CN116434979A - Physiological state cloud monitoring method, monitoring system and storage medium - Google Patents
Physiological state cloud monitoring method, monitoring system and storage medium Download PDFInfo
- Publication number
- CN116434979A CN116434979A CN202310514125.5A CN202310514125A CN116434979A CN 116434979 A CN116434979 A CN 116434979A CN 202310514125 A CN202310514125 A CN 202310514125A CN 116434979 A CN116434979 A CN 116434979A
- Authority
- CN
- China
- Prior art keywords
- user
- information
- physiological
- physiological state
- discussion group
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 230000035790 physiological processes and functions Effects 0.000 title claims abstract description 110
- 238000012544 monitoring process Methods 0.000 title claims abstract description 101
- 238000000034 method Methods 0.000 title claims abstract description 35
- 238000012549 training Methods 0.000 claims abstract description 28
- 230000004962 physiological condition Effects 0.000 claims abstract description 9
- 238000003745 diagnosis Methods 0.000 claims description 11
- 239000008280 blood Substances 0.000 claims description 10
- 210000004369 blood Anatomy 0.000 claims description 10
- 238000013528 artificial neural network Methods 0.000 claims description 8
- 238000012986 modification Methods 0.000 claims description 6
- 230000004048 modification Effects 0.000 claims description 6
- 230000036772 blood pressure Effects 0.000 claims description 5
- 230000036760 body temperature Effects 0.000 claims description 5
- 238000013507 mapping Methods 0.000 claims description 5
- WQZGKKKJIJFFOK-GASJEMHNSA-N Glucose Natural products OC[C@H]1OC(O)[C@H](O)[C@@H](O)[C@@H]1O WQZGKKKJIJFFOK-GASJEMHNSA-N 0.000 claims description 3
- 239000008103 glucose Substances 0.000 claims description 3
- 150000002632 lipids Chemical class 0.000 claims description 3
- 238000007781 pre-processing Methods 0.000 claims description 3
- 238000012552 review Methods 0.000 claims description 3
- 238000012550 audit Methods 0.000 claims description 2
- 230000036541 health Effects 0.000 abstract description 16
- 230000003993 interaction Effects 0.000 abstract description 7
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 8
- 230000006870 function Effects 0.000 description 8
- 238000007726 management method Methods 0.000 description 5
- 238000012806 monitoring device Methods 0.000 description 4
- 230000008901 benefit Effects 0.000 description 3
- 238000011161 development Methods 0.000 description 3
- 238000010586 diagram Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 3
- 238000013473 artificial intelligence Methods 0.000 description 2
- 230000006399 behavior Effects 0.000 description 2
- 230000003750 conditioning effect Effects 0.000 description 2
- 238000012937 correction Methods 0.000 description 2
- 238000001514 detection method Methods 0.000 description 2
- 201000010099 disease Diseases 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 239000011521 glass Substances 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 238000012795 verification Methods 0.000 description 2
- 208000019901 Anxiety disease Diseases 0.000 description 1
- 206010020772 Hypertension Diseases 0.000 description 1
- 241001465754 Metazoa Species 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000036506 anxiety Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
- 238000013501 data transformation Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 206010012601 diabetes mellitus Diseases 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000003862 health status Effects 0.000 description 1
- 201000001421 hyperglycemia Diseases 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 230000007774 longterm Effects 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 239000004984 smart glass Substances 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H80/00—ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- General Health & Medical Sciences (AREA)
- Physics & Mathematics (AREA)
- Biomedical Technology (AREA)
- Theoretical Computer Science (AREA)
- Public Health (AREA)
- Data Mining & Analysis (AREA)
- Epidemiology (AREA)
- Primary Health Care (AREA)
- Life Sciences & Earth Sciences (AREA)
- Computing Systems (AREA)
- Artificial Intelligence (AREA)
- Biophysics (AREA)
- Computational Linguistics (AREA)
- Evolutionary Computation (AREA)
- Molecular Biology (AREA)
- Pathology (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Software Systems (AREA)
- Databases & Information Systems (AREA)
- Measuring And Recording Apparatus For Diagnosis (AREA)
Abstract
The embodiment of the invention provides a physiological state cloud monitoring method, a physiological state cloud monitoring system and a physiological state cloud storage medium, and belongs to the technical field of health monitoring. The method comprises the following steps: collecting physiological information of a user; training in a pre-trained diagnostic model based on the system user portraits and corresponding physiological information of the user to obtain a physiological state monitoring result of the user; creating a discussion group for users with the same physiological state based on the physiological state monitoring result of each user; and pushing the physiological state monitoring result and the affiliated discussion group to the corresponding user side. The invention solves the problems that the prior health management scheme is complex to use and the user cannot perform real-time experience interaction based on the physiological condition of the user.
