervention proposal for the target user based on the physiological state;
The intervention subsystem is used for reminding the target user of executing the target intervention advice based on the target intervention advice.
The technical scheme of the embodiment of the invention specifically comprises the following steps: acquiring acquisition data of a target user, wherein the acquisition data comprises video data and physiological data, and determining video weight corresponding to the video data and physiological weight corresponding to the physiological data; the physiological state of the target user is determined based on the video data, the video weight, the physiological data, and the physiological weight, and the target intervention proposal of the target user is determined based on the physiological state of the target user. According to the technical scheme provided by the embodiment of the invention, the physiological state of the target user can be more efficiently and accurately determined by determining the weights corresponding to the acquired data of the target user and based on the data and the corresponding weights, and more accurate corresponding target intervention suggestions are generated based on the physiological state, so that the service efficiency can be greatly improved, and the social resources can be saved.
Drawings
In order to more clearly illustrate the technical solution of the exemplary embodiments of the present invention, a brief description is given below of the drawings required for describing the embodiments. It is obvious that the drawings presented are only drawings of some of the embodiments of the invention to be described, and not all the drawings, and that other drawings can be made according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flow chart of a method for analyzing collected data according to a first embodiment of the present invention;
fig. 2 is a schematic structural diagram of an acquired data analysis device according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of an acquired data analysis system according to a third embodiment of the present invention;
FIG. 4 is a schematic diagram of an interaction flow of a method for analyzing acquired data according to a third embodiment of the invention
Fig. 5 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present invention.
Detailed Description
The invention is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting thereof. It should be further noted that, for convenience of description, only some, but not all of the structures related to the present invention are shown in the drawings.
Example 1
Fig. 1 is a flowchart of a method for analyzing collected data according to a first embodiment of the present invention, where the embodiment is applicable to a case of analyzing collected data of a user, and in particular, to a case of analyzing video data and physiological data of the user to obtain a physiological state of the user, and generating a target intervention suggestion of the user according to the physiological state. The method may be performed by an acquired data analysis apparatus, which may be implemented in software and/or hardware.
Before the technical scheme of the embodiment of the present invention is introduced, an application scenario of the embodiment is introduced in an exemplary manner: the old people suffering from chronic diseases at present generally need to be checked and treated for multiple times, but because various reasons are inconvenient to go to the hospital for medical treatment for multiple times, the change of the diseases cannot be found in time, so that checking items and treatment schemes cannot be adjusted in time, and the illness state of the patient is delayed.
In order to solve the above technical problems, the technical solution of this embodiment is to preset a video acquisition device and preset a wearable device or a portable physiological signal acquisition device capable of acquiring preset physiological data in the daily activity range of the target user. Acquiring acquisition data of a target user based on preset acquisition conditions, the video acquisition device and the physiological signal acquisition equipment. Specifically, the acquisition data includes video data and physiological data. Determining each weight corresponding to each acquired data of the target user according to the acquired scene; determining the physiological state of a target user according to each data and each corresponding weight, determining a target intervention suggestion of the target user according to the physiological state, and acquiring the intervention suggestion according to the analysis result of the acquired data so as to realize regular examination and intervention treatment; and the collected data of the target user is analyzed efficiently, the service advice is pushed intelligently, the service efficiency can be improved greatly, and the social resources are saved.
As shown in fig. 1, the method specifically includes the following steps:
s110, acquiring acquisition data of a target user; wherein the acquisition data includes video data and physiological data.
In this embodiment, the acquisition data includes video data and physiological data. The video data may be, but is not limited to, physiological video data based on a preset duration of time that the video acquisition device acquires when the target user performs preset physiological actions such as taking medicine, lying in bed, sleeping, eating, etc. The physiological data are physiological data corresponding to a preset type of physiological signal acquired by the wearable equipment and other physiological signal acquisition equipment, for example, the preset type of physiological signal can be an electrocardio physiological signal, an electroencephalogram physiological signal, a blood pressure physiological signal, a blood oxygen physiological signal, a blood sugar physiological signal and the like physiological data; of course, in other embodiments, the psychological data further includes physiological data collected by each sensor configured on the signal collection device, for example, collected data such as the number of exercise steps, sleep time, etc. may also be used as the physiological data.
