CN116798631A - Digital healthy living platform based on big data - Google Patents
Digital healthy living platform based on big data Download PDFInfo
- Publication number
- CN116798631A CN116798631A CN202310856250.4A CN202310856250A CN116798631A CN 116798631 A CN116798631 A CN 116798631A CN 202310856250 A CN202310856250 A CN 202310856250A CN 116798631 A CN116798631 A CN 116798631A
- Authority
- CN
- China
- Prior art keywords
- health
- data
- user
- platform
- medical
- 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
- 230000036541 health Effects 0.000 claims abstract description 265
- 238000004458 analytical method Methods 0.000 claims abstract description 32
- 238000012545 processing Methods 0.000 claims abstract description 31
- 238000000034 method Methods 0.000 claims abstract description 18
- 238000007726 management method Methods 0.000 claims description 98
- 238000012544 monitoring process Methods 0.000 claims description 20
- 238000004422 calculation algorithm Methods 0.000 claims description 17
- 230000033001 locomotion Effects 0.000 claims description 17
- 238000013473 artificial intelligence Methods 0.000 claims description 10
- 230000002159 abnormal effect Effects 0.000 claims description 9
- 239000008280 blood Substances 0.000 claims description 8
- 210000004369 blood Anatomy 0.000 claims description 8
- 238000013480 data collection Methods 0.000 claims description 8
- 230000003993 interaction Effects 0.000 claims description 8
- 230000036772 blood pressure Effects 0.000 claims description 7
- 235000005911 diet Nutrition 0.000 claims description 7
- 230000037213 diet Effects 0.000 claims description 7
- 238000013058 risk prediction model Methods 0.000 claims description 7
- 238000004140 cleaning Methods 0.000 claims description 6
- 201000010099 disease Diseases 0.000 claims description 6
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims description 6
- 239000003814 drug Substances 0.000 claims description 6
- 229940126585 therapeutic drug Drugs 0.000 claims description 6
- 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 5
- 238000003745 diagnosis Methods 0.000 claims description 5
- 229940079593 drug Drugs 0.000 claims description 5
- 239000008103 glucose Substances 0.000 claims description 5
- 238000007418 data mining Methods 0.000 claims description 3
- 238000012377 drug delivery Methods 0.000 claims description 3
- 238000012806 monitoring device Methods 0.000 claims description 3
- 238000007781 pre-processing Methods 0.000 claims description 3
- 239000000955 prescription drug Substances 0.000 claims description 3
- 230000003860 sleep quality Effects 0.000 claims description 3
- 238000007619 statistical method Methods 0.000 claims description 3
- 238000010586 diagram Methods 0.000 description 4
- 230000004044 response Effects 0.000 description 4
- 230000000694 effects Effects 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 230000008569 process Effects 0.000 description 3
- 230000008859 change Effects 0.000 description 2
- 208000012260 Accidental injury Diseases 0.000 description 1
- 208000024172 Cardiovascular disease Diseases 0.000 description 1
- 206010020772 Hypertension Diseases 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 208000026106 cerebrovascular disease Diseases 0.000 description 1
- 238000003066 decision tree Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 206010012601 diabetes mellitus Diseases 0.000 description 1
- 230000006806 disease prevention Effects 0.000 description 1
- 230000035622 drinking Effects 0.000 description 1
- 235000006694 eating habits Nutrition 0.000 description 1
- 230000002526 effect on cardiovascular system Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000011156 evaluation Methods 0.000 description 1
- 230000005713 exacerbation Effects 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 208000015181 infectious disease Diseases 0.000 description 1
- 208000014674 injury Diseases 0.000 description 1
- 238000010801 machine learning Methods 0.000 description 1
- 229940126532 prescription medicine Drugs 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 238000007637 random forest analysis Methods 0.000 description 1
- 230000000391 smoking effect Effects 0.000 description 1
- 238000012706 support-vector machine Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
Landscapes
- Measuring And Recording Apparatus For Diagnosis (AREA)
- Medical Treatment And Welfare Office Work (AREA)
Abstract
The application discloses a digital health living platform based on big data and a control method thereof, wherein the digital health living platform comprises a health management platform and a medical institution signed with the health management platform, and the health management platform comprises: equipment end, intelligent analysis system and intelligent early warning system, intelligent analysis system includes: the system comprises a database, a data receiving end and a data processing end, wherein the data receiving end is used for acquiring the acquired user health data; the data processing end is used for analyzing the user health data and automatically generating a user health file; the database is used for storing the generated user health files and realizing information intercommunication with the medical institutions; the intelligent early warning system is used for analyzing the physical condition and health trend of the user according to the health file and the medical records of the user, and can timely inform the user or the medical institution subscribed by the health management platform through the emergency reminding service set by the intelligent early warning system once the emergency or health risk of the user is detected.