Description
Technical Field
The invention relates to the technical field of health monitoring, in particular to a physiological state cloud monitoring method, a physiological state cloud monitoring system and a storage medium.
Background
With the rapid development of internet of things and artificial intelligence technology, internet of things has become an important part of the current internet of things, and a large number of wearable devices, health monitoring devices, fitness trackers, intelligent glasses and the like can be used for collecting health related data of users, such as heart rate, blood pressure, blood sugar, blood fat, body temperature and the like.
The internet of things well meets the requirements of people on real-time physical state monitoring, but as the functions of the wearable equipment are increased, the internet of things also drives people to have higher attention to various physiological state parameters. When a user wants to detect certain physiological information, the user needs to find a corresponding function and actively trigger the function to monitor. Even if some schemes have real-time monitoring of certain physiological state parameters, the physiological state parameters are displayed in real time, and corresponding to non-professional users, the users often cannot judge the meaning represented by the physiological information and cannot evaluate the health state of the users based on the physiological information. And the physical state is often the comprehensive expression of multiple items of physiological information, and the physiological information of the existing scheme is displayed one by one, so that the user cannot be informed of the current specific physiological state. Furthermore, even if the user estimates the physiological state of the user through the monitored physiological information, experience about notes, conditioning matters and the like of the current physiological state still needs to be searched for consultation, for example, the user searching for the same state shares experience, and searches for doctors to perform professional consultation, which cannot be realized in the current scheme. Aiming at the problems that the existing health management scheme is complex to use and the user cannot perform real-time experience interaction based on the physiological condition of the user, a new physiological state monitoring scheme needs to be created.
Disclosure of Invention
The invention aims to provide a physiological state cloud monitoring method, a physiological state cloud monitoring system and a storage medium, which are used for solving the problems that the use is complex and a user cannot perform real-time experience interaction based on the physiological condition of the user in the existing health management scheme.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
the first aspect of the invention provides a physiological state cloud monitoring method, which comprises the following steps: collecting physiological information of a user; training in a pre-trained diagnostic model based on the system user portraits and corresponding physiological information of the user to obtain a physiological state monitoring result of the user; creating a discussion group for users with the same physiological state based on the physiological state monitoring result of each user; and pushing the physiological state monitoring result and the affiliated discussion group to the corresponding user side.
Optionally, the physiological information of the user is collected based on the wearable device.
Optionally, the physiological information at least includes: heart rate, blood pressure, blood glucose, blood lipid, body temperature, and entered information.
Optionally, the input information is actively input information by a user; the input information comprises: medical history information, disorder image information, disorder description text information, and past history information.
Optionally, the system user portrait is an initial user portrait or a historical user portrait; the initial user representation is a user representation generated based on new user basic body information; the historical user portraits are user portraits generated based on past physiological state monitoring results of old users.
Optionally, the method further comprises: performing diagnostic model training, comprising: collecting historical medical record information of each department; preprocessing the history medical record information to obtain preprocessed history medical record information containing the mapping relation between the physiological information and the physiological state monitoring result; and taking the preprocessed history medical record information as a training sample, performing model training in a pre-constructed neural network, and taking the obtained training model as a diagnosis model.
Optionally, after obtaining the physiological status monitoring result of the user, the method further includes: pushing the physiological state monitoring result to a preset expert end, and opening a modification function; recovering auditing information of the expert based on the preset expert terminal; wherein, the audit information comprises consent information, objection information and modification information; and correcting the physiological state monitoring result based on the auditing information to obtain a corrected physiological state monitoring result.
Optionally, creating a discussion group for users with the same physiological state based on the physiological state monitoring result of each user includes: classifying the physiological states of the users based on the preset system states, wherein each user can be simultaneously under a plurality of preset system state classification results; establishing a corresponding discussion group aiming at each preset system state type, and recommending a current preset system state related knowledge graph in the discussion group; members of the discussion group include users and doctors; and acquiring the input information of each member in the discussion group in real time, pushing the input information to the discussion group in real time, and opening the review authority for all the members in the current discussion group.