The method for acquiring the acquired data of the target user can be as follows: monitoring a preset action of a target user based on video acquisition equipment, and acquiring video data of preset duration after the preset action of the target user; and acquiring physiological data of a preset type of a target user in a preset time period based on the physiological signal acquisition equipment.
Specifically, a camera is adopted to monitor the video of the target user, and when the target user has preset action, the video with preset duration after the action is collected as video data; of course, the method may also be to start to collect video when the target user has a preset action, stop collecting video when the target user is detected to end the preset action, and use the video collected during the preset action as video data. For example, when the feeding action of the target user is acquired, the acquisition of the video data of the target user is started, and the acquisition is ended after the preset feeding time is fifteen minutes, wherein the fifteen minutes of video is taken as the video data of the target user under the feeding action, or of course, the acquisition of the video is stopped after the target user finishes feeding after detecting that the target user stops feeding for five minutes, and the video during the period of starting the feeding action and stopping the acquisition after the feeding action is taken as the video data of the target user under the feeding action.
Specifically, physiological data corresponding to a target user preset type physiological signal can be collected by using a physiological signal collection device, the physiological signal collection device can include, but is not limited to, wearable devices, portable monitors and other devices, and the preset type physiological signal can be blood glucose, blood pressure, blood oxygen and other physiological signals. Of course, the type of the physiological signal to be acquired can be preset, and the physiological signal of the preset type of the target user can be acquired at preset acquisition time intervals to obtain the physiological signal. For example, it may be that blood glucose of the target subject is detected based on the blood glucose detection device and blood glucose data of the target subject is acquired during the first half hour of eating and the second half hour of eating, respectively, every day.
S120, determining video weight corresponding to the video data and physiological weight corresponding to the physiological data.
In this embodiment, the method for determining the video weight corresponding to the video data and the physiological weight corresponding to the physiological data may be: acquiring an acquisition scene of acquisition data, and determining a video weight corresponding to video data corresponding to the acquisition scene and a physiological weight corresponding to physiological data. The method for determining the acquisition scene of the acquired acquisition data can determine the acquisition scene of the acquisition data by determining the data type of the acquired acquisition data. Specifically, the data type of the acquired acquisition data comprises the acquisition data of the target object under the previous intervention advice or the acquisition data of the target object under the dry pre-advice.
Specifically, the data type of the collected data is determined, when the collected data is the collected data of the target object without interference pre-suggestion, the video weight corresponding to the video data and the physiological weight corresponding to the physiological data may be preset, for example, the weights may be set to equal weights, that is, the weights may be all 0.5, or the weights may be all 1, and the proportion and the numerical value of the setting of the weights corresponding to the data are not limited in this embodiment. Specifically, when the acquired data is acquired data of the target object under the previous intervention suggestion, determining an intervention type of the intervention suggestion, and determining video weights and physiological weights corresponding to the video data and the physiological data according to the intervention type. Wherein the types of intervention include pharmaceutical intervention and non-pharmaceutical intervention. Wherein, the pharmaceutical intervention comprises, but is not limited to, the intervention suggestions of injection, prescription, etc. of the target user; non-pharmaceutical interventions may include, but are not limited to, intervention advice on the target user to exercise, sleep, and sensitive food intake. Optionally, when the intervention type is a drug intervention, the preset physiological weight is greater than the video weight; when the intervention type is non-pharmaceutical intervention, the preset video weight is greater than the physiological weight. It should be noted that, when the physiological weight is greater than the video weight or the video weight is greater than the physiological weight, that is, when the weights corresponding to the two acquired data are not equal, the weight ratio of the two weights may be set to 0.2:0.5, or may be set to 0.8:0.3, or the two weight ratios may be specifically set according to the actual situation, and in this embodiment, the two weight ratios are not limited.
For example, when it is determined that the type of intervention proposed to the target object is a pharmaceutical intervention, i.e. an injection intervention proposal is made, it is determined that the video weight corresponding to the video data of the collected target object under the current condition is 0.7, and the physiological weight corresponding to the corresponding physiological data is 0.3; the beneficial effect of current setting proportion lies in: it may be determined from the video data whether there is an intervention suggestion to execute, and the execution result of the target object may be quick or quick.
