CN113066589A - Collected data analysis method and device, electronic equipment and storage medium - Google Patents
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Abstract
The embodiment of the invention discloses a method and a device for analyzing collected data, electronic equipment and a storage medium. The method comprises the following steps: acquiring collected data of a target user; wherein the collected data comprises video data and physiological data; determining a video weight corresponding to the video data and a physiological weight corresponding to the physiological data; determining a physiological state of the target user based on the video data, the video weights, the physiological data, and the physiological weights, and generating a target intervention recommendation for the target user based on the physiological state. By the technical scheme disclosed by the embodiment of the invention, the data of the user can be efficiently analyzed, the service suggestion can be intelligently pushed, the medicine intake and the chronic disease treatment of the user can be remotely intervened, the service efficiency can be greatly improved, and the social resources can be 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 collected data, electronic equipment and a storage medium.
Background
The proportion of the chronic diseases of the old is high, most of the chronic disease old patients need to continuously seek medical treatment and perform medical examination and medicine intervention, various inconveniences exist when the old patients go to a hospital to seek medical treatment, the efficiency of seeking medical treatment of the hospital is generally low, the treatment is not very timely once symptoms appear, meanwhile, the frequency of self-examination of the old people at home is low due to insufficient examination frequency, the accuracy of reading self-service household examination equipment is not enough, the old people can not find the change of the symptoms of the old people in time due to the untimely conditions, even the old people cannot intervene in time through treatment means, and the illness state is delayed. According to the prior art, doctors only have two channels to communicate with elderly chronic patients, or communicate with the patients face to face through an off-line clinic and perform diagnosis communication through examination and examination sheets, or communicate with the elderly through videos or voices on a pure line, and do not have enough data to assist doctors in accurately judging the state of the elderly, and the doctors cannot perform health maintenance work.
Disclosure of Invention
The invention provides a method and a device for analyzing collected data, electronic equipment and a storage medium, which can efficiently analyze data of a user, intelligently push service suggestions, greatly improve service efficiency and save social resources.
In a first aspect, an embodiment of the present invention provides a collected data analysis method, where the method includes:
acquiring collected data of a target user; wherein the collected data comprises video data and physiological data;
determining a video weight corresponding to the video data and a physiological weight corresponding to the physiological data;
determining a physiological state of the target user based on the video data, the video weights, the physiological data, and the physiological weights, and generating a target intervention recommendation for the target user based on the physiological state.
In a second aspect, an embodiment of the present invention further provides an apparatus for analyzing collected data, where the apparatus includes:
the acquisition module of the collected data, is used for obtaining the collected data of the target user; wherein the collected data comprises video data and physiological data;
the weight determining module is used for determining a video weight corresponding to the video data and a physiological weight corresponding to the physiological data;
a target intervention suggestion generation module to determine a physiological state of the target user based on the video data, the video weights, the physiological data, and the physiological weights, and generate a target intervention suggestion for the target user based on the physiological state.
In a third aspect, an embodiment of the present invention further provides a collected data analysis system, which is applied to the collected data analysis method described in any one of the above embodiments, and the system includes: the system comprises 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 weights, the physiological data, and the physiological weights, and generating a target intervention recommendation for the target user based on the physiological state;
the intervention subsystem is used for reminding the target user to execute the target intervention suggestion based on the target intervention suggestion.
The technical scheme of the embodiment of the invention specifically comprises the following steps: acquiring collected data of a target user, wherein the collected data comprises video data and physiological data, and determining a video weight corresponding to the video data and a physiological weight corresponding to the physiological data; determining a physiological state of the target user based on the video data, video weights, physiological data, and physiological weights, and determining a target intervention recommendation for the target user based on the physiological state of the target user. According to the technical scheme provided by the embodiment of the invention, the corresponding weight of each acquired data of the target user is determined, the physiological state of the target user can be more efficiently and accurately determined based on each data and the corresponding weight, and a more accurate corresponding target intervention suggestion is generated based on the physiological state, so that the service efficiency can be greatly improved, and social resources are saved.