A second aspect of the invention provides a physiological status cloud monitoring system, the system comprising: the acquisition unit is used for acquiring physiological information of a user; the diagnosis unit is used for training in a pre-trained diagnosis model based on the system user portrait and the corresponding physiological information of the user to obtain a physiological state monitoring result of the user; a creation unit for creating a discussion group for users having the same physiological state based on the physiological state monitoring result of each user; and the pushing unit is used for pushing the physiological state monitoring result and the affiliated discussion group to the corresponding user side.
In another aspect, the present invention provides a computer readable storage medium having instructions stored thereon, which when run on a computer cause the computer to perform the physiological state cloud monitoring method described above.
The invention has the beneficial effects that:
1) According to the scheme, the physiological information of the user is collected in real time, then the physiological state monitoring result of the user is obtained based on the user portrait and the physiological information of the user, when the age and the sex of the user are different, even if the same physiological information value exists, the corresponding physiological states are different, and the physiological state monitoring of the user is carried out based on the user portrait, so that the monitoring result obtained by each user is an accurate monitoring result suitable for the user.
2) After the physiological state monitoring result of the user is obtained, a discussion group is automatically created for the user with the same physiological state as the current user based on the user group, so that the user can conveniently share experience or consult in the discussion group based on the real-time physiological state, and the use experience of the user is improved.
3) And finally, the physiological state monitoring result and the discussion group are pushed to the user together, the user directly receives the monitoring result processed based on the physiological information of the user, and each item of information does not need to be analyzed and judged one by one, so that the use convenience is improved. The problems that the existing health management scheme is complex to use and the user cannot conduct real-time experience interaction based on the physiological condition of the user are solved.
Drawings
FIG. 1 is a flow chart of the steps of a physiological status cloud monitoring method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a physiological state cloud monitoring method implementation architecture according to an embodiment of the present invention;
fig. 3 is a system configuration diagram of a physiological status cloud monitoring system according to an embodiment of the present invention.
Detailed Description
Further advantages and effects of the present invention will become readily apparent to those skilled in the art from the disclosure herein, by referring to the accompanying drawings and the preferred embodiments. The invention may be practiced or carried out in other embodiments that depart from the specific details, and the details of the present description may be modified or varied from the spirit and scope of the present invention. It should be understood that the preferred embodiments are presented by way of illustration only and not by way of limitation.
With the rapid development of internet of things and artificial intelligence technology, internet of things has become an important part of the current internet of things, and a large number of wearable devices, health monitoring devices, fitness trackers, intelligent glasses and the like can be used for collecting health related data of users, such as heart rate, blood pressure, blood sugar, blood fat, body temperature and the like.
The internet of things well meets the requirements of people on real-time physical state monitoring, but as the functions of the wearable equipment are increased, the internet of things also drives people to have higher attention to various physiological state parameters. When a user wants to detect certain physiological information, the user needs to find a corresponding function and actively trigger the function to monitor. Even if some schemes have real-time monitoring of certain physiological state parameters, the physiological state parameters are displayed in real time, and corresponding to non-professional users, the users often cannot judge the meaning represented by the physiological information and cannot evaluate the health state of the users based on the physiological information. And the physical state is often the comprehensive expression of multiple items of physiological information, and the physiological information of the existing scheme is displayed one by one, so that the user cannot be informed of the current specific physiological state.
Furthermore, even if the user estimates the physiological state of the user through the monitored physiological information, experience about notes, conditioning matters and the like of the current physiological state still needs to be searched for consultation, for example, the user searching for the same state shares experience, and searches for doctors to perform professional consultation, which cannot be realized in the current scheme.
Aiming at the problems that the use is complex and the user cannot conduct real-time experience interaction based on the physiological condition of the user in the existing health management scheme, the invention provides a physiological state cloud monitoring method. After the physiological state monitoring result of the user is obtained, a discussion group is automatically created for the user with the same physiological state as the current user based on the user group, so that the user can conveniently share experience or consult in the discussion group based on the real-time physiological state, and the use experience of the user is improved. And finally, the physiological state monitoring result and the discussion group are pushed to the user together, the user directly receives the monitoring result processed based on the physiological information of the user, and each item of information does not need to be analyzed and judged one by one, so that the use convenience is improved. The problems that the existing health management scheme is complex to use and the user cannot conduct real-time experience interaction based on the physiological condition of the user are solved.