For example, when it is determined that the type of intervention proposed for the intervention of the target object is a non-pharmaceutical intervention, that is, a motion intervention, it is determined that the video weight corresponding to the video data of the collected target object in the current situation is 0.2, and the physiological weight corresponding to the corresponding physiological data is 0.8; the beneficial effect of current setting proportion lies in: whether the target object performs the intervention result can be known according to the number of motion steps in the physiological data, and the execution result of the target object can be fast or performed.
In some alternative embodiments, the video data may include, but is not limited to, sleep data, food intake data, exercise data, etc., and the physiological data may include a plurality of different types of data, including, but not limited to, blood glucose data, blood pressure data, heart rate data, etc. After the weights of the physiological data and the video data are determined, the method further comprises the steps of determining the weights of the various types of data according to the weights of the physiological data and the weight proportion of the various types of data in the physiological data, and determining the specific weights of the sleep data, the food intake data and the movement data according to the weights of the video data, the weight proportion of the sleep data, the food intake data and the movement data. The weight of the physiological data is the weight sum of various types of physiological data, and the weight of the video data is the weight sum of sleep data, food intake data and motion data. Furthermore, when no intervention advice exists, the weight proportion of the data of the various types, the weight proportion of the sleep data, the food intake data and the exercise data can be preset and directly called; and determining the weight proportion of each type of data, and the weight proportion of sleep data, food intake data and exercise data according to the specific content of the intervention advice. Optionally, the weight of the type of physiological data is increased if the number of pre-advice includes a drug for any type of physiological data, and the weight of the corresponding sleep data, food intake data, and exercise data in the intervention advice is increased if the number of pre-advice includes advice for any of sleep data, food intake data, and exercise data. The weight adjustment rule may be preset for the weight of any data, for example, the weight proportion of the data corresponding to the intervention advice is greater than 0.5, and the weight proportion of blood sugar is greater than 0.5 if the intervention advice includes blood sugar intervention drugs, and the weight proportion sum of sleep data and exercise data is greater than 0.5 if the plurality of pre-advice includes advice of sleep and exercise.
S130, determining the physiological state of the target user based on the video data, the video weight, the physiological data and the physiological weight, and generating a target intervention proposal of the target user based on the physiological state.
In embodiments of the present invention, the physiological state may include a physical state of whether the target subject is healthy, in particular, the physiological state includes, but is not limited to, a healthy state or an unhealthy state, although sub-healthy states may also be included in some embodiments. The intervention advice may be corresponding intervention advice generated from the respective physiological states. Specifically, the method can include an intervention suggestion that does not intervene in the target subject when the physiological state of the target subject is healthy; or an intervention proposal for performing different intervention degrees on the target when the physiological state of the target object is sub-healthy or unhealthy, such as performing non-drug intervention when sub-healthy or performing drug intervention when unhealthy.
Specifically, the method for determining the physiological state of the target object based on the acquired video data and physiological data of the target object and the determined video weight and physiological weight respectively corresponding to the video data and the physiological data may be: mapping the obtained physiological data and the physiological data of the target object into corresponding physiological values and video values, and calculating in a preset calculation mode based on the values and the weights of the data corresponding to the values to obtain a target result value. And comparing the target result value with preset physiological state value ranges, and determining the physiological state of the target object according to the preset physiological state value range to which the target result value belongs.
For example, the video data of the target object is mapped to a video value of 0.3, and the physiological data of the target object is mapped to a physiological value of 0.4, and the target result value of the target object is 0.37 through weighting calculation according to the corresponding weight values (i.e., 0.3 and 0.7) of the video data and the physiological data when no suggestion exists. And comparing the physiological state value corresponding to the target result value with a preset physiological health state value range, and determining that the physiological state corresponding to the target object is unhealthy.
In other embodiments, if the acquired data is acquired data of the target object under the previous intervention advice, determining a physiological state corresponding to the target object under the previous intervention advice; and determining a key factor corresponding to the physiological state, and determining a video weight corresponding to the video data and a physiological weight corresponding to the physiological data based on the key factor.