Description
Technical Field
The application belongs to the technical field of digital health management cloud platforms, and particularly relates to a digital health life platform based on big data and a control method thereof.
Background
Remote digital health management is an important means for popularizing health management, and by means of remote digital management and providing health digital services, human resource investment of the health services is effectively reduced, standards and efficiency of the health management are improved, and the remote digital health management is a necessary trend of development of health industries at home and abroad.
The Chinese patent CN104680034.B discloses a digital health management cloud platform and a data processing method thereof, comprising the following steps: the system comprises a data receiving end, a data transmitting end, a data processing end, a doctor or health manager management system and a database; the data processing end is used for carrying out matching processing on the monitoring data and the characteristics of the existing samples in the database; when the monitoring data is matched with the corresponding sample from the database, a processing scheme of the corresponding sample is called from the database and is sent to a data sending end; when the monitoring data cannot be matched with the corresponding sample from the database, the closest sample and the monitoring data which are called from the database are sent to a doctor or health manager management system; the closest sample matching in the database is increased, samples with high similarity are directly processed by the background, the workload of a background doctor or a health manager is greatly reduced, the time required for processing comments is shortened, and the working efficiency of the background is greatly improved.
While the above-described approach may enable remote digital health management, at the platform users face for example: sudden diseases or rapid exacerbations of illness need timely treatment; accidental injury or infection, requiring emergency assistance; the corresponding response mode cannot be selected intelligently in combination with the current situation, and the corresponding response mode can be processed in time by manual intervention, so that the workload of a background doctor or a health manager is increased, and meanwhile, some situations can be processed according to misinformation, so that a platform user cannot be timely and emergently helped.
Therefore, the digital health management cloud platform needs to be further optimized, and more reliable, intelligent and convenient health monitoring and management services are provided for platform users, so that the platform users can be timely helped, and better health management effects are achieved.
Disclosure of Invention
The application provides a digital health life platform based on big data and a control method thereof, which can intelligently select corresponding response modes according to health files and medical records of users when detecting that the users encounter emergency, and provide emergency rescue services so as to provide more reliable, intelligent and convenient health monitoring and management services for platform users, ensure that the platform users can be timely rescued and achieve better health management effects.
In order to achieve the above object, the present application provides the following technical solutions: the utility model provides a digital healthy life platform based on big data, includes health management platform and the medical institution who signs up with health management platform for according to the health archives of record in the platform and the medical records of storing in above-mentioned medical institution, the present physical condition of analysis user, health management platform include:
the equipment end is used for collecting various physiological index data of the platform user, and motion data and sleep data of the platform user in real time and uploading the physiological index data, the motion data and the sleep data to the intelligent analysis system.
The intelligent analysis system, the intelligent analysis system include: the system comprises a database, a data receiving end and a data processing end, wherein the data receiving end is used for acquiring the acquired user health data of each platform; the data processing end is used for analyzing the health data of the platform user through big data processing and an artificial intelligence algorithm and automatically generating a user health file; the database is used for storing the generated user health files and realizing information intercommunication with the medical institutions, wherein the user health files at least have the information of various physiological index data, platform user motion data and sleep data, disease history, diagnosis and treatment records and medication records of the platform user acquired by the equipment end.
And the intelligent early warning system is used for analyzing the physical condition and health trend of the user according to the health record and the medical record of the platform user, and timely notifying the platform user or the medical institution subscribed by the health management platform through the emergency reminding service set by the intelligent early warning system once the emergency or health risk of the platform user is detected.