Fig. 1 is a method flow chart of a physiological status cloud monitoring method provided in an embodiment of the present invention. As shown in fig. 1, an embodiment of the present invention provides a physiological status cloud monitoring method, which includes:
step S10: physiological information of a user is collected.
Specifically, in daily life of a user, on the premise of not affecting normal life, the monitoring of the physiological state of the user can be performed, which is a scheme expected by the user. With the development of wearable equipment technology, the wearable equipment carries out results on the physiological monitoring device and wearing articles, and a user can carry the physiological monitoring device in real time in a wearing mode, so that the real-time acquisition of physiological information is realized. The scheme of the invention fully utilizes the advantages of the wearable device, and the wearable device is used for collecting the physiological information of the user in real time, such as a smart watch, a smart bracelet, smart glasses and the like.
Preferably, the physiological information of the user at least includes: heart rate, blood pressure, blood glucose, blood lipid, body temperature, and entered information.
In the embodiment of the invention, as shown in fig. 2, the scheme of the invention fully utilizes the functions of the current wearable equipment to collect various physiological information, and the more types of physiological information are collected, the higher the accuracy of the subsequent generation of the physiological state monitoring result of the user based on the physiological information is. And these parameters are also direct reflected parameters of the physiological state of the user, the wearable device has high acquisition precision at present, and the subsequent state judgment is carried out based on the high-precision acquisition data, so that the result is credible.
Preferably, the input information is actively input information by a user; the input information comprises: medical history information, disorder image information, disorder description text information, and past history information.
In the embodiment of the invention, when the wearable device collects physiological information of the user, the physiological information is determined by the corresponding sensor matched with a conversion algorithm, and the manner needs to ensure that the human body can produce the information required to be collected by the corresponding sensor. Although this collected information can also monitor the physiological state of the user, the individuals of the user vary widely. For example, there are two users with the same physiological information, and there is a great difference in the health status between them, one with long-term illness and the other with health, and that the same physiological information must be different in the physiological status of the two users. In order to ensure that the scheme of the invention can control the difference and realize the targeted analysis of each individual, the scheme of the invention also can collect active input information of a user, including one or more of medical record information, disease image information, disease description text information and past history information, when the scheme of the invention collects physiological information. These parameters can accurately represent the physical condition of the user, and the accuracy of the physiological state monitoring result generated based on the accurate physical condition must also be higher.
In one possible implementation, the user is not mandatory to enter the information, but is only a preference, so that the customer use satisfaction is ensured, and the user use experience is prevented from being reduced due to complicated data transmission requirements. Of course, the user can also directly select the options of age, health state and the like, so as to ensure that the system can know the basic physical condition of the user, and the accuracy of the subsequent physiological state monitoring result is improved as much as possible.
Step S20: training is performed in a pre-trained diagnostic model based on the system user portraits and corresponding physiological information of the user, and a physiological state monitoring result of the user is obtained.
Specifically, in step S10, the user input information is collected, if the user inputs information such as medical record information, disorder image information, disorder description text information, past history information and the like, these information can be used as portrait information of the user, which is also called user role, as an effective tool for outlining target users, contacting user requirements and design directions, and user portraits are widely used in various fields. We often combine the user's attributes, behaviors, and expected data transformations in the most superficial and life-oriented utterances during the course of actual operation. As a virtual representation of an actual user, the user image forms a user character that is not built outside of the product and market, and the formed user character needs to be representative to represent the primary audience and target group of the product.
In the scheme of the invention, the pointed user portrait can accurately evaluate the relevant parameters of the physical state of the user, such as the height, weight, age, sex, past history and the like of the user, the information reflects the basic physical state of the user, and the subsequent physical state monitoring result of the user combined with the real-time physiological information of the user on the basis is more consistent with the actual situation of the user, and is correspondingly pushed to the monitoring result and professional advice of the user, so that the user portrait is more reliable.