In an exemplary embodiment, when it is determined that the physiological state corresponding to the previous intervention advice of the target object is an unhealthy state, abnormal data in each acquired data of the target object is determined according to the physiological state, and a key factor corresponding to the physiological health is determined according to the abnormal data. For example, when the physiological health of the target object is unhealthy, according to the collected data, it is determined that the blood glucose is a key factor corresponding to the physiological state of the target object, and according to the collected mode of the blood glucose, it is determined that the weight corresponding to the collected data of the corresponding collected mode is larger, that is, in this embodiment, the physiological weight corresponding to the physiological data is larger than the video weight corresponding to the video data. Of course, the above methods for determining the video weights corresponding to the video data and the physiological weights corresponding to the physiological data are only optional embodiments, and the weights corresponding to the acquired data may be specifically set according to actual situations, which is not limited in this embodiment.
The technical scheme of the embodiment of the invention specifically comprises the following steps: acquiring acquisition data of a target user, wherein the acquisition data comprises video data and physiological data, and determining video weight corresponding to the video data and physiological weight corresponding to the physiological data; the physiological state of the target user is determined based on the video data, the video weight, the physiological data, and the physiological weight, and the target intervention proposal of the target user is determined based on the physiological state of the target user. According to the technical scheme provided by the embodiment of the invention, the physiological state of the target user can be more efficiently and accurately determined by determining the weights corresponding to the acquired data of the target user and based on the data and the corresponding weights, and more accurate corresponding target intervention suggestions are generated based on the physiological state, so that the service efficiency can be greatly improved, and the social resources can be saved.
The following is an embodiment of an acquired data analysis apparatus provided in the embodiment of the present invention, which belongs to the same inventive concept as the acquired data analysis method of the above embodiments, and reference may be made to the embodiment of the acquired data analysis method for details that are not described in detail in the embodiment of the acquired data analysis apparatus.
Example two
Fig. 2 is a schematic structural diagram of an acquired data analysis device according to a second embodiment of the present invention, where the present embodiment is applicable to a case of analyzing acquired data of a user, and in particular, to a case of analyzing video data and physiological data of the user to obtain a physiological state of the user, and generating a target intervention suggestion of the user according to the physiological state. The specific structure of the collected data analysis device is as follows: an acquisition data acquisition module 210, a weight determination module 220, and a target intervention suggestion generation module 230; in particular, the method comprises the steps of,
An acquisition data acquisition module 210, configured to acquire acquisition data of a target user; wherein the acquired data includes video data and physiological data;
A weight determining module 220, configured to determine a video weight corresponding to the video data and a physiological weight corresponding to the physiological data;
a target intervention proposal generation module 230 for determining a physiological state of the target user based on the video data, the video weight, the physiological data, and the physiological weight, and generating a target intervention proposal of the target user based on the physiological state.
The technical scheme of the embodiment of the invention specifically comprises the following steps: acquiring acquisition data of a target user, wherein the acquisition data comprises video data and physiological data, and determining video weight corresponding to the video data and physiological weight corresponding to the physiological data; the physiological state of the target user is determined based on the video data, the video weight, the physiological data, and the physiological weight, and the target intervention proposal of the target user is determined based on the physiological state of the target user. According to the technical scheme provided by the embodiment of the invention, the physiological state of the target user can be more efficiently and accurately determined by determining the weights corresponding to the acquired data of the target user and based on the data and the corresponding weights, and more accurate corresponding target intervention suggestions are generated based on the physiological state, so that the service efficiency can be greatly improved, and the social resources can be saved.
On the basis of the technical solution provided in the foregoing embodiment, the acquired data acquisition module 210 includes:
The video data acquisition unit is used for monitoring the preset action of the target user based on video acquisition equipment and acquiring video data of preset duration after the preset action of the target user;
the physiological data acquisition unit is used for acquiring the physiological data of the preset type of the target user in the preset time period based on the physiological signal acquisition equipment.
