CN112509698A - Health monitoring management system based on big data - Google Patents

Health monitoring management system based on big data Download PDF

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Publication number
CN112509698A
CN112509698A CN202011487974.9A CN202011487974A CN112509698A CN 112509698 A CN112509698 A CN 112509698A CN 202011487974 A CN202011487974 A CN 202011487974A CN 112509698 A CN112509698 A CN 112509698A
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data
platform
management
module
unit
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韩锐丰
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Anhui Shengdong Technology Co Ltd
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Anhui Shengdong Technology Co Ltd
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    • 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
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/602—Providing cryptographic facilities or services
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/62—Protecting access to data via a platform, e.g. using keys or access control rules
    • G06F21/6218—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
    • G06F21/6245—Protecting personal data, e.g. for financial or medical purposes
    • 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

Abstract

The invention discloses a health monitoring and management system based on big data, which comprises a login unit, a data uploading platform, a management terminal, a cloud protection platform, a big database, a data preprocessing platform, a data matching module, a data management module, a cloud server, an information pushing unit, a mobile terminal, a government inquiry and supervision interface, an area chain mutual-aid platform and a data acquisition end, wherein the data uploading platform is connected with the data acquisition end through the cloud protection platform; one end of a data output port of the mobile terminal is in communication connection with the data uploading platform; one end of the mobile terminal data input port is in communication connection with the data acquisition end through a network. According to the system, personal physiological information data can be fed back to the system in real time through the data acquisition terminal, the cloud server and the data preprocessing platform, and the system can provide a professional health management, treatment or hospitalizing recommendation scheme by utilizing an internal algorithm and combining with professionals, so that the system is helpful for a user or related patients to know the self health condition and quickly prevent and treat diseases.

Description

Health monitoring management system based on big data
Technical Field
The invention belongs to the technical field of health information management, relates to a big data utilization technology in the medical industry, and particularly relates to a health monitoring and management system based on big data.
Background
By 2015, the number of elderly over 60 years of age will proliferate to around 2.2 billion; the rapid aging of population leads to the rapid increase of the number of patients with chronic diseases, thereby greatly increasing the medical expense; if the correspondence is not improved, the cost can be increased by 70% in the next five years; by 2015, the total sanitary expenditure of China is estimated to reach 3.3 trillion and account for 6.5% of GDP; the method is characterized in that prediction is made around dealing with population aging and chronic diseases, and corresponding production element planning such as fund, institution, talents, information, technology and the like is developed; at present, most of medical systems at the present stage are used for recording basic information and disease conditions of patients in hospitals, registration, queuing, outpatient appointment, charging systems and the like are mostly involved, and even if a patient information collection system is provided, the collected information is little and targeted collection is not performed.
At the present stage, the health information management system cannot process massive medical data and can only analyze a small amount of data, and the obtained result has no universality and accuracy, and is low in analysis speed and easy to make mistakes; contradictory to this, in recent years, with the rapid expansion of medical and health data and the increase of geometric grade; based on the above problems, a big data health information management system is needed, which can perform health monitoring and disease management on people in real time, and meanwhile, with the development of the network era, the disclosure of personal information is more and more serious, so that how to effectively protect the personal information while performing disease management becomes a problem to be solved.
Disclosure of Invention
The invention aims to provide a health monitoring and management system based on big data.
The technical problem to be solved by the invention is as follows:
(1) how to manage and prevent diseases of people and how to link with governments;
(2) how to effectively encrypt information when managing a group of people;
(3) how to effectively realize the intercommunication of information flow in the disease management.
The purpose of the invention can be realized by the following technical scheme:
a health monitoring and management system based on big data comprises a login unit, a data uploading platform, a management terminal, a cloud protection platform, a big database, a data preprocessing platform, a data matching module, a data management module, a cloud server, an information pushing unit, a mobile terminal, a government inquiry and supervision interface, an area chain mutual-aid platform and a data acquisition end;
one end of the data output port of the mobile terminal is in communication connection with the data uploading platform; one end of the mobile terminal data input port is in communication connection with the data acquisition end through a network; the data end of the mobile terminal and the information pushing unit carry out bidirectional data transmission; the data output end of the data uploading platform is in communication connection with the data preprocessing platform; the data output end of the data preprocessing platform is connected with a data packet generating module; the data output end of the data packet generation module is in communication connection with the data matching module; the data matching module and the data management module carry out bidirectional data transmission with the big database; the government inquiry and supervision interface data terminal is in communication connection with the login unit; the data terminals of the area chain mutual-aid platform, the cloud server and the data management module are in bidirectional data transmission with the management terminal; one end of the data output port of the data matching module is connected with a data output module;
one end of the data output port of the data output module is respectively connected with a conventional data output unit and an abnormal data output unit in a communication way; the data output end of the conventional data output unit is in communication connection with the cloud server; the data output end of the abnormal data output unit is in communication connection with the management terminal;
the data acquisition end, the data preprocessing platform, the data packet generation module, the data matching module, the big database, the login unit, the information pushing unit and the cloud server data end are in bidirectional communication with the cloud protection platform;
the data preprocessing platform comprises a data classification unit and a data screening unit which are sequentially in communication connection.