In one possible implementation, the system user representation is an initial user representation or a historical user representation; the initial user representation is a user representation generated based on new user basic body information; the historical user portraits are user portraits generated based on past physiological state monitoring results of old users.
In the embodiment of the invention, if the user is a new user, basic body information of the user is acquired when the user uses the user for the first time, and if the user uploads other input information, an initial portrait of the user is generated based on the basic body information and the input information. In the continuous use process of the user, the user portrait information is corrected in real time along with the increase of the monitoring data quantity of the user, so that the user portrait information at each moment is guaranteed to be the most practical user portrait at the current moment. When the old user uses the user portrait based on the real-time update as the user portrait for the subsequent physiological state monitoring.
Preferably, as described above, the physiological state of the user needs to be comprehensively considered by integrating multiple physiological parameters, and the physiological state indexes represented by the human body parameters are different, so that the weight ratio in the overall physiological state is also different. The index mapping relationship and the weight ratio have to be considered in order to accurately couple out the most accurate physiological state monitoring result based on each parameter. In the cloud platform, the diagnosis model training is carried out based on the neural network, and the neural network is an algorithm mathematical model which imitates the behavior characteristics of the animal neural network and carries out distributed parallel information processing. The network relies on the complexity of the system and achieves the purpose of processing information by adjusting the relationship of the interconnection among a large number of nodes. The method can train based on a large amount of historical physiological detection data, and the relation of various physiological parameters coupled with the final monitoring result is found through training and learning. According to the scheme, the physiological state monitoring result of the user is generated through the neural network, and the monitoring efficiency is greatly improved on the premise of ensuring the accuracy.
Based thereon, the method further comprises performing diagnostic model training, comprising: collecting historical medical record information of each department; preprocessing the history medical record information to obtain preprocessed history medical record information containing the mapping relation between physiological information and physiological state monitoring results; and taking the preprocessed history medical record information as a training sample, performing model training in a pre-constructed neural network, and taking the obtained training model as a diagnosis model.
In the embodiment of the invention, in order to ensure that the training sample data are effective, the scheme of the invention acquires the historical data through the historical medical record information of each department, and then screens out the data containing the mapping relation between the physiological information and the physiological state monitoring result, and the data are used as the training sample of the preset neural network. Preferably, the training sample is split into training data, verification data and correction data, and model training is performed based on the training data to obtain an initial model; and then verifying the initial model based on the verification data, and if the difference exists, giving correction data to correct and train the model to obtain a final model as a diagnosis model. The accuracy of the training model is ensured in this way, so that the accuracy of the finally obtained physiological detection result is ensured.
Step S30: based on the physiological state monitoring results of each user, a discussion group is created for users having the same physiological state.
Specifically, the physiological states of the users are classified based on the preset system states, and each user can be simultaneously under a plurality of preset system state classification results; establishing a corresponding discussion group aiming at each preset system state type, and recommending a current preset system state related knowledge graph in the discussion group; members of the discussion group include users and doctors; and acquiring the input information of each member in the discussion group in real time, pushing the input information to the discussion group in real time, and opening the review authority for all the members in the current discussion group.
In the embodiment of the invention, the existing physiological monitoring schemes are aimed at individual users, the users can only carry out self-evaluation by pushing data, when doubts exist, the users are required to actively search for experience ways or professional ways to carry out consultation, and for users with good experiences, the users have difficulty in sharing experiences in the special ways. Therefore, the scheme of the invention classifies the physiological states of each user based on the preset system states, such as hypertension groups, hyperglycemia groups, diabetes groups and the like, constructs discussion groups aiming at the different groups, and automatically distributes the user discussion groups based on the current physiological states of the users. The method has the advantages that a platform for professional consultation and experience sharing is provided for users, the users can perform professional consultation and experience sharing through the discussion group at any time, and doctors are invited to join the discussion group, so that professional consultation results in the discussion group are more reliable, the users can realize physiological state evaluation without going out, and the use experience of the users is improved.
Step S40: and pushing the physiological state monitoring result and the affiliated discussion group to the corresponding user side.
In the embodiment of the invention, the information finally pushed to the user comprises the physiological state monitoring result after processing each item of data, so that the user does not need to distinguish and analyze the data, the using and operating steps of the user are greatly reduced, and the using convenience of the system is improved. After receiving the discussion group, the user can freely speak in the discussion group, upload the tested file or the professional consultation problem, and other members in the discussion group can synchronously acquire information, so that the real-time performance of interaction is ensured, and the use experience of the user is improved.