Drawings
In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, a brief description is given below of the drawings used in describing the embodiments. It should be clear that the described figures are only views of some of the embodiments of the invention to be described, not all, and that for a person skilled in the art, other figures can be derived from these figures without inventive effort.
Fig. 1 is a schematic flow chart of a collected data analysis method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of a collected data analysis apparatus according to a second embodiment of the present invention;
fig. 3 is a schematic structural diagram of a collected data analysis system according to a third embodiment of the present invention;
FIG. 4 is a schematic diagram of an interaction flow of a collected data analysis method according to a third embodiment of the present invention
Fig. 5 is a schematic structural diagram of an electronic device according to a fourth embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Example one
Fig. 1 is a flowchart of a collected data analysis method according to an embodiment of the present invention, where the present embodiment is applicable to a situation of analyzing collected data of a user, and in particular, to a situation of analyzing video data and physiological data of a 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 a collected data analysis apparatus, which may be implemented by means of software and/or hardware.
Before the technical solution of the embodiment of the present invention is introduced, an application scenario of the embodiment is introduced exemplarily: in the prior art, the old people generally need to carry out a plurality of times of examination and treatment on chronic diseases, but the old people are inconvenient to go to a hospital for medical treatment for a plurality of times due to various reasons, so that the change of diseases cannot be found in time, the examination items and the treatment scheme cannot be adjusted in time, and the illness state of the patients is delayed.
In order to solve the above technical problem, in the technical scheme of this embodiment, a video capture device is preset in a daily activity range of a target user, and a wearable device or a portable physiological signal capture device capable of capturing preset physiological data is preset. And acquiring the acquisition data of the target user based on preset acquisition conditions, the video acquisition device and the physiological signal acquisition equipment. Specifically, the collected data includes video data and physiological data. Determining each weight corresponding to each acquired data of the target user according to the acquisition scene; determining the physiological state of a target user according to the data and the corresponding weights, 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 efficiently analyzed, and the service suggestion is intelligently pushed, so that the service efficiency can be greatly improved, and social resources are saved.
As shown in fig. 1, the method specifically includes the following steps:
s110, acquiring collected data of a target user; wherein the collected data comprises 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 time length acquired by the video acquisition device when the target user performs a preset physiological action such as taking medicine, lying in bed, sleeping, eating, etc. The physiological data is based on physiological data corresponding to preset type physiological signals acquired by wearable equipment and other physiological signal acquisition equipment, for example, the preset type physiological signals can be electrocardio, electroencephalogram, blood pressure, blood oxygen, blood sugar and other physiological signals; of course, in other embodiments, the psychological data further includes physiological data collected by each sensor configured on the signal collecting device, and data such as the collected exercise step number, sleep time, and the like may also be taken as the physiological data.
The method for acquiring the collected data of the target user may be: 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; the method comprises the steps of acquiring preset type physiological data of a target user in a preset time period based on physiological signal acquisition equipment.
Specifically, a camera may be used to perform video monitoring on a target user, and when a preset action occurs to the target user, a video with a preset duration after the action occurs is collected as video data; of course, the video collection may also be started when the target user has a preset action, and the video collection is stopped when it is detected that the target user has finished the preset action, and the video collected during the preset action is used as the video data. Illustratively, when the action of the target user eating is collected, the collection of the video data of the target user is started, and the collection is finished after fifteen minutes of the preset eating, the fifteen minutes of the video is used as the video data of the target user under the eating action, of course, the target user stops eating after five minutes, the collection of the video is stopped after the target user finishes eating, and the video during the starting collection of the eating action and the stopping collection of the video after the ending of the eating action are used as the video data of the target user under the eating action.
Specifically, the physiological data corresponding to the preset type of physiological signal of the target user may be acquired by using a physiological signal acquisition device, the physiological signal acquisition device may include but is not limited to wearable devices, portable monitors, and other devices, and the preset type of physiological signal may be a physiological signal such as blood sugar, blood pressure, blood oxygen, and the like. Of course, the type of the physiological signal to be acquired may also be preset, and the preset acquisition time interval is preset to acquire the preset type of physiological signal of the target user to obtain the physiological signal. For example, the blood glucose of the target subject may be detected by the blood glucose detection device and blood glucose data of the target subject may be acquired based on the blood glucose detection device respectively in half an hour before eating and half an hour after eating each day.