Preferably, the intelligent early warning system includes:
and the data interaction end is used for carrying out data interaction with the intelligent analysis system through wireless signals.
The data acquisition end is used for generating a data collection instruction, and calling the user health file generated in the database and the medical records in the medical institution contracted with the health management platform according to the generated data collection instruction.
And the data monitoring end is used for analyzing and monitoring the collected user health files and medical records through big data processing and an artificial intelligence algorithm and predicting the health risk possibly occurring in the future.
The early warning notification terminal is used for timely notifying a user or a medical institution subscribed by the health management platform when the data monitoring terminal monitors the possible health risks, and providing corresponding suggestions and treatment schemes.
Preferably, the intelligent early warning system further comprises:
the remote medical service is used for providing on-line inquiry, expert consultation and prescription drug delivery service for the user so as to facilitate the medical treatment and treatment of the user.
The health management terminal is used for autonomously generating a health management scheme according to personal information, health files and medical records of the platform user, wherein the health management scheme at least has management information for diet guidance, exercise and fitness and therapeutic drugs.
Preferably, the device end can be an intelligent exercise bracelet integrated with the physiological index monitoring device, and can also be a wearable blood pressure and blood glucose monitor.
In order to achieve the above object, the present application provides another technical solution: the digital healthy living platform control method based on big data comprises the following steps:
the platform user wears the equipment end to collect various physiological index data, motion data and sleep data in real time, and synchronously uploads the physiological index data, the motion data and the sleep data into the intelligent analysis system.
And acquiring health data of the user through a data receiving end in the intelligent analysis system, analyzing the health data through a data processing end according to the big data and an artificial intelligent algorithm, and automatically generating a user health file.
And storing the generated user health file into a database, and realizing information intercommunication with a medical institution signed by a health management platform.
And analyzing physical conditions and health trends of the user according to the health files and the medical records of the user through the intelligent early warning system, and predicting possible health risks in the future.
When the intelligent early warning system monitors that the user has health risks, the early warning informing end informs the user or a medical institution subscribed by the health management platform in time, and the remote medical service combines the user health files and the historical medical records to propose corresponding suggestions and treatment schemes.
Preferably, the method further comprises:
and automatically generating a health management scheme by the health management terminal according to the personal information, the health file and the medical records of the user, wherein the health management scheme comprises diet guidance, exercise and fitness and management information of therapeutic drugs.
Preferably, the analyzing the health data by the data processing end according to the big data and the artificial intelligence algorithm specifically includes:
and cleaning the collected original data to remove repeated data, abnormal data and incomplete data.
Extracting important characteristic values from the data, and selecting data indexes to be analyzed according to basic information, physical conditions and health targets preset by a user, wherein the analyzed data indexes comprise: blood pressure, blood glucose, number of steps of exercise, and sleep quality.
And analyzing the selected data indexes, determining the health state, trend and preference of the user through a data mining and statistical method, and automatically generating the health file of the user according to the analysis result.
Preferably, the analyzing the physical condition and health trend of the user and predicting the health risk possibly occurring in the future by the intelligent early warning system according to the health record and the medical record of the user specifically comprises:
and acquiring the health record and the medical record of the user, wherein the health record and the medical record comprise personal information, physiological indexes and physical examination reports of the user.
And preprocessing and cleaning the obtained health files and medical record data, removing abnormal data and missing data, and converting the abnormal data and the missing data into a universal format.
And selecting the characteristics of the obtained data according to preset characteristics possibly causing health risks of the user, wherein the characteristics possibly causing health risks of the user are at least daily physiological indexes and life style factors of the user.
And establishing a health risk prediction model according to the selected health risk characteristics, and predicting the health risk through the model.
The application provides a building engineering quality supervision and management method based on big data, which can acquire various physiological index data, movement data and sleep data of a platform user in real time through a device end in a health management platform, process and analyze the data through an intelligent analysis system to generate a health file of the user, realize comprehensive monitoring and tracking, and acquire disease history, diagnosis and treatment records, medication records and the like of the user through medical institution records integrated in the health management platform, so that the physical condition and health trend of the user are more comprehensively analyzed.
On the other hand, the health data of the user can be analyzed through the intelligent analysis system through big data processing and an artificial intelligent algorithm, so that the change of the physical condition and the health trend of the user can be accurately found, more accurate early warning and management advice can be provided, the health management and health life of the user can be promoted through the health management platform which is in information intercommunication with the medical institution, and further, when the emergency or health risk of the user is monitored through the intelligent early warning system, warning information can be sent to the user or the medical institution signed by the health management platform, so that the purposes of timely early warning and processing can be achieved.
In summary, the application can integrate a plurality of medical institutions and health management platform resources, optimize the configuration of medical service resources, improve the efficiency and quality of medical service, and provide comprehensive and one-stop health management service for users.
Drawings
FIG. 1 is a schematic diagram of a digital healthy living platform structure based on big data;
FIG. 2 is a schematic diagram of a health management platform;
FIG. 3 is a schematic diagram of the structure of an intelligent analysis system;
FIG. 4 is a schematic diagram of a user health record;
fig. 5 is a flowchart of a digital healthy living platform control method.
Detailed Description
In order to enable those skilled in the art to better understand the present application, the following description will make clear and complete descriptions of the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application.
1-2, a digital health life platform based on big data, including health management platform and with health management platform contract medical institution for according to the health record of record in the platform and the medical record of storing in above-mentioned medical institution, the present physical condition of analysis user, health management platform include:
the equipment end is used for collecting various physiological index data of the platform user, and motion data and sleep data of the platform user in real time and uploading the physiological index data, the motion data and the sleep data to the intelligent analysis system.
Referring to fig. 4, the intelligent analysis system includes: the system comprises a database, a data receiving end and a data processing end, wherein the data receiving end is used for acquiring the acquired user health data of each platform; the data processing end is used for analyzing the health data of the platform user through big data processing and an artificial intelligence algorithm and automatically generating a user health file; the database is used for storing the generated user health files and realizing information intercommunication with the medical institutions, wherein the user health files at least have the information of various physiological index data, platform user motion data and sleep data, disease history, diagnosis and treatment records and medication records of the platform user acquired by the equipment end.
And the intelligent early warning system is used for analyzing the physical condition and health trend of the user according to the health record and the medical record of the platform user, and timely notifying the platform user or the medical institution subscribed by the health management platform through the emergency reminding service set by the intelligent early warning system once the emergency or health risk of the platform user is detected.
On one hand, the embodiment can collect various physiological index data, motion data and sleep data of the platform user in real time through the equipment end in the health management platform, process and analyze the data through the intelligent analysis system, generate health files of the user and realize comprehensive monitoring and tracking. Meanwhile, records of medical institutions are integrated in the health management platform so as to acquire disease history, diagnosis and treatment records, medication records and the like of users, and therefore physical conditions and health trends of the users are analyzed more comprehensively.
On the other hand, the health data of the user can be analyzed through the intelligent analysis system by big data processing and an artificial intelligent algorithm, so that the change of the physical condition and the health trend of the user can be accurately found, and more accurate early warning and management advice can be provided.
Compared with the prior art, the health management platform can improve the medical service quality through the health management platform which is in information intercommunication with the medical institution, promote the health management and the health life of the user, and send out alarm information to the user or the medical institution signed by the health management platform when the emergency or the health risk of the user is monitored through the intelligent early warning system arranged in the health management platform, so that the purposes of early warning and processing in time are achieved.
Referring to fig. 3, in one embodiment, the intelligent pre-warning system includes:
and the data interaction end is used for carrying out data interaction with the intelligent analysis system through wireless signals.
The data acquisition end is used for generating a data collection instruction, and calling the user health file generated in the database and the medical records in the medical institution contracted with the health management platform according to the generated data collection instruction.
And the data monitoring end is used for analyzing and monitoring the collected user health files and medical records through big data processing and an artificial intelligence algorithm and predicting the health risk possibly occurring in the future.
The early warning notification terminal is used for timely notifying a user or a medical institution subscribed by the health management platform when the data monitoring terminal monitors the possible health risks, and providing corresponding suggestions and treatment schemes.
In this embodiment, the data interaction end that can perform data interaction with the intelligent analysis system through using the wireless signal can make the data transmission more efficient, so as to more rapidly complete the functions of early warning and reminding, and a data collection instruction is generated through the data collection end, so as to retrieve the user health record and the medical record in the database, so as to comprehensively monitor the body and the health condition of the user, thereby reducing the redundancy and the waste of data, and improving the accuracy and the comprehensiveness of the data.
Meanwhile, through the data monitoring end for analyzing and detecting the collected information according to big data processing and an artificial intelligence algorithm, the potential health risk is predicted, the accuracy and precision of prediction are improved, and through the early warning informing end, when the health risk of a user is monitored by the data monitoring end, the user or a medical institution subscribed by a health management platform is timely informed, corresponding suggestions and treatment schemes are provided, the purposes of high-efficiency early warning and management are achieved, and further, the corresponding response mode is intelligently selected according to the current situation, so that the user is helped to process the health risk in time.
In one embodiment, the intelligent early warning system further comprises:
the remote medical service is used for providing on-line inquiry, expert consultation and prescription drug delivery service for the user so as to facilitate the medical treatment and treatment of the user.
The health management terminal is used for autonomously generating a health management scheme according to personal information, health files and medical records of the platform user, wherein the health management scheme at least has management information for diet guidance, exercise and fitness and therapeutic drugs.
In the embodiment, on-line inquiry, expert consultation and prescription medicine distribution services can be provided for the user through the remote medical service, so that the user can conveniently see the doctor and treat, meanwhile, the time and the cost for the user to go to a hospital can be reduced, the efficiency and the convenience of the medical service are improved, a health management scheme is independently generated through the health management end according to personal information, health files and medical records of the user, management information in aspects of diet guidance, exercise, body building, medicine treatment and the like is provided for the user, and the health consciousness and the health management level of the user are improved.
In one embodiment, the device end may be an intelligent exercise bracelet integrated with a physiological index monitoring device, or may be a wearable blood pressure and blood glucose monitor.
Referring to fig. 5, a digital healthy living platform control method based on big data includes:
the platform user wears the equipment end to collect various physiological index data, motion data and sleep data in real time, and synchronously uploads the physiological index data, the motion data and the sleep data into the intelligent analysis system.
And acquiring health data of the user through a data receiving end in the intelligent analysis system, analyzing the health data through a data processing end according to the big data and an artificial intelligent algorithm, and automatically generating a user health file.
And storing the generated user health file into a database, and realizing information intercommunication with a medical institution signed by a health management platform.
And analyzing physical conditions and health trends of the user according to the health files and the medical records of the user through the intelligent early warning system, and predicting possible health risks in the future.
When the intelligent early warning system monitors that the user has health risks, the early warning informing end informs the user or a medical institution subscribed by the health management platform in time, and the remote medical service combines the user health files and the historical medical records to propose corresponding suggestions and treatment schemes.
And automatically generating a health management scheme by the health management terminal according to the personal information, the health file and the medical records of the user, wherein the health management scheme comprises diet guidance, exercise and fitness and management information of therapeutic drugs.
According to the control method, various pieces of physiological index data, exercise data and sleep data can be collected in real time through a platform user wearing equipment end, real-time monitoring and recording of the body and health conditions of a user are achieved, the health data are analyzed through a data processing end in an intelligent analysis system according to big data and an artificial intelligent algorithm, a user health file is automatically generated, personalized health files and health management schemes are provided for the user, information intercommunication is achieved through a medical institution signing with a health management platform, multiparty data sharing and collaboration are achieved, efficiency and quality of medical service are improved, then the health situation and health trend of the user are analyzed through an intelligent early warning system according to the health files and the medical records of the user, health risks which possibly occur in the future are predicted, the occurrence of the health risks can be timely prevented, when the health risks of the user are detected by the intelligent early warning system, the user or the medical institution signing of the health management platform is timely notified through the early warning notification end, corresponding suggestions and treatment schemes are provided through the combination of the health files and the history medical records of the remote medical service, meanwhile, the efficiency and accuracy of the medical service can be improved, and the user health management scheme can be provided according to personal information, the health management and health management information of the user and the health management scheme is provided for the user, and the user enjoyment of the health management is directed.
In one embodiment, the analyzing the health data by the data processing end according to the big data and the artificial intelligence algorithm specifically includes:
and cleaning the collected original data to remove repeated data, abnormal data and incomplete data.
Extracting important characteristic values from the data, and selecting data indexes to be analyzed according to basic information, physical conditions and health targets preset by a user, wherein the analyzed data indexes comprise: blood pressure, blood glucose, number of steps of exercise, and sleep quality.
And analyzing the selected data indexes, determining the health state, trend and preference of the user through a data mining and statistical method, and automatically generating the health file of the user according to the analysis result.
According to the health record and the medical record of the user, the intelligent early warning system analyzes the physical condition and the health trend of the user and predicts the possible health risk in the future, wherein the method specifically comprises the following steps:
and acquiring the health record and the medical record of the user, wherein the health record and the medical record comprise personal information, physiological indexes and physical examination reports of the user.
And preprocessing and cleaning the obtained health files and medical record data, removing abnormal data and missing data, and converting the abnormal data and the missing data into a universal format.
And selecting the characteristics of the obtained data according to preset characteristics possibly causing health risks of the user, wherein the characteristics possibly causing health risks of the user are at least daily physiological indexes and life style factors of the user. The daily physiological indexes of the user comprise: blood pressure, blood sugar, heart rate, blood fat, etc., the user's daily life style factors include: daily eating habits, exercise data, sleep conditions, and the number of smoking and drinking.
And establishing a health risk prediction model according to the selected health risk characteristics, and predicting the health risk through the model so as to predict the possible future health risk conditions of the user, such as hypertension, diabetes, cardiovascular and cerebrovascular diseases and the like. Meanwhile, the system can also provide corresponding management advice according to the prediction result to help the user to carry out health management and disease prevention.
The health risk prediction model described in the above method may use a machine learning algorithm to build a health risk prediction model, such as decision trees, random forests, support vector machines, and the like. And through combining the prediction model with the user data collected in real time, the physical condition and the health trend of the user can be continuously monitored and analyzed through the intelligent early warning system, the possible health risk can be predicted in time, and personalized and accurate health management service is provided for the user.
Meanwhile, after the intelligent early warning system predicts the health risk, the health risk prediction model can be evaluated. The evaluation of the health risk prediction model can be used for measuring performance indexes such as accuracy, recall rate and F1 value of the model through cross verification, and also can be used for measuring performance indexes such as accuracy, recall rate and F1 value of the model through a leave-out method so as to ensure the reliability of a prediction result.
Certain terms are used throughout the description and claims to refer to particular components. Those of skill in the art will appreciate that a hardware manufacturer may refer to the same component by different names. The description and claims do not take the form of an element differentiated by name, but rather by functionality. As used throughout the specification and claims, the word "comprise" is an open-ended term, and thus should be interpreted to mean "include, but not limited to. By "substantially" is meant that within an acceptable error range, a person skilled in the art is able to solve the technical problem within a certain error range, substantially achieving the technical effect.
It should be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a product or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such product or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a commodity or system comprising such elements.
While the foregoing description illustrates and describes the preferred embodiments of the present application, it is to be understood that the application is not limited to the forms disclosed herein, but is not to be construed as limited to other embodiments, and is capable of numerous other combinations, modifications and environments and is capable of changes or modifications within the scope of the inventive concept as expressed herein, either as a result of the foregoing teachings or as a result of the knowledge or technology of the relevant art. And that modifications and variations which do not depart from the spirit and scope of the application are intended to be within the scope of the appended claims.
Claims (8)
1. The utility model provides a digital healthy life platform based on big data, its characterized in that includes health management platform and the medical institution who contracts with health management platform for according to the health archives of record in the platform and the medical record of storing in above-mentioned medical institution, the present physical condition of analysis user, health management platform include: the equipment end is used for collecting various physiological index data of the platform user, and motion data and sleep data of the platform user in real time and uploading the physiological index data, the motion data and the sleep data to the intelligent analysis system; the intelligent analysis system, the intelligent analysis system include: the system comprises a database, a data receiving end and a data processing end, wherein the data receiving end is used for acquiring the acquired user health data of each platform; the data processing end is used for analyzing the health data of the platform user through big data processing and an artificial intelligence algorithm and automatically generating a user health file; the database is used for storing the generated user health files and realizing information intercommunication with the medical institutions, wherein the user health files at least have the information of various physiological index data, platform user motion data and sleep data, disease history, diagnosis and treatment records and medication records of the platform user acquired by the equipment end; and the intelligent early warning system is used for analyzing the physical condition and health trend of the user according to the health record and the medical record of the platform user, and timely notifying the platform user or the medical institution subscribed by the health management platform through the emergency reminding service set by the intelligent early warning system once the emergency or health risk of the platform user is detected.
2. The digital health life platform based on big data of claim 1, wherein the intelligent early warning system comprises: the data interaction end is used for carrying out data interaction with the intelligent analysis system through wireless signals; the data acquisition end is used for generating a data collection instruction, and calling the user health file generated in the database and the medical records in the medical institution contracted with the health management platform according to the generated data collection instruction; the data monitoring end is used for analyzing and monitoring the collected user health files and medical records through big data processing and an artificial intelligence algorithm and predicting the health risk possibly occurring in the future; the early warning notification terminal is used for timely notifying a user or a medical institution subscribed by the health management platform when the data monitoring terminal monitors the possible health risks, and providing corresponding suggestions and treatment schemes.
3. The digital health life platform based on big data of claim 2, wherein the intelligent pre-warning system further comprises: the remote medical service is used for providing on-line inquiry, expert consultation and prescription drug delivery service for the user so as to facilitate the medical treatment and treatment of the user; the health management terminal is used for autonomously generating a health management scheme according to personal information, health files and medical records of the platform user, wherein the health management scheme at least has management information for diet guidance, exercise and fitness and therapeutic drugs.
4. The digital health life platform based on big data according to claim 1, wherein the device end can be an intelligent exercise bracelet integrated with a physiological index monitoring device, or can be a wearable blood pressure and blood sugar monitor.
5. The digital healthy living platform control method based on big data is characterized by comprising the following steps: the platform user wears the equipment end to collect various physiological index data, movement data and sleep data in real time, and synchronously upload the physiological index data, the movement data and the sleep data into the intelligent analysis system; acquiring health data of a user through a data receiving end in the intelligent analysis system, analyzing the health data through a data processing end according to big data and an artificial intelligent algorithm, and automatically generating a user health file; storing the generated user health file into a database, and realizing information intercommunication with a medical institution signed by a health management platform; when the intelligent early warning system monitors that the user has health risks, the early warning informing end informs the user or a medical institution subscribed by the health management platform in time, and the remote medical service combines the user health files and the historical medical records to propose corresponding suggestions and treatment schemes.
6. The digital healthy living platform control method based on big data according to claim 5, further comprising: and automatically generating a health management scheme by the health management terminal according to the personal information, the health file and the medical records of the user, wherein the health management scheme comprises diet guidance, exercise and fitness and management information of therapeutic drugs.
7. The digital health life platform control method based on big data according to claim 5, wherein the analyzing the health data by the data processing end according to the big data and the artificial intelligence algorithm is specifically as follows: cleaning the collected original data to remove repeated data, abnormal data and incomplete data; extracting important characteristic values from the data, and selecting data indexes to be analyzed according to basic information, physical conditions and health targets preset by a user, wherein the analyzed data indexes comprise: blood pressure, blood glucose, number of steps of exercise, and sleep quality; and analyzing the selected data indexes, determining the health state, trend and preference of the user through a data mining and statistical method, and automatically generating the health file of the user according to the analysis result.
8. The digital health life platform control method based on big data according to claim 5, wherein the analyzing physical condition and health trend of the user and predicting health risk possibly occurring in the future by the intelligent early warning system according to the health record and medical record of the user specifically comprises: acquiring a health file and a medical record of a user, wherein the health file and the medical record comprise personal information, physiological indexes and physical examination reports of the user; preprocessing and cleaning the obtained health files and medical record data, removing abnormal data and missing data, and converting the abnormal data and missing data into a universal format; selecting the characteristics of the obtained data according to preset characteristics possibly causing health risks of the user, wherein the characteristics possibly causing health risks of the user are at least daily physiological indexes and life style factors of the user; and establishing a health risk prediction model according to the selected health risk characteristics, and predicting the health risk through the model.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310856250.4A CN116798631A (en) | 2023-07-13 | 2023-07-13 | Digital healthy living platform based on big data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310856250.4A CN116798631A (en) | 2023-07-13 | 2023-07-13 | Digital healthy living platform based on big data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116798631A true CN116798631A (en) | 2023-09-22 |
Family
ID=88044901
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310856250.4A Pending CN116798631A (en) | 2023-07-13 | 2023-07-13 | Digital healthy living platform based on big data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116798631A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117038100A (en) * | 2023-10-09 | 2023-11-10 | 深圳市乗名科技有限公司 | Health management system based on IOT technology |
| CN117457208A (en) * | 2023-11-03 | 2024-01-26 | 青岛众精普汇医学科技有限公司 | Urine digital health management system based on data analysis |
-
2023
- 2023-07-13 CN CN202310856250.4A patent/CN116798631A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117038100A (en) * | 2023-10-09 | 2023-11-10 | 深圳市乗名科技有限公司 | Health management system based on IOT technology |
| CN117038100B (en) * | 2023-10-09 | 2024-03-15 | 深圳市乗名科技有限公司 | Health management system based on IOT technology |
| CN117457208A (en) * | 2023-11-03 | 2024-01-26 | 青岛众精普汇医学科技有限公司 | Urine digital health management system based on data analysis |
| CN117457208B (en) * | 2023-11-03 | 2024-04-23 | 青岛众精普汇医学科技有限公司 | Urine digital health management system based on data analysis |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Chatrati et al. | Smart home health monitoring system for predicting type 2 diabetes and hypertension | |
| US20230082019A1 (en) | Systems and methods for monitoring brain health status | |
| CN116798631A (en) | Digital healthy living platform based on big data | |
| US20110288379A1 (en) | Body sign dynamically monitoring system | |
| WO2014036173A1 (en) | Methods and systems for calculating and using statistical models to predict medical events | |
| JP2018524137A (en) | Method and system for assessing psychological state | |
| CN113241196B (en) | Remote medical treatment and grading monitoring system based on cloud-terminal cooperation | |
| KR102522039B1 (en) | Method and system for intelligent processing of physiological data | |
| CN115662631A (en) | AI intelligence discrimination-based nursing home management system | |
| Bazi et al. | Real-time mobile-based electrocardiogram system for remote monitoring of patients with cardiac arrhythmias | |
| Ghazal et al. | An integrated caregiver-focused mHealth framework for elderly care | |
| KR20130062464A (en) | System and method based on usn for bio-signal gathering | |
| Panagiotou et al. | A multi: modal decision making system for an ambient assisted living environment | |
| KR20150102880A (en) | System and method for depression monitoring based on user information | |
| Ebada et al. | Applying apache spark on streaming big data for health status prediction | |
| Kim et al. | Analysis of bio-signal data of stroke patients and normal elderly people for real-time monitoring | |
| EP4113535A1 (en) | Remote monitoring methods and systems for monitoring patients suffering from chronical inflammatory diseases | |
| CN114093450A (en) | Chronic disease management system and method based on wearable equipment | |
| Pawar et al. | A survery on e-health care monitoring for heart care using IOT | |
| Shwetha et al. | Remote monitoring of heart patients using robotic process automation (RPA) | |
| Singh et al. | Performance of IoT-Enabled Devices in Remote Health Monitoring Applications | |
| Kumar et al. | Proactive health monitoring and screening using IoT and Artificial Intelligence | |
| US20220359073A1 (en) | Edge-intelligent Iot-based Wearable Device For Detection of Cravings in Individuals | |
| Alhameed et al. | Remote Patient Monitoring: Data Sharing and Prediction Using Machine Learning | |
| Singh et al. | 8 Performance of IoT |
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 |