CN114005521B - Method and system for data communication of medical equipment - Google Patents
Method and system for data communication of medical equipment Download PDFInfo
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- CN114005521B CN114005521B CN202111264268.2A CN202111264268A CN114005521B CN 114005521 B CN114005521 B CN 114005521B CN 202111264268 A CN202111264268 A CN 202111264268A CN 114005521 B CN114005521 B CN 114005521B
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- 238000000034 method Methods 0.000 title claims abstract description 24
- 238000004891 communication Methods 0.000 title claims abstract description 15
- 238000013136 deep learning model Methods 0.000 claims description 13
- 238000012545 processing Methods 0.000 claims description 6
- 238000013527 convolutional neural network Methods 0.000 claims description 3
- 230000007787 long-term memory Effects 0.000 claims description 3
- 230000006403 short-term memory Effects 0.000 claims description 3
- 238000013135 deep learning Methods 0.000 abstract description 2
- 239000008280 blood Substances 0.000 description 34
- 210000004369 blood Anatomy 0.000 description 34
- 230000036772 blood pressure Effects 0.000 description 29
- 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 description 26
- 239000008103 glucose Substances 0.000 description 26
- 238000011161 development Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
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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
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/20—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/25—Integrating or interfacing systems involving database management systems
- G06F16/252—Integrating or interfacing systems involving database management systems between a Database Management System and a front-end application
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- G—PHYSICS
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- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
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Abstract
The invention provides a method and a system for indirectly communicating medical equipment data, which can realize the communication of the data of different medical equipment by converting image data into structured medical data through deep learning image identification by utilizing Root rights of a main App under the condition of not depending on a unified data interface, and can be used for summarizing the data among different medical equipment of different manufacturers, thereby avoiding the problem that a user needs to check the medical data to each independent App.
Description
Technical Field
The present invention relates to the field of data communication of medical devices, and in particular, to a method and a system for data communication of a medical device.
Background
With the development of economy and society, professional medical equipment is no longer exclusive to hospitals, and more portable medical equipment is brought into the home of common people. Many manufacturers have proposed various portable medical devices, such as portable blood pressure monitors, blood glucose meters, etc., for this use in the home.
Meanwhile, with the development of computing technology and network technology, many portable medical devices have network and communication functions. For example, the medical device may automatically send and record the detected medical index to the terminal of the user, and the manufacturer of each medical device also develops APPs matched with the medical device for the user to use, and the same manufacturer also often develops a plurality of APPs for different devices, so that the user can view the medical index of himself or herself or others in real time through the terminal App, and learn the physical condition of himself or others.
Although a user can view medical indexes through apps, the apps cannot communicate with each other, and in this case, data of each medical device cannot be communicated, the user has to use a plurality of apps to view data of different medical devices of different manufacturers, which is often inconvenient.
Disclosure of Invention
In order to solve the problem of data obstruction among medical equipment, the invention provides a method for indirectly communicating data of the medical equipment, which can collect the data among different medical equipment of different manufacturers without depending on a unified data interface, thereby avoiding the need of users to check the medical data to each independent App.
A method for data communication of a medical device, comprising in particular the steps of:
step 1: installing a main App in a user terminal, wherein the main App has Root rights;
Step 2: acquiring unique identifiers of one or more auxiliary apps, wherein the auxiliary apps are medical equipment data records apps developed by different manufacturers;
step 3: registering App unique identifiers of one or more accessory apps in a configuration interface of the main App;
step 4: the method for acquiring the medical data in the one or more auxiliary apps in the main App specifically comprises the following steps:
Step 4.1: a data acquisition interface of a main App is entered, a data acquisition button is arranged on the interface, a preset operation aiming at the button is received, the main App is moved back to a background operation, and one or more auxiliary Apps registered in an App configuration interface are sequentially opened;
step 4.2: sequentially capturing the opened one or more auxiliary apps, capturing the image data of the medical equipment in the auxiliary apps, and storing the image data to a default screenshot storage address;
step 4.3: killing one or more auxiliary App processes and returning to a main App interface;
Step 4.4: the main App accesses the screenshot saving address to acquire medical equipment image data in the auxiliary App;
Step 4.5: the main App sends the image data of the medical equipment in the auxiliary App to a server;
Step 4.6: a trained deep learning model is operated on the server, and medical equipment image data in the auxiliary App are identified by using the deep learning model;
step 4.7: the server generates structured medical equipment data according to the identification result;
step 4.8: the server stores the structured medical equipment data in a structured database;
Step 4.9: the main App accesses the structured database, and the structured medical equipment data is obtained from the database;
Step 5: the method comprises the steps that data processing is carried out on blood pressure data and blood glucose data obtained from a database in a main App, and processed data are obtained;
step 6: the main App is switched to a data display interface, and the processed data are displayed in the data display interface;
a system for medical device data communication, comprising:
the terminal, the server and the database are connected through a network;
the system operates by:
step 1: installing a main App in a user terminal, wherein the main App has Root rights;
Step 2: acquiring unique identifiers of one or more auxiliary apps in a system, wherein the auxiliary apps are medical equipment data records apps developed by different manufacturers;
step 3: registering App unique identifiers of one or more accessory apps in a configuration interface of the main App;
step 4: the method for acquiring the medical data in the one or more auxiliary apps in the main App specifically comprises the following steps:
Step 4.1: a data acquisition interface of a main App is entered, a data acquisition button is arranged on the interface, a preset operation aiming at the button is received, the main App is moved back to a background operation, and one or more auxiliary Apps registered in an App configuration interface are sequentially opened;
step 4.2: sequentially capturing the opened one or more auxiliary apps, capturing the image data of the medical equipment in the auxiliary apps, and storing the image data to a default screenshot storage address;
step 4.3: killing one or more auxiliary App processes and returning to a main App interface;
Step 4.4: the main App accesses the screenshot saving address to acquire medical equipment image data in the auxiliary App;
Step 4.5: the main App sends the image data of the medical equipment in the auxiliary App to a server;
Step 4.6: a trained deep learning model is operated on the server, and medical equipment image data in the auxiliary App are identified by using the deep learning model;
step 4.7: the server generates structured medical equipment data according to the identification result;
step 4.8: the server stores the structured medical equipment data in a structured database;
Step 4.9: the main App accesses the structured database, and the structured medical equipment data is obtained from the database;
step 5: data processing is carried out on the data acquired from the database in the main App, so as to obtain processed data;
step 6: the main App is switched to a data display interface, and the processed data are displayed in the data display interface;
The invention has the beneficial effects that:
according to the method and the system provided by the invention, communication among different medical equipment data can be indirectly realized, the medical data in a plurality of auxiliary apps are subjected to screenshot by utilizing Root rights of the main App, the medical data in the different auxiliary apps are extracted by utilizing image recognition capability endowed by deep learning, the data in the different medical equipment apps are unified, the medical data are stored in a database, the unification and the continuous storage of the different medical equipment data are realized, the medical data recorded in each auxiliary App are checked through the main App, the inconvenience that a user switches and checks the medical data acquired by different medical equipment among the different apps is avoided, and the experience of the user is maximally improved.
Drawings
FIG. 1 is a system configuration diagram in an embodiment of the present application;
FIG. 2 is a blood glucose data display interface of a corresponding secondary App of a medical device for measuring blood glucose;
FIG. 3 is a blood pressure data display interface of a corresponding accessory App of a medical device for measuring blood pressure;
FIG. 4 is a medical data presentation interface of the host App;
FIG. 5 is a secondary App configuration interface in App;
FIG. 6 is a csv file screenshot of structured blood glucose data;
fig. 7 is a csv file screenshot of structured blood pressure data.
Detailed Description
In order to make the invention more clear, the invention is further explained below with reference to the accompanying drawings:
as shown in fig. 1, a main App and two auxiliary apps are both installed in a terminal, wherein the main App has Root rights;
The two auxiliary apps are respectively an auxiliary App corresponding to medical equipment for measuring blood sugar content and an auxiliary App corresponding to medical equipment for measuring blood pressure;
As shown in fig. 2, the App corresponding to the medical device for measuring blood glucose displays blood glucose data measured by the user from day 10, 9 to day 10, 18;
as shown in fig. 3, the sub App corresponding to the medical device for measuring blood pressure displays blood pressure data measured by the user on a date ranging from 9 days of 10 months to 18 days of 10 months;
Acquiring unique identifiers of the two auxiliary apps in a system;
The unique identifier of the secondary App as shown in fig. 2 is 0x011010010;
the unique identifier of the secondary App as shown in fig. 3 is 0x011011101;
As shown in fig. 5, in the configuration page of the master App, the unique identifiers of one or more slave apps are registered;
Clicking the registration button in fig. 5, adding the App name of the blood glucose accessory App and its corresponding unique identifier 0x011010010 to the main App;
Clicking the registration button in fig. 5 to add the App name of the blood pressure accessory App and its corresponding unique identifier 0x011011101 to the main App;
medical data in two auxiliary apps are acquired in the main App, the method specifically comprises the following steps:
The method comprises the steps of entering a data acquisition interface of a main App, wherein a data acquisition button is arranged on the interface, clicking the data acquisition button, receiving preset operation aiming at the button, and returning the main App to a background operation;
the main App automatically opens a blood sugar auxiliary App registered in the main App, captures a blood sugar data interface shown in fig. 2, and stores the blood sugar data interface capture in a storage space with an initial address of 0x1001000111110001 in the main App;
Killing the process of the blood glucose accessory App, and closing the blood glucose accessory App;
After killing the blood glucose auxiliary App, the main App automatically opens the blood pressure auxiliary App registered in the main App, captures a blood glucose data interface as shown in fig. 3, and stores the blood glucose data interface screenshot in a storage space with a starting address of 0x1001000111110001 in the main App;
Killing the process of the blood pressure accessory App, and closing the blood pressure accessory App;
the main App sends the blood glucose data screenshot and the blood pressure data screenshot which are stored in a storage space with the initial address of 0x1001000111110001 to a server;
The server receives blood glucose data image data and blood pressure data screenshot data sent from a main App;
The server is operated with a trained deep learning model, and the deep learning model is a convolutional neural network model or a long-term and short-term memory network model;
Identifying the received blood glucose image data and blood pressure image data using the deep learning model;
the server generates structured medical equipment data according to the identification result;
As shown in fig. 6, after identifying the blood glucose image data, the server generates structured blood glucose data, where the structured blood glucose data is a csv file, and the file structure is shown in fig. 6;
As shown in fig. 7, after identifying the blood pressure image data, the server generates structured blood pressure data, where the structured blood pressure data is a csv file, and the file structure is shown in fig. 7;
The server stores the structured blood glucose data and blood pressure data shown in fig. 6 and 7 in a MySQL database, and each csv file corresponds to a separate table in the database;
setting the name of the database as HEALTHDATA;
The table BS is set as a table for recording blood glucose data;
setting a table BP as a table for recording blood pressure data;
The Schema of the database is specifically set according to the following codes: create Database HealthData Create Table BS ('date' varchar (20), 'measurement value' varchar (20), 'reference value' varchar (20)); create Table BP ('date' varchar (20), 'measurement value' varchar (20), 'reference value' varchar (20));
Inserting structured blood glucose data and blood pressure data in csv files as shown in fig. 6 and 7 into tables BS and BP below HEALTHDATA database, respectively;
The main App accesses HEALTHDATA database in MySQL, obtains structured blood glucose data and blood pressure data from tables BS and BP, and returns the data to the main App;
the code for acquiring the blood glucose data and the blood pressure data is as follows: use HealthData Select from BS; Select from BP;
The method comprises the steps that data processing is carried out on blood pressure data and blood glucose data acquired from a database in a main App, wherein the processing comprises the steps of removing reference value columns in tables BS and BP;
Combining blood sugar and blood pressure data in a main App to obtain combined blood sugar and blood pressure data;
the combined blood sugar and blood pressure data structure is shown in fig. 4, and the combined data comprises date, blood sugar value and blood pressure value;
the data display interface in the main App displays the blood glucose and blood pressure data after being combined in the main App as shown in fig. 4.
Claims (6)
1. A method for data communication of a medical device, comprising in particular the steps of:
step 1: installing a main App in a user terminal, wherein the main App has Root rights;
Step 2: acquiring unique identifiers of one or more auxiliary apps in a system, wherein the auxiliary apps are medical equipment data records apps developed by different manufacturers;
Step 3: registering unique identifiers of one or more auxiliary apps in a configuration interface of the main App;
Step 4: the method comprises the steps of acquiring medical data in one or more auxiliary apps from a main App, wherein the medical data comprise:
Step 4.1: a data acquisition interface of a main App is entered, a data acquisition button is arranged on the interface, a preset operation aiming at the button is received, the main App is moved back to a background operation, and one or more auxiliary Apps registered in an App configuration interface are sequentially opened;
step 4.2: sequentially capturing the opened one or more auxiliary apps, capturing the image data of the medical equipment in the auxiliary apps, and storing the image data to a default screenshot storage address;
step 4.3: killing one or more auxiliary App processes and returning to a main App interface;
Step 4.4: the main App accesses the screenshot saving address to acquire medical equipment image data in the auxiliary App;
Step 4.5: the main App sends the image data of the medical equipment in the auxiliary App to a server;
Step 4.6: a trained deep learning model is operated on the server, and medical equipment image data in the auxiliary App are identified by using the deep learning model;
Step 4.7: the server generates structured medical equipment data according to the identification result, wherein the format of the structured medical equipment data is csv file;
step 4.8: the server stores the structured medical equipment data in a structured database;
Step 4.9: the main App accesses the structured database, and the structured medical equipment data is obtained from the database;
Step 5: processing the acquired medical data in one or more auxiliary apps in the main App to obtain processed data;
Step 6: the main App switches to a data display interface, and medical data in the acquired one or more auxiliary apps are displayed in the data display interface.
2. A method for medical device data communication as claimed in claim 1, wherein:
The structured database is MySQL, and the Schema of the database is specifically:
the database creates a separate table for each secondary App to store data from the secondary apps.
3. A method for medical device data communication as claimed in claim 2, wherein:
the deep learning model is a convolutional neural network model or a long-term and short-term memory network model.
4. A system for data communication of medical devices, characterized by:
The system comprises a terminal, a server and a database, wherein the terminal, the server and the database are connected through a network;
the system operates by:
step 1: installing a main App in a user terminal, wherein the main App has Root rights;
Step 2: acquiring unique identifiers of one or more auxiliary apps in a system, wherein the auxiliary apps are medical equipment data records apps developed by different manufacturers;
Step 3: registering unique identifiers of one or more auxiliary apps in a configuration interface of the main App;
Step 4: the method comprises the steps of acquiring medical data in one or more auxiliary apps from a main App, wherein the medical data comprise:
Step 4.1: a data acquisition interface of a main App is entered, a data acquisition button is arranged on the interface, a preset operation aiming at the button is received, the main App is moved back to a background operation, and one or more auxiliary Apps registered in an App configuration interface are sequentially opened;
step 4.2: sequentially capturing the opened one or more auxiliary apps, capturing the image data of the medical equipment in the auxiliary apps, and storing the image data to a default screenshot storage address;
step 4.3: killing one or more auxiliary App processes and returning to a main App interface;
Step 4.4: the main App accesses the screenshot saving address to acquire medical equipment image data in the auxiliary App;
Step 4.5: the main App sends the image data of the medical equipment in the auxiliary App to a server;
Step 4.6: a trained deep learning model is operated on the server, and medical equipment image data in the auxiliary App are identified by using the deep learning model;
Step 4.7: the server generates structured medical equipment data according to the identification result, wherein the format of the structured medical equipment data is csv file;
step 4.8: the server stores the structured medical equipment data in a structured database;
Step 4.9: the main App accesses the structured database, and the structured medical equipment data is obtained from the database;
Step 5: processing the acquired medical data in one or more auxiliary apps in the main App to obtain processed data;
Step 6: the main App switches to a data display interface, and medical data in the acquired one or more auxiliary apps are displayed in the data display interface.
5. A system for medical device data communication as defined in claim 4, wherein:
The structured database is MySQL, and the Schema of the database is specifically:
the database creates a separate table for each secondary App to store data from the secondary apps.
6. A system for medical device data communication as defined in claim 5, wherein:
the deep learning model is a convolutional neural network model or a long-term and short-term memory network model.
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| CN104834855A (en) * | 2015-04-20 | 2015-08-12 | 北京奇虎科技有限公司 | System data acquiring method and apparatus, and mobile terminal |
| CN105930343A (en) * | 2016-04-03 | 2016-09-07 | 北京设集约科技有限公司 | Method and system for quoting favorited APP content |
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| US20020007287A1 (en) * | 1999-12-16 | 2002-01-17 | Dietmar Straube | System and method for electronic archiving and retrieval of medical documents |
| CN104902019B (en) * | 2015-05-20 | 2016-11-16 | 腾讯科技（深圳）有限公司 | A kind of application method, server and terminal |
| CN106375696B (en) * | 2016-09-30 | 2019-05-24 | 腾讯科技（深圳）有限公司 | A kind of film recording method and device |
| CN108010562A (en) * | 2017-10-10 | 2018-05-08 | 北京妙医佳信息技术有限公司 | A kind of health data interactive system |
| CN112565512A (en) * | 2020-12-14 | 2021-03-26 | 华东师范大学 | Method and system for acquiring data through screenshot and recording between Android applications |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN104834855A (en) * | 2015-04-20 | 2015-08-12 | 北京奇虎科技有限公司 | System data acquiring method and apparatus, and mobile terminal |
| CN105930343A (en) * | 2016-04-03 | 2016-09-07 | 北京设集约科技有限公司 | Method and system for quoting favorited APP content |
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