And 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 acquired data, and determining video weight corresponding to video data corresponding to the acquisition scene and physiological weight corresponding to the physiological data. In other words, the method for determining the acquisition scene of the acquired data may be to determine the acquisition scene of the acquired data by determining the data type of the acquired data. Specifically, the data type of the acquired acquisition data includes acquisition data of the target object under the previous intervention suggestion or acquisition data of the target object when there is no intervention suggestion.
Specifically, the data type of the collected data is determined, when the collected data is the collected data of the target object without the intervention suggestion, the video weight corresponding to the video data and the physiological weight corresponding to the physiological data may be preset, for example, each weight may be set to be equal weight, that is, each weight is 0.5, or each weight may be set to be 1, and the present embodiment does not limit the proportion and the value of the weight setting corresponding to each data. Specifically, when the collected data is the collected data of the target object under the previous intervention suggestion, the intervention type of the intervention suggestion is determined, and the video weight and the physiological weight corresponding to the video data and the physiological data are determined according to the intervention type. Wherein the intervention type comprises a pharmaceutical intervention and a non-pharmaceutical intervention. The medicine intervention comprises but is not limited to intervention suggestions such as injection, prescription and the like for a target user; non-pharmaceutical interventions may include, but are not limited to, intervention recommendations for exercising, sleeping, and sensitive food eating by the target user. Optionally, when the intervention type is drug intervention, the preset physiological weight is greater than the video weight; when the intervention type is non-drug 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, the weights corresponding to the two collected 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 may be specifically set according to actual situations, and the ratio of the two weights is not limited in this embodiment.
Illustratively, when the intervention type of the intervention suggestion on the target object is determined to be drug intervention, that is, an injection intervention suggestion is made, it is determined that the video weight corresponding to the video data of the acquired target object under the current situation is 0.7, and then the physiological weight corresponding to the corresponding physiological data is 0.3; the beneficial effect of the current setting proportion lies in: whether there is an intervention recommendation to execute may be determined from the video data and the results of the execution of the target object may be rapid.
Illustratively, when the intervention type of the intervention suggestion on the target object is determined to be non-drug intervention, namely motion intervention, the video weight corresponding to the video data of the acquired target object under the current condition is determined to be 0.2, and the physiological weight corresponding to the corresponding physiological data is 0.8; the beneficial effect of the current setting proportion lies in: whether the target subject performs the intervention result can be known from the number of moving steps in the physiological data, and the execution result of the target subject can be quickly obtained.
In some alternative embodiments, the video data may include, but is not limited to, sleep data, food intake data, exercise data, and the like, 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, and the like, for example. After the weights of the physiological data and the video data are determined, the weights of all types of data are determined according to the weights of the physiological data and the weight proportion of all types of data in the physiological data, and the specific weights of the sleep data, the food intake data and the motion data are determined according to the weights of the video data and the weight proportion of the sleep data, the food intake data and the motion data. Wherein, 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 the sleep data, the food intake data and the exercise data. Further, when there is no intervention suggestion, the weight proportion of the above types of data, and the weight proportion of the sleep data, the food intake data and the exercise data may be preset and may be directly called; in the presence of the previous intervention suggestion, the weight proportion of each type of data and the weight proportion of the sleep data, the food intake data and the exercise data are determined according to the specific content of the intervention suggestion. Optionally, if the plurality of pre-suggestions include a suggestion for any type of physiological data about a drug, the weight of the type of physiological data is increased, and if the plurality of pre-suggestions include a suggestion for any one of sleep data, food intake data and exercise data, the weight of the corresponding sleep data, food intake data and exercise data in the intervention suggestion is increased. The weight of any data can be adjusted by presetting a weight adjusting rule, for example, the weight ratio of data corresponding to the intervention suggestion is greater than 0.5, the intervention suggestion illustratively includes a blood sugar intervention drug, then the weight ratio of blood sugar is greater than 0.5, and the pre-suggestions include suggestions for sleeping and exercising, then the weight ratio of sleeping data and exercising data is greater than 0.5.