On the basis of the technical solution provided in the foregoing embodiment, the acquired data includes acquired data of the target object under the previous intervention advice or acquired data of the target object under the dry pre-advice;
Accordingly, the weight determining module 220 includes:
the weight determining sub-module is used for acquiring an acquisition scene of the acquisition data and determining a video weight corresponding to the video data and a physiological weight corresponding to the physiological data corresponding to the acquisition scene.
On the basis of the technical solution provided in the foregoing embodiment, the weight determining submodule includes:
An intervention type determining unit, configured to determine an intervention type of a previous intervention suggestion if the acquired data is acquired data of the target object under the previous intervention suggestion;
And the weight determining unit is used for determining the video weight corresponding to the video data and the physiological weight corresponding to the physiological data according to the intervention type.
On the basis of the technical solutions provided in the above embodiments, the intervention types include pharmaceutical intervention and non-pharmaceutical intervention;
correspondingly, the weight determining unit comprises:
the first weight determining subunit is used for presetting the physiological weight to be larger than the video weight if the intervention type is non-pharmaceutical intervention;
And the first weight determination subunit is used for presetting that the video weight is greater than the physiological weight if the intervention type is the drug intervention.
On the basis of the technical solution provided in the foregoing embodiment, the weight determining submodule further includes:
The physiological state determining unit is used for determining the corresponding physiological state of the target object under the previous intervention advice if the acquired data is acquired data of the target object under the previous intervention advice;
And the physiological weight determining unit is used for determining key factors corresponding to the physiological states, and determining video weights corresponding to the video data and physiological weights corresponding to the physiological data based on the key factors.
Based on the technical solutions provided in the foregoing embodiments, the target intervention suggestion generating module 230 includes:
And the target intervention advice generation unit is used for comparing the physiological state with a preset intervention state threshold value and generating target intervention advice of the target user according to the comparison result.
The acquired data analysis device provided by the embodiment of the invention can execute the acquired data analysis method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
It should be noted that, in the embodiment of the collected data analysis device, each unit and module included are only divided according to the functional logic, but not limited to the above-mentioned division, so long as the corresponding functions can be implemented; in addition, the specific names of the functional units are also only for distinguishing from each other, and are not used to limit the protection scope of the present invention.
The following is an embodiment of an acquired data analysis apparatus provided in the embodiment of the present invention, which belongs to the same inventive concept as the acquired data analysis method of the above embodiments, and reference may be made to the embodiment of the acquired data analysis method for details that are not described in detail in the embodiment of the acquired data analysis apparatus.
Example III
Fig. 3 is a schematic structural diagram of an analysis system for collected data according to a third embodiment of the present invention, where the present embodiment is applicable to a case of analyzing collected data of a user, and in particular, to a case of analyzing video data and physiological data of the user to obtain a physiological state of the user, and generating a target intervention suggestion of the user according to the physiological state. The specific structure of the collected data analysis system is as follows: a data acquisition subsystem 310, the data analysis subsystem 320, and an intervention subsystem 330; in particular, the method comprises the steps of,
The data acquisition subsystem 310 is configured to acquire acquisition data of a target user, where the acquisition data includes video data and physiological data;
The data analysis subsystem 320 is configured to receive video data and physiological data of a target user; determining a video weight corresponding to the video data and a physiological weight corresponding to the physiological data; and determining a physiological state of the target user based on the video data, the video weight, the physiological data, and the physiological weight, and generating a target intervention proposal for the target user based on the physiological state;
The intervention subsystem 330 is configured to prompt the target user to execute the target intervention advice based on the target intervention advice.
The technical scheme of the embodiment of the invention specifically comprises the following steps: acquiring acquisition data of a target user, wherein the acquisition data comprises video data and physiological data, and determining video weight corresponding to the video data and physiological weight corresponding to the physiological data; the physiological state of the target user is determined based on the video data, the video weight, the physiological data, and the physiological weight, and the target intervention proposal of the target user is determined based on the physiological state of the target user. According to the technical scheme provided by the embodiment of the invention, the physiological state of the target user can be more efficiently and accurately determined by determining the weights corresponding to the acquired data of the target user and based on the data and the corresponding weights, and more accurate corresponding target intervention suggestions are generated based on the physiological state, so that the service efficiency can be greatly improved, and the social resources can be saved.
On the basis of the technical solution provided in the foregoing embodiment, the system further includes: a digital twinning subsystem; wherein,
The digital twin subsystem is used for comparing the digital twin processing result with the acquired data under the target intervention proposal so as to determine an execution result of the target intervention proposal.
On the basis of the above embodiment, the present embodiment further provides an optional embodiment, which specifically introduces an interaction flow of each subsystem in the present system. Specifically, as shown in fig. 4:
In the embodiment, a user collects video data of a preset action of the user through a camera and uploads the video data to a data analysis subsystem; the user can also collect physiological data of the physiological signal of the preset type of the user through the physiological signal collection device and upload the physiological data to the data analysis subsystem.
Optionally, the data analysis subsystem acquires video data physiological data of the user, and because the current acquisition scene is the dry pre-suggestion, calculates a target result value of the user according to the video weight and the physiological weight corresponding to each acquisition data during the dry pre-suggestion, determines a physiological state of the user according to the target result value, and generates the first intervention suggestion according to the physiological state.
Optionally, the intervention subsystem reminds the user to execute the intervention advice based on the generated target intervention advice, monitors the user, and gives a corresponding reminder when the user does not execute the intervention advice. The intervention subsystem can also receive and process the intervention advice returned by the cloud of the system, and control corresponding hardware to realize healthy intervention on the user, such as controlling the type of medicines for the user to take, such as controlling and changing the dosage of medicine reagents which the user needs to self-inject, so as to achieve the purpose of adjusting the diagnosis and treatment intervention of the user.
Optionally, in a preset time period, physiological data and video data of the target object under the proposal of the first intervention are collected and uploaded to a data analysis subsystem;
Optionally, the data analysis subsystem determines a physiological state of the target object according to each acquired data and the video weight and the physiological weight corresponding to each acquired data under the previous intervention advice, and determines a second intervention advice according to the physiological state.
Optionally, the intervention subsystem continues to alert and supervise the user to execute the intervention advice based on the second intervention advice.
Optionally, the technical solution of the above embodiment is circulated, and the intervention technology is not performed on the user when the physiological state of the target object is a healthy state, but at this time, the user may be continuously monitored and the acquired data may be uploaded at a preset time interval, and the acquired data may be analyzed to determine the physiological state of the target object, until the physiological state is sub-healthy or unhealthy, and the intervention suggestion is continued on the user.
On the basis of the above embodiment, the present embodiment further includes, when the generation data analysis subsystem generates the intervention advice each time, synchronously transmitting the intervention advice to a digital twin sub-model, specifically, a twin model of the target object built based on each video data and physiological data of the target object; when each intervention suggestion is received, the digital twin sub-model executes the intervention suggestion on the twin model of the target object, acquires video data and physiological data under the previous intervention suggestion, compares the acquired data with the acquired video data and physiological data of the target object to determine a comparison result of the target intervention suggestion, and determines that the intervention suggestion needs to be adjusted according to the comparison result.
The acquired data analysis device provided by the embodiment of the invention can execute the acquired data analysis method provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
Example IV
Fig. 5 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present invention. Fig. 5 illustrates a block diagram of an exemplary electronic device 12 suitable for use in implementing embodiments of the present invention. The electronic device 12 shown in fig. 5 is merely an example and should not be construed as limiting the functionality and scope of use of embodiments of the present invention.
As shown in fig. 5, the electronic device 12 is in the form of a general purpose computing electronic device. Components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, a bus 18 that connects the various system components, including the system memory 28 and the processing units 16.
Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, and a local bus using any of a variety of bus architectures. By way of example, and not limitation, such architectures include Industry Standard Architecture (ISA) bus, micro channel architecture (MAC) bus, enhanced ISA bus, video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.
Electronic device 12 typically includes a variety of computer system readable media. Such media can be any available media that is accessible by electronic device 12 and includes both volatile and nonvolatile media, removable and non-removable media.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM) 30 and/or cache memory 32. The electronic device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from or write to non-removable, nonvolatile magnetic media (not shown in FIG. 5, commonly referred to as a "hard disk drive"). Although not shown in fig. 5, a magnetic disk drive for reading from and writing to a removable non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive for reading from or writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In such cases, each drive may be coupled to bus 18 through one or more data medium interfaces. The system memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to carry out the functions of the embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored in, for example, system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each or some combination of which may include an implementation of a network environment. Program modules 42 generally perform the functions and/or methods of the embodiments described herein.
The electronic device 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), one or more devices that enable a user to interact with the electronic device 12, and/or any devices (e.g., network card, modem, etc.) that enable the electronic device 12 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 22. Also, the electronic device 12 may communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet, through a network adapter 20. As shown in fig. 5, the network adapter 20 communicates with other modules of the electronic device 12 over the bus 18. It should be appreciated that although not shown in fig. 5, other hardware and/or software modules may be used in connection with electronic device 12, including, but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.
The processing unit 16 executes various functional applications and sample data acquisition by running programs stored in the system memory 28, for example, implementing the steps of an acquired data analysis method provided in the present embodiment, the acquired data analysis method includes:
Acquiring acquisition data of a target user; wherein the acquired data includes video data and physiological data; determining video weights corresponding to the video data and physiological weights corresponding to the physiological data;
A physiological state of the target user is determined based on the video data, the video weights, the physiological data, and the physiological weights, and a target intervention proposal for the target user is generated based on the physiological state.
Of course, those skilled in the art will appreciate that the processor may also implement the technical solution of the sample data obtaining method provided in any embodiment of the present invention.
Example five
The fifth embodiment provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements, for example, the steps of an acquired data analysis method provided by the present embodiment, and the acquired data analysis method includes:
acquiring acquisition data of a target user; wherein the acquired data includes video data and physiological data;
Determining video weights corresponding to the video data and physiological weights corresponding to the physiological data;
A physiological state of the target user is determined based on the video data, the video weights, the physiological data, and the physiological weights, and a target intervention proposal for the target user is generated based on the physiological state.
The computer storage media of embodiments of the invention may take the form of any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. The computer readable storage medium may be, for example, but not limited to: an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations of the present invention may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
It will be appreciated by those of ordinary skill in the art that the modules or steps of the invention described above may be implemented in a general purpose computing device, they may be centralized on a single computing device, or distributed over a network of computing devices, or they may alternatively be implemented in program code executable by a computer device, such that they are stored in a memory device and executed by the computing device, or they may be separately fabricated as individual integrated circuit modules, or multiple modules or steps within them may be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
Note that the above is only a preferred embodiment of the present invention and the technical principle applied. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, while the invention has been described in connection with the above embodiments, the invention is not limited to the embodiments, but may be embodied in many other equivalent forms without departing from the spirit or scope of the invention, which is set forth in the following claims.
Claims (6)
1. A method of analyzing collected data, comprising:
acquiring acquisition data of a target user; wherein the acquired data includes video data and physiological data;
Determining video weights corresponding to the video data and physiological weights corresponding to the physiological data;
determining a physiological state of the target user based on the video data, the video weight, the physiological data, and the physiological weight, and generating a target intervention proposal for the target user based on the physiological state;
The acquired data comprise the acquired data of the target object under the previous intervention proposal;
Correspondingly, the determining the video weight corresponding to the video data and the physiological weight corresponding to the physiological data includes:
Acquiring an acquisition scene of the acquisition data, and determining a video weight corresponding to the video data and a physiological weight corresponding to the physiological data corresponding to the acquisition scene;
The acquiring the acquisition scene of the acquisition data comprises the following steps:
Determining an acquisition scene of the acquired acquisition data through the acquired data type of the acquisition data;
the determining the video weight corresponding to the video data and the physiological weight corresponding to the physiological data corresponding to the acquisition scene includes:
if the acquired data is the acquired data of the target object under the previous intervention proposal, determining the intervention type of the previous intervention proposal;
determining a video weight corresponding to the video data and a physiological weight corresponding to the physiological data according to the intervention type;
Wherein the types of intervention include pharmaceutical intervention and non-pharmaceutical intervention;
Correspondingly, the determining the video weight corresponding to the video data and the physiological weight corresponding to the physiological data includes:
If the intervention type is non-pharmaceutical intervention, presetting that the physiological weight is greater than the video weight;
If the intervention type is drug intervention, presetting that the video weight is greater than the physiological weight;
the determining the video weight corresponding to the video data and the physiological weight corresponding to the physiological data corresponding to the acquisition scene further includes:
If the acquired data is the acquired data of the target object under the previous intervention suggestion, determining a corresponding physiological state of the target object under the previous intervention suggestion;
and determining a key factor corresponding to the physiological state, and determining a video weight corresponding to the video data and a physiological weight corresponding to the physiological data based on the key factor.
2. The method of claim 1, wherein the acquiring the acquisition data of the target user comprises:
Monitoring a preset action of the target user based on video acquisition equipment, and acquiring video data of preset duration after the preset action of the target user;
And acquiring physiological data of a preset type of the target user in a preset time period based on a physiological signal acquisition device.
3. The method of claim 1, wherein the generating the target intervention proposal for the target user based on the physiological state comprises:
comparing the physiological state with a preset intervention state threshold value, and generating a target intervention suggestion of the target user according to the comparison result.
4. An acquired data analysis apparatus, comprising:
The acquisition data acquisition module is used for acquiring acquisition data of a target user; wherein the acquired data includes video data and physiological data;
The weight determining module is used for determining the video weight corresponding to the video data and the physiological weight corresponding to the physiological data;
a target intervention proposal generation module for determining a physiological state of the target user based on the video data, the video weight, the physiological data, and the physiological weight, and generating a target intervention proposal of the target user based on the physiological state;
The acquired data comprise the acquired data of the target object under the previous intervention proposal;
the weight determination module includes:
The weight determining submodule is used for acquiring an acquisition scene of the acquisition data and determining a video weight corresponding to the video data corresponding to the acquisition scene and a physiological weight corresponding to the physiological data;
The acquiring the acquisition scene of the acquisition data comprises the following steps:
Determining an acquisition scene of the acquired acquisition data through the acquired data type of the acquisition data;
the weight determination submodule includes:
An intervention type determining unit, configured to determine an intervention type of a previous intervention suggestion if the acquired data is acquired data of the target object under the previous intervention suggestion;
The weight determining unit is used for determining the video weight corresponding to the video data and the physiological weight corresponding to the physiological data according to the intervention type;
Wherein the types of intervention include pharmaceutical intervention and non-pharmaceutical intervention;
Correspondingly, the weight determining unit comprises:
the first weight determining subunit is used for presetting the physiological weight to be larger than the video weight if the intervention type is non-pharmaceutical intervention; if the intervention type is drug intervention, presetting that the video weight is greater than the physiological weight;
The weight determination submodule further includes:
The physiological state determining unit is used for determining the corresponding physiological state of the target object under the previous intervention advice if the acquired data is acquired data of the target object under the previous intervention advice;
And the physiological weight determining unit is used for determining key factors corresponding to the physiological states, and determining video weights corresponding to the video data and physiological weights corresponding to the physiological data based on the key factors.
5. A collected data analysis system, characterized by being applied to the collected data analysis method as claimed in any one of claims 1 to 3, comprising: a data acquisition subsystem, a data analysis subsystem and an intervention subsystem; wherein:
The data acquisition subsystem is used for acquiring acquisition data of a target user, wherein the acquisition data comprises video data and physiological data;
the data analysis subsystem is used for receiving video data and physiological data of a target user; determining a video weight corresponding to the video data and a physiological weight corresponding to the physiological data; and determining a physiological state of the target user based on the video data, the video weight, the physiological data, and the physiological weight, and generating a target intervention proposal for the target user based on the physiological state;
The intervention subsystem is used for reminding the target user of executing the target intervention advice based on the target intervention advice.
6. The system of claim 5, further comprising a digital twinning subsystem;
The digital twin subsystem is used for comparing the digital twin processing result with the acquired data under the target intervention advice so as to determine the execution result of the target intervention advice.
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