Furthermore, the data acquisition end is any one or more of wearable medical equipment, a sphygmomanometer, a blood glucose meter, a thermometer, a pulse oximeter, an apnea monitor and an electrocardiograph monitor; the information which can be collected by the data collecting end comprises any one or more of human body temperature data, blood pressure data, blood oxygen data, respiration data and heart rate electrocardio data; the data acquisition end is used for acquiring human body sign information data of a human body.
Further, the data preprocessing platform sequentially classifies and screens the data uploaded by the mobile terminal through data processing software or a data processing algorithm;
during classification, the data processing platform adopts the following algorithm flow, and after the data classification screening processing is finished, the data preprocessing platform transmits the data to the data packet generation module through data processing or integrated software;
during the data generation process of the data packet generation module, the cloud protection platform automatically performs format conversion and data encryption on data; after the data integration is finished, the data packet generation module outputs the data to the data matching module, and the data matching module automatically compares the received data with the data in the big database through data processing software;
the data uploading platform automatically marks related data through a related algorithm in combination with an uploading time period in the data transmission process of the data, wherein the uploading time period is marked as t in sequence by taking 30min as a segment in the uploading process1、t2、t3、t4、t5、t6、t7……The uploading date is generated in a follow-up way, and the uploading time period t is1Then, the following classification marking method is adopted for uploading data in the time interval, and thus, the human body temperature data can be automatically marked as A-t1The blood pressure data will be automatically marked as B-type-t1The blood oxygen data will be automatically marked as class C-t1The respiratory data will be automatically labeled as class D-t1The heart rate electrocardio data can be automatically marked as E type-t1；
After the data is marked by the data uploading platform, the processed data is uploaded to the data preprocessing platform through a network or an internal transmission system, after the data preprocessing platform receives the data, the data uploaded by the data uploading platform is automatically filed in A, B, C, D and E types through mark identification software, after the data preprocessing platform is filed, the uploaded data is screened and removed through a related algorithm or software by the data screening unit, and when the data screening unit works, the following algorithm is adopted;
such as t1Next, the human body temperature data received by the data screening unit is marked as A-t type1The specific temperature data under this category is labeled t1-[ADetection of]；t1Blood pressure data under B after identification is class-t1The specific temperature data under this category is labeled t1-[BDetection of]And so on;
the data screening unit is internally provided with a multi-type data screening threshold value under various time periods, taking A-type data as an example:
such as t1In time period, the built-in screening threshold value of the data screening unit is t1-[Amin-Amax]The specific uploaded data of the data classification unit is t1-[ADetection of]The data preprocessing platform automatically compares the data in the time period through an algorithm, and concretely comprises the following steps;
SS001, Dang [ A ]Detection of]The value is in [ A ]min-Amax]In the meantime, the data preprocessing platform outputs the data to the data packet generating module;
SS002, Dang [ A ]Detection of]The value is 0.85-1.15 times [ A ]min-Amax]In the meantime, the data preprocessing platform still outputs the variable element to the data packet generating module according to the variable element rule;
SS003, Dang [ A ]Detection of]The value is not 0.85-1.15 times [ A ]min-Amax]And do not belong to [ A ]min-Amax]In the meantime, the data preprocessing platform rejects the group of data, after the data is rejected, the cloud server feeds back information to the mobile terminal through the information pushing unit, and the mobile terminal performs re-acquisition and re-uploading of the rejected information according to information prompt;
and the big database provides data support for the data preprocessing platform.