In one possible implementation, the expert may be requested to connect to the line and the consultation is performed by multiple persons on the line. Treatment advice and attention is given. Thus not only improving the efficiency, but also relieving the anxiety of the patient. And can also share resources in remote areas and places with poor medical conditions.
Fig. 3 is a system configuration diagram of a physiological status cloud monitoring system according to an embodiment of the present invention. As shown in fig. 3, an embodiment of the present invention provides a physiological status cloud monitoring system, the system including: the acquisition unit is used for acquiring the physiological information of each user; the diagnosis unit is used for training in a pre-trained diagnosis model based on the system user portraits and corresponding physiological information of each user to obtain physiological state monitoring results of each user; a creation unit for creating a discussion group for users having the same physiological state based on the physiological state monitoring result of each user; and the pushing unit is used for pushing the physiological state monitoring result and the discussion group to the corresponding user side.
The embodiment of the invention also provides a computer readable storage medium, wherein the computer readable storage medium stores instructions, and when the computer readable storage medium runs on a computer, the computer is caused to execute the physiological state cloud monitoring method.
Those skilled in the art will appreciate that all or part of the steps in a method for implementing the above embodiments may be implemented by a program stored in a storage medium, where the program includes several instructions for causing a single-chip microcomputer, chip or processor (processor) to perform all or part of the steps in a method according to the embodiments of the invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The alternative embodiments of the present invention have been described in detail above with reference to the accompanying drawings, but the embodiments of the present invention are not limited to the specific details of the above embodiments, and various simple modifications may be made to the technical solutions of the embodiments of the present invention within the scope of the technical concept of the embodiments of the present invention, and all the simple modifications belong to the protection scope of the embodiments of the present invention. In addition, the specific features described in the above embodiments may be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the various possible combinations of embodiments of the invention are not described in detail.
In addition, any combination of the various embodiments of the present invention may be made, so long as it does not deviate from the idea of the embodiments of the present invention, and it should also be regarded as what is disclosed in the embodiments of the present invention.
Claims (10)
1. A method of physiological state cloud monitoring, the method comprising:
collecting physiological information of a user;
training in a pre-trained diagnostic model based on the system user portraits and corresponding physiological information of the user to obtain a physiological state monitoring result of the user;
creating a discussion group for users with the same physiological state based on the physiological state monitoring result of each user;
and pushing the physiological state monitoring result and the affiliated discussion group to the corresponding user side.
2. The physiological state cloud monitoring method of claim 1, wherein the physiological information of the user is collected based on a wearable device.
3. The physiological state cloud monitoring method of claim 1, wherein the physiological information comprises at least:
heart rate, blood pressure, blood glucose, blood lipid, body temperature, and entered information.
4. A physiological state cloud monitoring method according to claim 3, wherein the entered information is information actively entered by a user;
the input information comprises: medical history information, disorder image information, disorder description text information, and past history information.
5. The physiological state cloud monitoring method of claim 1, wherein said system user profile is an initial user profile or a historical user profile;
the initial user representation is a user representation generated based on new user basic body information;
the historical user portraits are user portraits generated based on past physiological state monitoring results of old users.
6. The physiological state cloud monitoring method of claim 1, wherein the method further comprises: performing diagnostic model training, comprising:
collecting historical medical record information of each department;
preprocessing the history medical record information to obtain preprocessed history medical record information containing the mapping relation between the physiological information and the physiological state monitoring result;
and taking the preprocessed history medical record information as a training sample, performing model training in a pre-constructed neural network, and taking the obtained training model as a diagnosis model.
7. The physiological condition cloud monitoring method of claim 1, wherein after obtaining the physiological condition monitoring result of the user, the method further comprises:
pushing the physiological state monitoring result to a preset expert end, and opening a modification function;
recovering auditing information of the expert based on the preset expert terminal; wherein, the audit information comprises consent information, objection information and modification information;
and correcting the physiological state monitoring result based on the auditing information to obtain a corrected physiological state monitoring result.