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 suggestion of the target user based on the physiological state.
In an embodiment of the present invention, the physiological state may include a physical state of whether the target subject is healthy, and specifically, the physiological state includes, but is not limited to, a healthy state or an unhealthy state, and may also include a sub-healthy state in some embodiments. The intervention recommendations may be corresponding intervention recommendations generated from respective physiological states. Specifically, an intervention suggestion that the target subject is not intervened when the physiological state of the target subject is healthy can be included; or an intervention suggestion for performing different degrees of intervention on the target when the physiological state of the target object is sub-healthy or unhealthy, for example, performing non-drug intervention in sub-healthy state and performing drug intervention in unhealthy state.
Specifically, the method for determining the physiological status of the target object based on the collected video data and physiological data of the target object and the video weight and physiological weight respectively corresponding to the determined video data and physiological data may be: mapping the acquired physiological data and physiological data of the target object into corresponding physiological numerical values and video numerical values, and calculating in a preset calculation mode based on the numerical values and the weight of the data corresponding to the numerical 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.
Illustratively, 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 a target result value of 0.37 is obtained through weighting calculation according to corresponding weight values (i.e. 0.3 and 0.7) of the video data and the physiological data when there is no suggestion. 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 an unhealthy state.
In other embodiments, if the collected data is the data collected for the target object under the previous intervention suggestion, determining the physiological state of the target object corresponding to the previous intervention suggestion; and determining key factors corresponding to the physiological state, and determining video weight corresponding to the video data and physiological weight corresponding to the physiological data based on the key factors.
Illustratively, when the physiological state corresponding to the last intervention suggestion of the target object is determined to be an unhealthy state, abnormal data in all collected data of the target object is determined according to the physiological state, and key factors corresponding to physiological health are determined according to the abnormal data. For example, when the physiological health of the target object is unhealthy, if the value of the blood glucose data of the target object is found to be abnormal 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 it is determined that the weight corresponding to the collected data of the corresponding collection mode is larger according to the collection mode of the blood glucose, 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 weight corresponding to the video data and the physiological weight corresponding to the physiological data are only used as optional embodiments, and each weight corresponding to each collected data may also 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 collected data of a target user, wherein the collected data comprises video data and physiological data, and determining a video weight corresponding to the video data and a physiological weight corresponding to the physiological data; determining a physiological state of the target user based on the video data, video weights, physiological data, and physiological weights, and determining a target intervention recommendation for the target user based on the physiological state of the target user. According to the technical scheme provided by the embodiment of the invention, the corresponding weight of each acquired data of the target user is determined, the physiological state of the target user can be more efficiently and accurately determined based on each data and the corresponding weight, and a more accurate corresponding target intervention suggestion is generated based on the physiological state, so that the service efficiency can be greatly improved, and social resources are saved.
The following is an embodiment of the collected data analysis apparatus provided in the embodiment of the present invention, and the apparatus and the collected data analysis method in the above embodiments belong to the same inventive concept, and details that are not described in detail in the embodiment of the collected data analysis apparatus may refer to the embodiment of the collected data analysis method described above.
Example two
Fig. 2 is a schematic structural diagram of a collected data analysis apparatus according to a second embodiment of the present invention, which is applicable to a situation of analyzing collected data of a user, and in particular, is applicable to a situation of analyzing video data and physiological data of a 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: the collected data acquisition module 210, the weight determination module 220 and the target intervention suggestion generation module 230; in particular, the method comprises the following steps of,
a collected data acquiring module 210, configured to acquire collected data of a target user; wherein the collected data comprises 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 suggestion generation module 230, configured to determine a physiological state of the target user based on the video data, the video weights, the physiological data, and the physiological weights, and generate a target intervention suggestion for the target user based on the physiological state.
The technical scheme of the embodiment of the invention specifically comprises the following steps: acquiring collected data of a target user, wherein the collected data comprises video data and physiological data, and determining a video weight corresponding to the video data and a physiological weight corresponding to the physiological data; determining a physiological state of the target user based on the video data, video weights, physiological data, and physiological weights, and determining a target intervention recommendation for the target user based on the physiological state of the target user. According to the technical scheme provided by the embodiment of the invention, the corresponding weight of each acquired data of the target user is determined, the physiological state of the target user can be more efficiently and accurately determined based on each data and the corresponding weight, and a more accurate corresponding target intervention suggestion is generated based on the physiological state, so that the service efficiency can be greatly improved, and social resources are saved.
On the basis of the technical solution provided by the above embodiment, the collected data obtaining 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;
and the physiological data acquisition unit is used for acquiring the preset type of physiological data of the target user in a preset time period based on the physiological signal acquisition equipment.
On the basis of the technical solution provided by the above embodiment, the acquired data includes acquired data of the target object under the previous intervention suggestion or acquired data of the target object without the intervention suggestion;
accordingly, the weight determination module 220 includes:
the weight determining submodule is used for acquiring an acquisition scene of the acquired 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.
On the basis of the technical solution provided by the above embodiment, the weight determining submodule includes:
the intervention type determining unit is used for determining the intervention type of the 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 scheme provided by the embodiment, the intervention types comprise pharmaceutical intervention and non-pharmaceutical intervention;
correspondingly, the weight determination unit comprises:
a first weight determining subunit, configured to preset that the physiological weight is greater than the video weight if the intervention type is non-drug intervention;
a first weight determining subunit, configured to preset that the video weight is greater than the physiological weight if the intervention type is a drug intervention.
On the basis of the technical solution provided by the above 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 last intervention suggestion if the acquired data is acquired data of the target object under the last intervention suggestion;
and the physiological weight determining unit is used for determining key factors corresponding to the physiological state and determining the video weight corresponding to the video data and the physiological weight corresponding to the physiological data based on the key factors.
On the basis of the technical solution provided by the above embodiment, the target intervention suggestion generation module 230 includes:
and the target intervention suggestion generation unit is used for comparing the physiological state with a preset intervention state threshold value and generating a target intervention suggestion of the target user according to a comparison result.
The collected data analysis device provided by the embodiment of the invention can execute the collected data analysis method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
It should be noted that, in the embodiment of the collected data analysis apparatus, each included unit and each included module are only divided according to functional logic, but are not limited to the above division, as long as corresponding functions can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
The following is an embodiment of the collected data analysis apparatus provided in the embodiment of the present invention, and the apparatus and the collected data analysis method in the above embodiments belong to the same inventive concept, and details that are not described in detail in the embodiment of the collected data analysis apparatus may refer to the embodiment of the collected data analysis method described above.
EXAMPLE III
Fig. 3 is a schematic structural diagram of a collected data analysis system according to a third embodiment of the present invention, which is applicable to a situation of analyzing collected data of a user, specifically, a situation of analyzing video data and physiological data of a 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, a data analysis subsystem 320 and an intervention subsystem 330; in particular, the method comprises the following steps of,
the data acquisition subsystem 310 is configured to acquire acquired data of a target user, where the acquired data includes video data and physiological data;
the data analysis subsystem 320 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 weights, the physiological data, and the physiological weights, and generating a target intervention recommendation 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 recommendation based on the target intervention recommendation.
The technical scheme of the embodiment of the invention specifically comprises the following steps: acquiring collected data of a target user, wherein the collected data comprises video data and physiological data, and determining a video weight corresponding to the video data and a physiological weight corresponding to the physiological data; determining a physiological state of the target user based on the video data, video weights, physiological data, and physiological weights, and determining a target intervention recommendation for the target user based on the physiological state of the target user. According to the technical scheme provided by the embodiment of the invention, the corresponding weight of each acquired data of the target user is determined, the physiological state of the target user can be more efficiently and accurately determined based on each data and the corresponding weight, and a more accurate corresponding target intervention suggestion is generated based on the physiological state, so that the service efficiency can be greatly improved, and social resources are saved.
On the basis of the technical scheme provided by the above embodiment, the system further comprises: a digital twin subsystem; wherein,
and the digital twin subsystem is used for comparing the digital twin processing result with the acquired data under the target intervention suggestion to determine the execution result of the target intervention suggestion.
On the basis of the above embodiments, this embodiment also provides an optional embodiment, which specifically introduces an interaction flow of each subsystem in the system. Specifically, as shown in fig. 4:
in this embodiment, a user acquires 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 acquire physiological data of preset physiological signals of the user through the physiological signal acquisition equipment and upload the physiological data to the data analysis subsystem.
Optionally, the data analysis subsystem obtains video data physiological data of the user, and when the current collection scene is a non-intervention suggestion, calculates a target result value of the user according to the video weight and the physiological weight corresponding to each collected data when the non-intervention suggestion exists, determines a physiological state of the user according to the target result value, and generates a first intervention suggestion according to the physiological state.
Optionally, the intervention subsystem prompts the user to execute the intervention suggestion based on the generated target intervention suggestion, monitors the user, and gives a corresponding prompt when the user does not execute the intervention suggestion. The intervention subsystem can also receive and process the intervention suggestion returned by the cloud of the system, and control corresponding hardware to realize health intervention on the user, such as controlling the type of medicine provided for the user to take, for example, controlling and changing the dosage of medicine reagents required to be injected by the user in a self-service manner, so that the aim of adjusting diagnosis and treatment intervention of the user is fulfilled.
Optionally, in a preset time period, acquiring physiological data and video data of the target subject based on the first intervention suggestion and uploading the physiological data and the video data to the data analysis subsystem;
optionally, the data analysis subsystem determines the physiological state of the target object according to the acquired data and the video weight and the physiological weight corresponding to the acquired data in the previous intervention suggestion, and determines the second intervention suggestion according to the physiological state.
Optionally, the intervention subsystem continues to prompt and supervise the user for execution of the intervention recommendation based on the second intervention recommendation.
Optionally, the technical solution of the above embodiment is circulated, and when the physiological state of the target object is a healthy state, no intervention technology is performed on the user, but at this time, the user may be continuously monitored, the collected data may be uploaded at a preset time interval, and the collected data may be analyzed to determine the physiological state of the target object, until the physiological state is sub-healthy or unhealthy, an intervention suggestion may be continuously performed on the user.
On the basis of the above embodiment, the embodiment further includes that, when the generated data analysis subsystem generates the intervention advice each time, the intervention advice is synchronously sent to a digital twin submodel, specifically, the submodel has a twin model of the target object established based on the video data and the physiological data of the target object; when the digital twin submodel receives each intervention suggestion, the intervention suggestion is executed on the twin model of the target object, video data and physiological data under the last intervention suggestion are obtained, the obtained data are compared with the collected video data and physiological data of the target object, the comparison result of the target intervention suggestion is determined, and the intervention suggestion is determined to be required to be adjusted according to the comparison result.
The collected data analysis device provided by the embodiment of the invention can execute the collected data analysis method provided by any embodiment of the invention, and has corresponding functional modules and beneficial effects of the execution method.
Example four
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 only an example and should not bring any limitation to the function and the scope of use of the embodiment of the present invention.
As shown in FIG. 5, electronic device 12 is embodied in the form of a general purpose computing electronic device. The components of electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.
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 and write to non-removable, nonvolatile magnetic media (not shown in FIG. 5, and commonly referred to as a "hard drive"). Although not shown in FIG. 5, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. System memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in 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 of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally carry out the functions and/or methodologies of the described embodiments of the invention.
The processing unit 16 executes various functional applications and sample data acquisition by running the program stored in the system memory 28, for example, implementing the steps of the collected data analysis method provided in this embodiment, where the collected data analysis method includes:
acquiring collected data of a target user; wherein the collected data comprises video data and physiological data; determining a video weight corresponding to the video data and a physiological weight corresponding to the physiological data;
determining a physiological state of the target user based on the video data, the video weights, the physiological data, and the physiological weights, and generating a target intervention recommendation for the target user based on the physiological state.
Of course, those skilled in the art can understand 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, on which a computer program is stored, where the computer program, when executed by a processor, implements, for example, the steps of the collected data analysis method provided in the fifth embodiment of the present invention, where the collected data analysis method includes:
acquiring collected data of a target user; wherein the collected data comprises video data and physiological data;
determining a video weight corresponding to the video data and a physiological weight corresponding to the physiological data;
determining a physiological state of the target user based on the video data, the video weights, the physiological data, and the physiological weights, and generating a target intervention recommendation for the target user based on the physiological state.
Computer storage media for embodiments of the invention may employ 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 any combination thereof. 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 the context of 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.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. 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 for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like 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 type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It will be understood by those skilled in the art that the modules or steps of the invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of computing devices, and optionally they may be implemented by program code executable by a computing device, such that it may be stored in a memory device and executed by a computing device, or it may be separately fabricated into various integrated circuit modules, or it may be fabricated by fabricating a plurality of modules or steps thereof into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. 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, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A method of analyzing collected data, comprising:
acquiring collected data of a target user; wherein the collected data comprises video data and physiological data;
determining a video weight corresponding to the video data and a physiological weight corresponding to the physiological data;
determining a physiological state of the target user based on the video data, the video weights, the physiological data, and the physiological weights, and generating a target intervention recommendation for the target user based on the physiological state.
2. The method of claim 1, wherein the obtaining of the collected data of the target user comprises:
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;
and acquiring preset type physiological data of the target user in a preset time period based on physiological signal acquisition equipment.
3. The method of claim 1, wherein the acquired data comprises acquired data of the target object under a previous intervention recommendation or acquired data of the target object without an intervention recommendation;
correspondingly, 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 acquired 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.
4. The method of claim 3, wherein determining a video weight corresponding to the video data and a physiological weight corresponding to the physiological data corresponding to the acquisition scenario comprises:
if the acquired data is acquired data of the target object under the previous intervention suggestion, determining the intervention type of the previous intervention suggestion;
and determining a video weight corresponding to the video data and a physiological weight corresponding to the physiological data according to the intervention type.
5. The method of claim 4, wherein the intervention types include pharmaceutical and non-pharmaceutical interventions;
correspondingly, 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-drug intervention, presetting that the physiological weight is greater than the video weight;
if the intervention type is drug intervention, the video weight is preset to be larger than the physiological weight.
6. The method of claim 3, wherein determining a video weight corresponding to the video data and a physiological weight corresponding to the physiological data corresponding to the acquisition scenario comprises:
if the acquired data is acquired data of the target object under the last intervention suggestion, determining the corresponding physiological state of the target object under the last 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.
7. The method of claim 1, wherein generating the target intervention recommendation for the target user based on the physiological state comprises:
and comparing the physiological state with a preset intervention state threshold value, and generating a target intervention suggestion of the target user according to a comparison result.
8. An apparatus for analyzing collected data, comprising:
the acquisition module of the collected data, is used for obtaining the collected data of the target user; wherein the collected data comprises video data and physiological data;
the weight determining module is used for determining a video weight corresponding to the video data and a physiological weight corresponding to the physiological data;
a target intervention suggestion generation module to determine a physiological state of the target user based on the video data, the video weights, the physiological data, and the physiological weights, and generate a target intervention suggestion for the target user based on the physiological state.
9. A collected data analysis system to be applied to the collected data analysis method according to any one of claims 1 to 7, comprising: the system comprises 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 weights, the physiological data, and the physiological weights, and generating a target intervention recommendation for the target user based on the physiological state;
the intervention subsystem is used for reminding the target user to execute the target intervention suggestion based on the target intervention suggestion.
10. The system of claim 9, further comprising a digital twinning subsystem;
and the digital twin subsystem is used for comparing the digital twin processing result with the acquired data under the target intervention suggestion to determine the execution result of the target intervention suggestion.
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