Further, the data matching module is used for receiving and matching the data received by the data packet generating module, when the data matching module is matched, the data is automatically compared with the data in the big database, and a corresponding health management, treatment or hospitalization recommendation scheme under a certain type of threshold value is stored in the big database;
such as t1In time period, the recommendation threshold of the A-type data scheme built in the big database comprises the following various t1-[P1A1-P2A2]、t1-[P2A2-P3A3]、t1-[P3A3-PmaxAmax]……；
Wherein [ P ]1A1]、[P2A2]、[P3A3]、[P4A4]The value is set in continuous increment; and [ P1A1]A value of 0.85 or more times [ A ]min]，[PmaxAmax]Is less than or equal to 1.15 times [ A ]max]；
Wherein, t1-[P1A1-P2A2]The corresponding health management, treatment or hospitalization recommendation scheme is P1；
t1-[P2A2-P3A3]The corresponding health management, treatment or hospitalization recommendation scheme is P2；
t1-[P3A3-P4A4]The corresponding health management, treatment or hospitalization recommendation scheme is P3And so on;
wherein, when matching, the method comprises the following steps:
SS001, when t1-[ADetection of]In (A)Detection of]Greater than [ P1A1]Is less than or equal to [ P2A2]The data matching module automatically matches P1Scheme, data matching module matches P1The scheme is to be output to a conventional data output unit through a data output unit;
SS002. when t is1-[ADetection of]In (A)Detection of]Greater than [ P2A2]Is less than or equal to [ P3A3]The data matching module automatically matches P2Scheme, data matching module matches P2The scheme is output to a conventional data output unit through a data output unit, and so on;
SS003, when t1-[ADetection of]In (A)Detection of]Is less than [ P1A1]Or greater than [ PmaxAmax]When the data matching module outputs the group of data to the abnormal data output unit; by analogy, the data matching module finally outputs the A type and the B type……And integrating the various schemes of (1);
after receiving the integrated output scheme of the data matching module, the conventional data output unit immediately feeds the integrated scheme back to the mobile terminal through the cloud server and the information push unit;
the abnormal data output unit feeds the abnormal data back to the management terminal after receiving the abnormal data feedback of the data matching module, and the management terminal gives a health recommendation scheme in a set period according to occupational judgment and opinion of a regional chain mutual aid platform; the health recommendation scheme finally given by the management terminal is fed back to the mobile terminal through the cloud server and the information push unit;
meanwhile, the management terminal establishes t according to the abnormal data1-[PXAX-PYAY]And establishing the corresponding scheme under the threshold value as PXAnd meanwhile, establishing the data into a large database.
Furthermore, the management terminal updates, edits, adds, deletes and modifies the data in the big database through the data management module; the data management module is data processing software;
e.g. adding t1-[PXAX-PYAY]And corresponding scheme P under the thresholdX；
Pruning, editing or modifying [ P ]1A1]、[P2A2]、[P3A3]、[P4A4]、[PmaxAmax]、[PXAX]、[PYAY]、P1、P2、P3、Pmax、PXAnd PYAny one or more of.
Further, the cloud protection platform performs MD5 algorithm encryption, network protection, virus resistance, authority verification, data format conversion and data cloud backup on data in the data acquisition end, the data preprocessing platform, the data packet generation module, the data matching module, the big database, the login unit, the information pushing unit and the cloud server based on a network security management and defense technology.
Further, the login unit provides login access service for the relevant equipment or the relevant user; the management terminal is any one or more of a PC (personal computer) and a WEB (world Wide Web) terminal; the management terminal is synchronously used online by a department of class A and a department of class B … …; after the management terminal receives the abnormal data, the type of the first-level abnormal data is automatically fed back to each department; the block chain mutual-help platform is any one or more of an information communication community, a chat room and a collaboration platform; the management terminal feeds back the information obtained from the big database to the block chain mutual-aid platform according to authorization; and the management terminal extracts the screened and verified data from the block chain mutual-aid platform and updates, adds and deletes the data in the large database.
Furthermore, the government inquiry and supervision interface establishes a related report, disease management, epidemic prevention and crowd management scheme after inquiring the data in the big database; the government inquiry and supervision interface can perform related management and information push on the system;
the mobile terminal can actively inquire relevant information in the cloud server and the big database through application; the mobile cloud server feeds back relevant information to the mobile terminal after receiving the query application of the mobile terminal; the big database performs storage service on all data under the system;
the data output module can also output health and data reports in a certain period of time.
The invention has the beneficial effects that:
(1) according to the system, personal physiological information data can be fed back to the system in real time through the data acquisition terminal, the cloud server and the data preprocessing platform, and the system can provide a professional health management, treatment or hospitalizing recommendation scheme by utilizing an internal algorithm and combining with professionals, so that the system is helpful for a user or related patients to know the self health condition and quickly prevent and treat diseases.
(2) The cloud protection platform is arranged, so that the use safety and the use stability of the system can be guaranteed, meanwhile, the probability of personal information sending leakage can be effectively reduced through the arrangement of the protection platform, the privacy of the system in use can be effectively improved, the timely feedback of disease information and the large-scale prevention and treatment management of diseases can be effectively realized through the arrangement of the government inquiry and supervision interface, the regional communication in the disease management process can be realized through the arrangement of the regional chain mutual assistance platform, and the treatment and protection efficiency of the system on the diseases can be effectively improved.
Drawings
In order to facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
FIG. 1 is a block diagram of the system of the present invention.
Detailed Description
As shown in fig. 1, a health monitoring and management system based on big data includes a login unit, a data upload platform, a management terminal, a cloud protection platform, a big database, a data preprocessing platform, a data matching module, a data management module, a cloud server, an information push unit, a mobile terminal, a government inquiry and supervision interface, an area chain mutual assistance platform, and a data acquisition end;
one end of the data output port of the mobile terminal is in communication connection with the data uploading platform; one end of the mobile terminal data input port is in communication connection with the data acquisition end through a network; the data end of the mobile terminal and the information pushing unit carry out bidirectional data transmission; the data output end of the data uploading platform is in communication connection with the data preprocessing platform; the data output end of the data preprocessing platform is connected with a data packet generating module; the data output end of the data packet generation module is in communication connection with the data matching module; the data matching module and the data management module carry out bidirectional data transmission with the big database; the government inquiry and supervision interface data terminal is in communication connection with the login unit; the data terminals of the area chain mutual-aid platform, the cloud server and the data management module are in bidirectional data transmission with the management terminal; one end of the data output port of the data matching module is connected with a data output module;
one end of the data output port of the data output module is respectively connected with a conventional data output unit and an abnormal data output unit in a communication way; the data output end of the conventional data output unit is in communication connection with the cloud server; the data output end of the abnormal data output unit is in communication connection with the management terminal;
the data acquisition end, the data preprocessing platform, the data packet generation module, the data matching module, the big database, the login unit, the information pushing unit and the cloud server data end are in bidirectional communication with the cloud protection platform;
the data preprocessing platform comprises a data classification unit and a data screening unit which are sequentially in communication connection.
The data acquisition end is any one or more of wearable medical equipment, a sphygmomanometer, a blood glucose meter, a thermometer, a pulse oximeter, an apnea monitor and an ECG monitor; the information which can be collected by the data collecting end comprises any one or more of human body temperature data, blood pressure data, blood oxygen data, respiration data and heart rate electrocardio data; the data acquisition end is used for acquiring human body sign information data of a human body.
The data preprocessing platform sequentially classifies and screens the data uploaded by the mobile terminal through data processing software or a data processing algorithm;
during classification, the data processing platform adopts the following algorithm flow, and after the data classification screening processing is finished, the data preprocessing platform transmits the data to the data packet generation module through data processing or integrated software;
during the data generation process of the data packet generation module, the cloud protection platform automatically performs format conversion and data encryption on data; after the data integration is finished, the data packet generation module outputs the data to the data matching module, and the data matching module automatically compares the received data with the data in the big database through data processing software;
the data uploading platform automatically marks related data through a related algorithm in combination with an uploading time period in the data transmission process of the data, wherein the uploading time period is marked as t in sequence by taking 30min as a segment in the uploading process1、t2、t3、t4、t5、t6、t7……The uploading date is generated in a follow-up way, and the uploading time period t is1Then, the following classification marking method is adopted for uploading data in the time interval, and thus, the human body temperature data can be automatically marked as A-t1The blood pressure data will be automatically marked as B-type-t1The blood oxygen data will be automatically marked as class C-t1The respiratory data will be automatically labeled as class D-t1The heart rate electrocardio data can be automatically marked as E type-t1；
After the data is marked by the data uploading platform, the processed data is uploaded to the data preprocessing platform through a network or an internal transmission system, after the data preprocessing platform receives the data, the data uploaded by the data uploading platform is automatically filed in A, B, C, D and E types through mark identification software, after the data preprocessing platform is filed, the uploaded data is screened and removed through a related algorithm or software by the data screening unit, and when the data screening unit works, the following algorithm is adopted;
such as t1Next, the human body temperature data received by the data screening unit is marked as A-t type1The specific temperature data under this category is labeled t1-[ADetection of]；t1Blood pressure data under B after identification is class-t1The specific temperature data under this category is labeled t1-[BDetection of]In this class, withPushing;
the data screening unit is internally provided with a multi-type data screening threshold value under various time periods, taking A-type data as an example:
such as t1In time period, the built-in screening threshold value of the data screening unit is t1-[Amin-Amax]The specific uploaded data of the data classification unit is t1-[ADetection of]The data preprocessing platform automatically compares the data in the time period through an algorithm, and concretely comprises the following steps;
SS001, Dang [ A ]Detection of]The value is in [ A ]min-Amax]In the meantime, the data preprocessing platform outputs the data to the data packet generating module;
SS002, Dang [ A ]Detection of]The value is 0.85-1.15 times [ A ]min-Amax]In the meantime, the data preprocessing platform still outputs the variable element to the data packet generating module according to the variable element rule;
SS003, Dang [ A ]Detection of]The value is not 0.85-1.15 times [ A ]min-Amax]And do not belong to [ A ]min-Amax]In the meantime, the data preprocessing platform rejects the group of data, after the data is rejected, the cloud server feeds back information to the mobile terminal through the information pushing unit, and the mobile terminal performs re-acquisition and re-uploading of the rejected information according to information prompt;
and the big database provides data support for the data preprocessing platform.
The data matching module is used for receiving and matching the data received by the data packet generating module, automatically comparing the data with the data in the big database when the data matching module is matched, and storing a corresponding health management, treatment or hospitalization recommendation scheme under a certain type of threshold in the big database;
such as t1In time period, the recommendation threshold of the A-type data scheme built in the big database comprises the following various t1-[P1A1-P2A2]、t1-[P2A2-P3A3]、t1-[P3A3-PmaxAmax]……；
Wherein [ P ]1A1]、[P2A2]、[P3A3]、[P4A4]The value is set in continuous increment; and [ P1A1]A value of 0.85 or more times [ A ]min]，[PmaxAmax]Is less than or equal to 1.15 times [ A ]max]；
Wherein, t1-[P1A1-P2A2]The corresponding health management, treatment or hospitalization recommendation scheme is P1；
t1-[P2A2-P3A3]The corresponding health management, treatment or hospitalization recommendation scheme is P2；
t1-[P3A3-P4A4]The corresponding health management, treatment or hospitalization recommendation scheme is P3And so on;
wherein, when matching, the method comprises the following steps:
SS001, when t1-[ADetection of]In (A)Detection of]Greater than [ P1A1]Is less than or equal to [ P2A2]The data matching module automatically matches P1Scheme, data matching module matches P1The scheme is to be output to a conventional data output unit through a data output unit;
SS002, when t1-[ADetection of]In (A)Detection of]Greater than [ P2A2]Is less than or equal to [ P3A3]The data matching module automatically matches P2Scheme, data matching module matches P2The scheme is output to a conventional data output unit through a data output unit, and so on;
SS003, when t1-[ADetection of]In (A)Detection of]Is less than [ P1A1]Or greater than [ PmaxAmax]When the data matching module outputs the group of data to the abnormal data output unit; by analogy, the data matching module finally outputs the A type and the B type……And integrating the various schemes of (1);
after receiving the integrated output scheme of the data matching module, the conventional data output unit immediately feeds the integrated scheme back to the mobile terminal through the cloud server and the information push unit;
the abnormal data output unit feeds the abnormal data back to the management terminal after receiving the abnormal data feedback of the data matching module, and the management terminal gives a health recommendation scheme in a set period according to occupational judgment and opinion of a regional chain mutual aid platform; the health recommendation scheme finally given by the management terminal is fed back to the mobile terminal through the cloud server and the information push unit;
meanwhile, the management terminal establishes t according to the abnormal data1-[PXAX-PYAY]And establishing the corresponding scheme under the threshold value as PX，While building the data into a large database.
The management terminal updates, edits, adds, deletes and modifies the data in the big database through the data management module; the data management module is data processing software;
e.g. adding t1-[PXAX-PYAY]And corresponding scheme P under the thresholdX；
Pruning, editing or modifying [ P ]1A1]、[P2A2]、[P3A3]、[P4A4]、[PmaxAmax]、[PXAX]、[PYAY]、P1、P2、P3、Pmax、PXAnd PYAny one or more of.
The cloud protection platform carries out MD5 algorithm encryption, network protection, virus resistance, authority verification, data format conversion and data cloud backup on data in a data acquisition end, a data preprocessing platform, a data packet generation module, a data matching module, a big database, a login unit, an information pushing unit and a cloud server based on a network security management and defense technology.
The login unit provides login access service for related equipment or related users; the management terminal is any one or more of a PC (personal computer) and a WEB (world Wide Web) terminal; the management terminal is synchronously used online by a department of class A and a department of class B … …; after the management terminal receives the abnormal data, the type of the first-level abnormal data is automatically fed back to each department; the block chain mutual-help platform is any one or more of an information communication community, a chat room and a collaboration platform; the management terminal feeds back the information obtained from the big database to the block chain mutual-aid platform according to authorization; and the management terminal extracts the screened and verified data from the block chain mutual-aid platform and updates, adds and deletes the data in the large database.
The government inquiry and supervision interface establishes a relevant report form, a disease management scheme, an epidemic prevention scheme and a crowd management scheme after inquiring data in a large database; the government inquiry and supervision interface can perform related management and information push on the system;
the mobile terminal can actively inquire relevant information in the cloud server and the big database through application; the mobile cloud server feeds back relevant information to the mobile terminal after receiving the query application of the mobile terminal; the big database performs storage service on all data under the system;
the data output module can also output health and data reports in a certain period of time.
When the system is used, government agencies can conduct interval management on the system through a government inquiry and supervision interface, relevant professional agencies conduct direct management on the system according to professional knowledge, and when the relevant professional agencies manage, disease monitoring thresholds such as [ P ] are monitored through a data management module according to pathological characteristics and pathological development conditions1A1]、[P2A2]、[P3A3]、[P4A4]、[PmaxAmax]、[PXAX]、[PYAY]、P1、P2、P3、Pmax、PXAnd PYAny one or more of the above steps are updated, edited, added, deleted and modified, so that the action effect of the system is ensured, a government organization realizes disease and disease joint control by referring to big data, and simultaneously establishes related reports, disease management, epidemic prevention and crowd management schemes according to related data, so that the pathological prevention and disease management of large-scale crowds are realized; the cloud protection platform performs MD5 algorithm encryption, network protection, virus resistance, authority verification, data format conversion and data cloud backup on the system in the whole operation process of the system, so that the safety and stability of the system in operation are fully ensured, the collection efficiency of the system on pathological data can be effectively improved and the absorption of the pathological data is ensured through the establishment of the data preprocessing platform, and the workload of managers can be effectively reduced and the automatic operation of the system and the automatic prevention and treatment of the pathology can be realized through the establishment of the data matching module.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.

Claims (8)

1. A health monitoring and management system based on big data is characterized by comprising a login unit, a data uploading platform, a management terminal, a cloud protection platform, a big database, a data preprocessing platform, a data matching module, a data management module, a cloud server, an information pushing unit, a mobile terminal, a government inquiry and supervision interface, an area chain mutual-help platform and a data acquisition end;
one end of the data output port of the mobile terminal is in communication connection with the data uploading platform; one end of the mobile terminal data input port is in communication connection with the data acquisition end through a network; the data end of the mobile terminal and the information pushing unit carry out bidirectional data transmission; the data output end of the data uploading platform is in communication connection with the data preprocessing platform; the data output end of the data preprocessing platform is connected with a data packet generating module; the data output end of the data packet generation module is in communication connection with the data matching module; the data matching module and the data management module carry out bidirectional data transmission with the big database; the government inquiry and supervision interface data terminal is in communication connection with the login unit; the data terminals of the area chain mutual-aid platform, the cloud server and the data management module are in bidirectional data transmission with the management terminal; one end of the data output port of the data matching module is connected with a data output module;
one end of the data output port of the data output module is respectively connected with a conventional data output unit and an abnormal data output unit in a communication way; the data output end of the conventional data output unit is in communication connection with the cloud server; the data output end of the abnormal data output unit is in communication connection with the management terminal;
the data acquisition end, the data preprocessing platform, the data packet generation module, the data matching module, the big database, the login unit, the information pushing unit and the cloud server data end are in bidirectional communication with the cloud protection platform;
the data preprocessing platform comprises a data classification unit and a data screening unit which are sequentially in communication connection.
2. The big data based health monitoring and management system as claimed in claim 1, wherein the data collection end is any one or more of wearable medical equipment, sphygmomanometer, blood glucose meter, thermometer, pulse oximeter, apnea monitor, and electrocardiograph monitor; the information which can be collected by the data collecting end comprises any one or more of human body temperature data, blood pressure data, blood oxygen data, respiration data and heart rate electrocardio data; the data acquisition end is used for acquiring human body sign information data of a human body.
3. The big-data-based health monitoring and management system according to claim 1, wherein the data preprocessing platform sequentially classifies and screens the data uploaded by the mobile terminal through data processing software or a data processing algorithm;
during classification, the data processing platform adopts the following algorithm flow, and after the data classification screening processing is finished, the data preprocessing platform transmits the data to the data packet generation module through data processing or integrated software;
during the data generation process of the data packet generation module, the cloud protection platform automatically performs format conversion and data encryption on data; after the data integration is finished, the data packet generation module outputs the data to the data matching module, and the data matching module automatically compares the received data with the data in the big database through data processing software;
the data uploading platform automatically marks related data through a related algorithm in combination with an uploading time period in the data transmission process of the data, wherein the uploading time period is marked as t in sequence by taking 30min as a segment in the uploading process1、t2、t3、t4、t5、t6、t7……The uploading date is generated in a follow-up way, and the uploading time period t is1Then, the following classification marking method is adopted for uploading data in the time interval, and thus, the human body temperature data can be automatically marked as A-t1The blood pressure data will be automatically marked as B-type-t1The blood oxygen data will be automatically marked as class C-t1The respiratory data will be automatically labeled as class D-t1The heart rate electrocardio data can be automatically marked as E type-t1；
After the data is marked by the data uploading platform, the processed data is uploaded to the data preprocessing platform through a network or an internal transmission system, after the data preprocessing platform receives the data, the data uploaded by the data uploading platform is automatically filed in A, B, C, D and E types through mark identification software, after the data preprocessing platform is filed, the uploaded data is screened and removed through a related algorithm or software by the data screening unit, and when the data screening unit works, the following algorithm is adopted;
such as t1Next, the human body temperature data received by the data screening unit is marked as A-t type1The specific temperature data under this category is labeled t1-[ADetection of]；t1Blood pressure data under B after identification is class-t1The specific temperature data under this category is labeled t1-[BDetection of]And so on;
the data screening unit is internally provided with a multi-type data screening threshold value under various time periods, taking A-type data as an example:
such as t1In time period, the built-in screening threshold value of the data screening unit is t1-[Amin-Amax]The specific uploaded data of the data classification unit is t1-[ADetection of]The data preprocessing platform automatically compares the data in the time period through an algorithm, and concretely comprises the following steps;
SS001, Dang [ A ]Detection of]The value is in [ A ]min-Amax]In the meantime, the data preprocessing platform outputs the data to the data packet generating module;
SS002, Dang [ A ]Detection of]The value is 0.85-1.15 times [ A ]min-Amax]In the meantime, the data preprocessing platform still outputs the variable element to the data packet generating module according to the variable element rule;
SS003, Dang [ A ]Detection of]The value is not 0.85-1.15 times [ A ]min-Amax]And do not belong to [ A ]min-Amax]In the meantime, the data preprocessing platform rejects the group of data, after the data is rejected, the cloud server feeds back information to the mobile terminal through the information pushing unit, and the mobile terminal performs re-acquisition and re-uploading of the rejected information according to information prompt;
and the big database provides data support for the data preprocessing platform.
4. The big-data-based health monitoring and management system according to claim 1, wherein the data matching module is configured to receive and match the data received by the data packet generation module, and when the data matching module matches the data, the data is automatically compared with the data in the big database, and the big database stores a corresponding health management, treatment or hospitalization recommendation scheme under a certain type of a certain threshold;
such as t1In time period, the recommendation threshold of the A-type data scheme built in the big database comprises the following various t1-[P1A1-P2A2]、t1-[P2A2-P3A3]、t1-[P3A3-PmaxAmax]……；
Wherein [ P ]1A1]、[P2A2]、[P3A3]、[P4A4]The value is set in continuous increment; and [ P1A1]A value of 0.85 or more times [ A ]min]，[PmaxAmax]Is less than or equal to 1.15 times [ A ]max]；
Wherein, t1-[P1A1-P2A2]The corresponding health management, treatment or hospitalization recommendation scheme is P1；
t1-[P2A2-P3A3]The corresponding health management, treatment or hospitalization recommendation scheme is P2；
t1-[P3A3-P4A4]The corresponding health management, treatment or hospitalization recommendation scheme is P3And so on;
wherein, when matching, the method comprises the following steps:
SS001, when t1-[ADetection of]In (A)Detection of]Greater than [ P1A1]Is less than or equal to [ P2A2]The data matching module automatically matches P1Scheme, data matching module matches P1The scheme is to be output to a conventional data output unit through a data output unit;
SS002, when t1-[ADetection of]In (A)Detection of]Greater than [ P2A2]Is less than or equal to [ P3A3]The data matching module automatically matches P2Scheme, data matching module matches P2The scheme is output to the data output unitA conventional data output unit, and so on;
SS003, when t1-[ADetection of]In (A)Detection of]Is less than [ P1A1]Or greater than [ PmaxAmax]When the data matching module outputs the group of data to the abnormal data output unit; by analogy, the data matching module finally outputs the A type and the B type……And integrating the various schemes of (1);
after receiving the integrated output scheme of the data matching module, the conventional data output unit immediately feeds the integrated scheme back to the mobile terminal through the cloud server and the information push unit;
the abnormal data output unit feeds the abnormal data back to the management terminal after receiving the abnormal data feedback of the data matching module, and the management terminal gives a health recommendation scheme in a set period according to occupational judgment and opinion of a regional chain mutual aid platform; the health recommendation scheme finally given by the management terminal is fed back to the mobile terminal through the cloud server and the information push unit;
meanwhile, the management terminal establishes t according to the abnormal data1-[PXAX-PYAY]And establishing the corresponding scheme under the threshold value as PX，While building the data into a large database.
5. The big data based health monitoring and management system according to claim 1, wherein the management terminal updates, edits, adds, deletes and modifies the data in the big database through the data management module; the data management module is data processing software;
e.g. adding t1-[PXAX-PYAY]And corresponding scheme P under the thresholdX；
Pruning, editing or modifying [ P ]1A1]、[P2A2]、[P3A3]、[P4A4]、[PmaxAmax]、[PXAX]、[PYAY]、P1、P2、P3、Pmax、PXAnd PYAny one or more of.
6. The big data based health monitoring and management system of claim 1, wherein the cloud protection platform performs MD5 algorithm encryption, network protection, virus defense, authority verification, data format conversion and data cloud backup on data in the data acquisition end, the data preprocessing platform, the data packet generation module, the data matching module, the big database, the login unit, the information pushing unit and the cloud server based on network security management and defense technology.
7. The big data based health monitoring and management system as claimed in claim 1, wherein the login unit provides login access service to the related device or the related user; the management terminal is any one or more of a PC (personal computer) and a WEB (world Wide Web) terminal; the management terminal is synchronously used online by a department of class A and a department of class B … …; after the management terminal receives the abnormal data, the type of the first-level abnormal data is automatically fed back to each department; the block chain mutual-help platform is any one or more of an information communication community, a chat room and a collaboration platform; the management terminal feeds back the information obtained from the big database to the block chain mutual-aid platform according to authorization; and the management terminal extracts the screened and verified data from the block chain mutual-aid platform and updates, adds and deletes the data in the large database.
8. The big data based health monitoring and management system of claim 1, wherein the government query and supervision interface establishes relevant statements, disease management, epidemic prevention and crowd management schemes after querying data in the big database; the government inquiry and supervision interface can perform related management and information push on the system;
the mobile terminal can actively inquire relevant information in the cloud server and the big database through application; the mobile cloud server feeds back relevant information to the mobile terminal after receiving the query application of the mobile terminal; the big database performs storage service on all data under the system;
the data output module can also output health and data reports in a certain period of time.
CN202011487974.9A 2020-12-16 2020-12-16 Health monitoring management system based on big data Withdrawn CN112509698A (en)

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Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113886126A (en) * 2021-10-13 2022-01-04 中里大数据服务(上海)有限公司 Fault-tolerant server-based intelligent management and control system and method
CN115359868A (en) * 2022-09-14 2022-11-18 亿慧云智能科技（深圳）股份有限公司 Intelligent medical monitoring method and system based on cloud computing technology
CN117240576A (en) * 2023-10-09 2023-12-15 上海市口腔医院(上海市口腔健康中心) Intrusion detection method and system for medical platform of Internet of things
WO2023246638A1 (en) * 2022-06-23 2023-12-28 维沃移动通信有限公司 Information processing method and apparatus, wearable device and electronic device

Cited By (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113886126A (en) * 2021-10-13 2022-01-04 中里大数据服务(上海)有限公司 Fault-tolerant server-based intelligent management and control system and method
WO2023246638A1 (en) * 2022-06-23 2023-12-28 维沃移动通信有限公司 Information processing method and apparatus, wearable device and electronic device
CN115359868A (en) * 2022-09-14 2022-11-18 亿慧云智能科技（深圳）股份有限公司 Intelligent medical monitoring method and system based on cloud computing technology
CN117240576A (en) * 2023-10-09 2023-12-15 上海市口腔医院(上海市口腔健康中心) Intrusion detection method and system for medical platform of Internet of things
CN117240576B (en) * 2023-10-09 2024-03-29 上海市口腔医院(上海市口腔健康中心) Intrusion detection method, system, electronic equipment and storage medium of medical platform of Internet of things

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