8. The physiological state cloud monitoring method of claim 1, wherein creating a discussion group for users having the same physiological state based on physiological state monitoring results of each user comprises:
classifying the physiological states of the users based on the preset system states, wherein each user can be simultaneously under a plurality of preset system state classification results;
establishing a corresponding discussion group aiming at each preset system state type, and recommending a current preset system state related knowledge graph in the discussion group; members of the discussion group include users and doctors;
and acquiring the input information of each member in the discussion group in real time, pushing the input information to the discussion group in real time, and opening the review authority for all the members in the current discussion group.
9. A physiological state cloud monitoring system, the system comprising:
the acquisition unit is used for acquiring physiological information of a user;
the diagnosis unit is used for training in a pre-trained diagnosis model based on the system user portrait and the corresponding physiological information of the user to obtain a physiological state monitoring result of the user;
a creation unit for creating a discussion group for users having the same physiological state based on the physiological state monitoring result of each user;
and the pushing unit is used for pushing the physiological state monitoring result and the affiliated discussion group to the corresponding user side.
10. A computer readable storage medium having instructions stored thereon, which when run on a computer cause the computer to perform the physiological condition cloud monitoring method of any of claims 1-8.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310514125.5A CN116434979A (en) | 2023-05-08 | 2023-05-08 | Physiological state cloud monitoring method, monitoring system and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310514125.5A CN116434979A (en) | 2023-05-08 | 2023-05-08 | Physiological state cloud monitoring method, monitoring system and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116434979A true CN116434979A (en) | 2023-07-14 |
Family
ID=87085627
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310514125.5A Pending CN116434979A (en) | 2023-05-08 | 2023-05-08 | Physiological state cloud monitoring method, monitoring system and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116434979A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116913519A (en) * | 2023-07-24 | 2023-10-20 | 东莞莱姆森科技建材有限公司 | Health monitoring method, device, equipment and storage medium based on intelligent mirror |
-
2023
- 2023-05-08 CN CN202310514125.5A patent/CN116434979A/en active Pending
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116913519A (en) * | 2023-07-24 | 2023-10-20 | 东莞莱姆森科技建材有限公司 | Health monitoring method, device, equipment and storage medium based on intelligent mirror |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP6881687B2 (en) | Methods and systems for modeling the user's mental / emotional state | |
| CN104287706B (en) | A kind of health status real time monitor and diagnosis and treatment commending system | |
| RU2757048C1 (en) | Method and system for assessing the health of the human body based on the large-volume sleep data | |
| KR20170061222A (en) | The method for prediction health data value through generation of health data pattern and the apparatus thereof | |
| CN109119130A (en) | A kind of big data based on cloud computing is health management system arranged and method | |
| CN108778097A (en) | Device and method for assessing heart failure | |
| US20240074698A1 (en) | Method, Computing Device And Wearable Device For Sleep Stage Detection | |
| CN108052973B (en) | Map symbol user interest analysis method based on multiple items of eye movement data | |
| CN108135548A (en) | For monitoring the method and system of pressure state | |
| JP2018524137A (en) | Method and system for assessing psychological state | |
| KR20090024808A (en) | Assessing dementia and dementia-type disorders | |
| WO2021147292A1 (en) | Product design scheme decision-making method combining electroencephalogram and eye movement with user similarity | |
| CN110584601A (en) | Method for monitoring and evaluating cognitive function of old people | |
| CN108652587A (en) | A kind of cognition dysfunction provisional monitor device | |
| CN116434979A (en) | Physiological state cloud monitoring method, monitoring system and storage medium | |
| CN111008269A (en) | Data processing method and device, storage medium and electronic terminal | |
| CN114512239A (en) | Cerebral apoplexy risk prediction method and system based on transfer learning | |
| CN113974589B (en) | Multi-modal behavior paradigm evaluation optimization system and cognitive ability evaluation method | |
| US20200321082A1 (en) | Confidence evaluation to measure trust in behavioral health survey results | |
| CN114202772B (en) | Reference information generation system and method based on artificial intelligence and intelligent medical treatment | |
| CN113724878B (en) | Medical risk information pushing method and device based on machine learning | |
| CN115497621A (en) | Old person cognitive status evaluation system | |
| CN115547491A (en) | Health management method and device, electronic equipment and storage medium | |
| Chauhan | A mobile platform for non-invasive diabetes screening | |
| Liu et al. | Intelligent assessment and prediction system for somatic fitness and healthcare using machine learning |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |