CN114373555A - Multi-terminal data fusion analysis method and system and computer equipment - Google Patents
Multi-terminal data fusion analysis method and system and computer equipment Download PDFInfo
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Abstract
The invention provides a multi-terminal data fusion analysis method, which comprises the following steps: the method comprises the steps that a device obtains a first data packet and/or a second data packet, wherein the first data packet comprises a patient ID, first event information, a device SN and a first import ID, and the second data packet comprises the patient ID, second event information, a second import ID and medical care information; the local equipment judges whether the network is connected currently; when the local equipment is networked, inquiring whether historical information associated with the patient ID exists in the cloud server or not according to the patient ID; when historical information associated with the patient ID exists in the cloud server, the local device downloads the historical information from the cloud server and uploads the first data packet and/or the second data packet to the cloud server; the local device acquires a sleep report generated by the cloud server according to the first data packet and/or the second data packet. The invention also provides a multi-terminal data fusion analysis system and computer equipment.
Description
Technical Field
The invention relates to the field of medical equipment, in particular to a multi-terminal data fusion analysis method, a multi-terminal data fusion analysis system and computer equipment.
Background
In the rapid development stage of internet medical treatment, the technical scheme for solving the business scene in the industry is more traditional, and a single computer is used for data display and data analysis. Because the quantity of the sleep preliminary screening equipment is huge, the sleep preliminary screening equipment is basically single-machine non-networking software, the data of the screening equipment is imported into a computer, the data and the reports can only be checked locally, data display and data analysis can only be carried out on one computer, the same kind of data of the same person cannot be stored in a cloud and non-networking mode, the data storage, data analysis and report checking are carried out only on the computer for importing the data in a single mode, and the use of other terminals cannot be expanded, so that the daily use efficiency and the data integrity are reduced.
The existing solution is to perform data analysis and report generation after data is imported locally, which is not enough in convenience and use, and after analysis software is installed in a computer, data import and data analysis and check can only be performed on the computer through the software, so that multiple persons can not share and store the data in a centralized manner. Moreover, under the mode that the single machine is not networked, sleep screening data cannot be conveniently checked through a browser, the problem of non-networked storage of the data in the mode is solved, the problem that the data cannot be retrieved when the machine is damaged or a disk is abnormal is solved, difficulty and inconvenience are brought when the data is integrated with healthy big data, a plurality of information islands are caused by the data of a plurality of doctors and patients, and the requirements of business cannot be met under the current internet medical treatment and big data trends.
Therefore, how to fuse the local data and the cloud data to obtain a more accurate sleep report is an urgent problem to be solved.
Disclosure of Invention
The invention provides an end data fusion analysis method, a multi-end data fusion analysis system and computer equipment, which can fuse local data and cloud data under the condition of networking to obtain a more accurate sleep report.
In a first aspect, an embodiment of the present invention provides a multi-end data fusion analysis method, where the multi-end data fusion analysis method includes:
the method comprises the steps that a local device acquires a first data packet and/or a second data packet, wherein the first data packet comprises a patient ID, first event information, a device SN and a first import ID, the first event information is a plurality of respiratory events monitored by a patient through a sleep monitoring device, the device SN is the number of the sleep monitoring device, the first import ID is a main key generated by the local device according to the time of acquiring the first event information, the second data packet comprises the patient ID, second event information, a second import ID and medical care information, the second event information is a plurality of respiratory events of the patient recorded by medical care personnel, and the second import ID is a main key generated by the local device according to the time of acquiring the second event information;
the local equipment judges whether the network is connected currently;
when the local equipment is networked, inquiring whether historical information associated with the patient ID exists in the cloud server or not according to the patient ID;
when historical information associated with the patient ID exists in the cloud server, the local device downloads the historical information from the cloud server and uploads the first data packet and/or the second data packet to the cloud server;
the local device acquires a sleep report generated by the cloud server according to the first data packet and/or the second data packet.
In a second aspect, an embodiment of the present invention provides a multi-end data fusion analysis system, where the multi-end data fusion analysis system includes:
a data acquisition module: the sleep monitoring system comprises a first data packet and/or a second data packet, wherein the first data packet comprises a patient ID, first event information, a device SN and a first import ID, the first event information is a plurality of respiratory events monitored by a patient through a sleep monitoring device, the device SN is the number of the sleep monitoring device, the first import ID is a main key generated by a local device according to the time for acquiring the first event information, the second data packet comprises the patient ID, second event information, a second import ID and medical care information, the second event information is a plurality of respiratory events of the patient recorded by medical care personnel, and the second import ID is a main key generated by the local device according to the time for acquiring the second event information;
a network detection module: the system is used for judging whether the local equipment is currently networked or not;
a communication module: when the local equipment is networked, whether historical information associated with the patient ID exists in the cloud server or not is inquired according to the patient ID; when historical information associated with the patient ID exists in the cloud server, the local device downloads the historical information from the cloud server and uploads the first data packet and/or the second data packet to the cloud server; the local device acquires a sleep report generated by the cloud server according to the first data packet and/or the second data packet.
In a third aspect, an embodiment of the present invention provides a computer device, where the computer device includes:
a memory for storing program instructions; and
and the processor is used for executing the program instructions to enable the computer equipment to realize the multi-terminal data fusion analysis method.
According to the multi-terminal data fusion analysis method, data between a patient and medical care can interact in real time under the networking condition, the data adopt the same set of algorithm under the networking and non-networking conditions, the data can be accurately and unmistakably analyzed under any scene, a screening report is formed, a sleep analysis report is formed, big data of the patient can be rapidly analyzed, the sleep analysis report can be obtained without networking under the non-networking condition, cloud server data can be pulled under the networking condition to perform data analysis to generate a report or preview of the cloud server report on local equipment is directly checked, data consistency is ensured, and medical care personnel can use the same previewed data in different places. When the method is networked, the acquired sleep screening data can be synchronized to a cloud server for permanent data storage, the cloud server can also carry out data statistics, analysis and sleep report generation remotely according to the uploaded sleep screening data, the sleep report information and detailed data are pushed to a doctor mobile port or a local equipment end background bound by the sleep screening equipment, and medical staff can check the data and the report through mobile terminals such as APP, WEB, small programs and the like; the doctor looks over patient's data through local equipment end or mobile terminal, and after the aassessment feedback, the high in the clouds pushes the sleep report that the doctor signed up for the mobile terminal that has bound patient ID, and the patient can directly look over sleep report and the sleep screening information that corresponds through APP or applet etc. of installing on the mobile device. The local data and the cloud data can be fused quickly, so that the sleep screening data is guaranteed to include all necessary information, a patient can obtain a sleep report quickly and timely, and the requirements of the patient on internet medical treatment and big data services are met.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below. It is to be understood that the drawings in the following description are merely exemplary of the invention and that other drawings may be derived from the structure shown in the drawings by those skilled in the art without the exercise of inventive faculty.
Fig. 1 is a flowchart of a multi-terminal data fusion analysis method according to a first embodiment of the present invention.
Fig. 2 is a sub-flowchart of a multi-terminal data fusion analysis method according to a second embodiment of the present invention.
Fig. 3 is a sub-flowchart of a multi-end data fusion analysis method according to a third embodiment of the present invention.
Fig. 4 is a schematic diagram of an internal structure of a multi-terminal data fusion analysis system according to a first embodiment of the present invention.
Fig. 5 is a schematic diagram of an internal structure of a computer device according to an embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims of the present application and in the drawings described above, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be noted that the description relating to "first", "second", etc. in the present invention is for descriptive purposes only and is not to be construed as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. In addition, technical solutions between various embodiments may be combined with each other, but must be realized by a person skilled in the art, and when the technical solutions are contradictory or cannot be realized, such a combination should not be considered to exist, and is not within the protection scope of the present invention.
Please refer to fig. 1, which is a flowchart illustrating a multi-terminal data fusion analysis method according to an embodiment of the present invention. The multi-terminal data fusion analysis method provided by the embodiment of the invention specifically comprises the following steps.
Step S101, a local device acquires a first data packet and/or a second data packet, wherein the first data packet includes a patient ID, first event information, a device SN and a first import ID, the first event information is a plurality of respiratory events monitored by the patient using a sleep monitoring device, the device SN is a serial number of the sleep monitoring device, the first import ID is a main key generated by the local device according to the time of acquiring the first event information, the second data packet includes the patient ID, second event information, a second import ID and medical care information, the second event information is a plurality of respiratory events of the patient recorded by the medical care personnel, and the second import ID is a main key generated by the local device according to the time of acquiring the second event information.
Specifically, respiratory events include obstructive apneas, central apneas, mixed apneas, hypopneas, flow restrictions, periodic breaths, respiratory effort related arousals, cheyne-stokes breaths, oxygen deprivation, and/or snoring. The sleep monitoring device comprises a blood oxygen monitoring device and a sleep prescreening device. Each sleep prescreening device has a unique device SN.
The first event information is various respiratory events of the patient monitored by the blood oxygen monitoring device and the sleep prescreening device in the process of using the patient, and the second event information is various respiratory events recorded by medical staff in the process of diagnosing the patient. The sleep preliminary screening equipment is mainly applied to scenes such as families outside a sleep center, the sleep signs of a patient are collected through the biosensor, the sleep state and the sleep quality of the patient are analyzed through signal acquisition and processing, the evaluation of respiratory events such as sleep respiratory disorder and sleep apnea is completed, and the screening purpose is achieved. The local device may be a desktop or laptop computer, etc.
In this embodiment, the sleep prescreening analysis software is installed in the local computer, and the sleep data that the sleep prescreening appearance was gathered can be looked over to this sleep prescreening analysis software to show with the wave form, in order to reach the purpose of data analysis, show, thereby the sleep state of analysis patient/patient (the people that have the sleep monitoring demand), carry out holistic data analysis, report generation, data storage etc. can also combine the high in the clouds system, save in local, and the high in the clouds data sharing.
Specifically, the local device is convenient for the sleep prescreening device to be bound with the patient, is provided with a device binding center, binds the known device SN and the device SN automatically identified by accessing the local device through the USB with the patient ID, directly binds the sleep prescreening device with the entered patient, is also convenient for the sleep prescreening device to be bound with the patient who is not entered, realizes directly binding after the information is rapidly entered, and simplifies the operation flow.
Blood oxygen monitoring facilities passes through the bluetooth and transmits to the sleep preliminary screening equipment in, and local equipment passes through the USB data line and is connected with the sleep preliminary screening equipment, acquires the first event information of the user of monitoring in the sleep preliminary screening equipment, and according to the time of the sleep information of transmission user generate first leading-in ID, and patient ID and equipment SN just constitute first data package in addition.
Medical personnel directly input various respiratory events recorded in the process of diagnosing the patient into local equipment, the local equipment generates a second import ID according to the time of transmitting the sleep information of the patient filled by the medical personnel, and the patient ID and the medical information form a second data packet. Specifically, local equipment carries out the accuracy matching in order to carry out patient basic information and sleep screening data record, for medical personnel increase a patient management center, carries out information entry to all users or the patient that use or will use the sleep preliminary screening, types detailed information and carries out accurate management, can in time match patient information when the preliminary screening equipment is bound, can carry out the accurate matching according to equipment SN when the screening data that sleeps upload. Patient information in the list contains patient information that medical personnel entered locally, also can synchronize this doctor at the patient information that the high in the clouds was maintained, guarantees that medical personnel's networking, non-networking can both manage patient information. More specifically, the patient management center provides newly-added, edited and unbound equipment, sleep screening records and sleep analysis records, and improves accurate query efficiency for medical personnel to manage patient information and sleep screening records.
After the sleep prescreening device is connected into a computer through a USB, the local device automatically identifies SN codes of the device and bound patient information, unbound patients can directly select or newly-built patients to bind, screening data recorded by the sleep prescreening device is imported after information is confirmed, meanwhile, import progress is displayed on an interface of the local device in real time, and after the import is successful, the prompt is given to continue importing data of other sleep prescreening devices or the data is directly jumped to for analysis and checking. When the import of the data is abnormal, the import is cancelled, and the local equipment interface simultaneously outputs a prompt of an import abnormity prompt message. Generally, the sleep screening data can be re-imported by plugging and unplugging the USB or after the equipment is powered off and restarted.
Furthermore, when the sleep screening device uploads the sleep screening data, the sleep screening data exist in an SD form, the local device end directly reads a data file in a preset format to perform data comparison such as CRC and the like, and then uploads and analyzes the sleep screening data, after the sleep screening data are stored in the local device, when a used computer is networked, the system can automatically upload the screening data to a cloud server for storage through the network, the import speed and the integrity of the data are guaranteed, and medical workers can also read the data simultaneously after logging in own accounts by other computers, so that better services are provided for patients.
In the present embodiment, the time unit of the time when the first event information is acquired and the time when the second event information is acquired is seconds.
Step S102, the local device judges whether the network is connected currently.
And step S103, when the local equipment is networked, inquiring whether historical information associated with the patient ID exists in the cloud server according to the patient ID.
And step S104, when history information associated with the patient ID exists in the cloud server, the local device downloads the history information from the cloud server and uploads the first data packet and/or the second data packet to the cloud server.
Step S105, the local device obtains a sleep report generated by the cloud server according to the first data packet and/or the second data packet.
In the above embodiment, the method is used in combination of multiple devices, such as offline analysis/report generation + cloud data persistence storage, local uploading data + cloud statistical analysis/report generation + mobile terminal usage, data fusion is performed by using patient ID through API between local and cloud terminals, the sleep screening data are encrypted by an AES encryption algorithm in the modes of SN, import ID, time and the like, the encrypted verification head carries out signature verification by an MD5 algorithm to synchronize data, the fusion mode of cloud and local data can be selected according to API (application programming interface) to be synchronized from the cloud to the local or from the local to the cloud, the local synchronization is completed in a covering mode to the cloud, the cloud is synchronized to the local and can be covered locally or can be combined according to data time nodes, the original data backup of the preset period is reserved at the cloud and the local during each operation data fusion, and the backup data can be retrieved for restoration according to the synchronous patient ID within the preset time.
The storage of the sleep screening data generates a data table according to the import ID during each import, records the patient ID, the equipment SN, the import ID and the unique main key (MsgId) generated according to the time second, records the sleep screening data collected according to the second unit independently, the sleep screening data fused with the local cloud end only needs to start a synchronous task thread according to the import ID in the background, the synchronous task encrypts and signs the data according to the storage rule second unit, the recorded value difference of different ends is compared with the cloud end patient ID, the equipment SN, the import ID, the MsgId and the like, and the data of the other end is fused when the difference data exists. The form of looking over storage in the high in the clouds server is diversified, and medical personnel pass through mobile device and look over patient's sleep screening data and the sleep report that reaches the high in the clouds server to can give the patient through high in the clouds server propelling movement with the aassessment feedback, the patient can directly look over the sleep report of oneself by modes such as mobile terminal, has increased user's experience sense and internet informationization, also makes things convenient for the doctor to swiftly handle data and feedback information and give the patient.
Please refer to fig. 2, which is a multi-terminal data fusion analysis method according to a second embodiment of the present invention. The difference between the multi-port data fusion analysis method provided in the second embodiment and the multi-port data fusion analysis method provided in the first embodiment is that the first data packet and the second data packet further include a sleep report, and after the local device acquires the first data packet and/or the second data packet, the multi-port data fusion analysis method provided in the second embodiment further includes the following steps.
In step S201, the local device acquires a report generation instruction.
Step S202, the local device generates a sleep report according to the first data packet and/or the second data packet.
In this embodiment, the local device performs waveform chart display on the imported sleep screening data, such as snore, nasal flow, effort to breathe, blood oxygen, pulse rate, sleeping posture, and the like.
The local device displays the acquired respiratory sleep event information such as Obstructive Apnea (OA), Central Apnea (CA), Mixed Apnea (MA), hypopnea (H), Flow Limitation (FL), Periodic Respiration (PR), Respiratory Effort Related Arousal (RERA), stale-inspired respiration (CSR), Oxygen Reduction (OR), snore (S) and the like, and clicking the corresponding event record can directly click on a time node of the data oscillogram. Corresponding events can be manually added according to analysis for storage, and a sleep analysis report is regenerated.
After the sleep preliminary screening data of the local equipment is successfully imported, the local equipment end can automatically perform algorithm analysis according to the sleep screening data to generate first sleep report data, report data can be generated again subsequently, report information is displayed, a doctor can give a monitoring conclusion and issue a report according to sleep statistical data in the report, and complete report information can be previewed and printed. After the local equipment generates the report, the report data and the labeling information on the waveform can be stored in the cloud server through network synchronization, and after the medical personnel confirm the accuracy and the specialty of the sleep report, the cloud server pushes the sleep report to the mobile terminal bound with the patient for the patient to check.
Please refer to fig. 3, which is a multi-terminal data fusion analysis method according to a third embodiment of the present invention. The difference between the multi-terminal data fusion analysis method provided in the third embodiment and the multi-terminal data fusion analysis method provided in the first embodiment is that before the local device acquires the sleep report generated by the cloud server according to the first data packet and/or the second data packet, the multi-terminal data fusion analysis method provided in the third embodiment further includes the following steps.
In step S301, the cloud server determines whether the first data packet and/or the second data packet includes a sleep report.
Step S302, when the first data packet and/or the second data packet does not include the sleep report, the cloud server generates the sleep report according to the first data packet and/or the second data packet.
In step S303, when the first data packet and/or the second data packet includes the sleep report, the cloud server does not generate the sleep report.
The difference between the multi-terminal data fusion analysis method provided by the fourth embodiment of the present invention and the multi-terminal data fusion analysis method provided by the first embodiment is that the multi-terminal data fusion analysis method provided by the fourth embodiment further includes that the cloud server sends the sleep report to the mobile device bound to the patient ID.
The difference between the multi-port data fusion analysis method provided in the fifth embodiment of the present invention and the multi-port data fusion analysis method provided in the first embodiment is that the multi-port data fusion analysis method provided in the fifth embodiment further includes that before uploading the first data packet and/or the second data packet to the cloud server, the local device encrypts the first data packet and/or the second data packet by using an AES encryption algorithm.
The embodiment can meet the requirement of not networking or independent use in the hospital in the rapid development stage of internet medical treatment, and can also meet the requirement of networking for remote data synchronization in a mechanism where internet medical treatment is comprehensively promoted. Furthermore, the scheme can meet the application requirements of different service scenes for using the non-networked single machine and synchronizing the cloud service, can ensure the advance of the technical architecture, and improves the competitiveness in the similar products.
Please refer to fig. 4, which is a schematic diagram of an internal structure of a multi-terminal data fusion analysis system according to a first embodiment of the present invention. The multi-terminal data fusion analysis system 400 includes: a data acquisition module 401, a network detection module 402 and a communication module 403.
The data acquisition module 401: the sleep monitoring system comprises a first data packet and/or a second data packet, wherein the first data packet comprises a patient ID, first event information, a device SN and a first import ID, the first event information is a plurality of respiratory events monitored by a patient through a sleep monitoring device, the device SN is the number of the sleep monitoring device, the first import ID is a main key generated by a local device according to the time of acquiring the first event information, the second data packet comprises the patient ID, second event information, a second import ID and medical care information, the second event information is a plurality of respiratory events of the patient recorded by medical care personnel, and the second import ID is a main key generated by the local device according to the time of acquiring the second event information.
The network detection module 402: for determining whether the local device is currently networked.
The communication module 403: and when the local equipment is networked, inquiring whether historical information associated with the patient ID exists in the cloud server according to the patient ID. When the history information associated with the patient ID exists in the cloud server, the local device downloads the history information from the cloud server and uploads the first data packet and/or the second data packet to the cloud server. The local device acquires a sleep report generated by the cloud server according to the first data packet and/or the second data packet.
The invention also provides a computer device 900, the computer device 900 comprising at least a memory 901 and a processor 902. The memory 901 is used for storing program instructions of the multi-terminal data fusion analysis method. The processor 902 is configured to execute program instructions to cause a computer device to implement the multi-terminal data fusion analysis method described above. Please refer to fig. 5, which is a schematic diagram illustrating an internal structure of a computer apparatus 900 according to an embodiment of the present invention.
The memory 901 includes at least one type of computer-readable storage medium, which includes flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a magnetic memory, a magnetic disk, an optical disk, and the like. The memory 901 may in some embodiments be an internal storage unit of the computer device 900, such as a hard disk of the computer device 900. The memory 901 may also be an external storage device of the computer device 900 in other embodiments, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital Card (SD), a Flash memory Card (Flash Card), etc., provided on the computer device 900. Further, the memory 901 may also include both internal storage units and external storage devices of the computer device 900. The memory 901 may be used not only to store application software installed in the computer device 900 and various types of data, such as program instructions of the multi-port data fusion analysis method, etc., but also to temporarily store data that has been output or is to be output, such as data generated by execution of the multi-port data fusion analysis method, etc.
Further, the computer device 900 may further include a bus 903 which may be a Peripheral Component Interconnect (PCI) standard bus or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one thick line is shown in FIG. 5, but this is not intended to represent only one bus or type of bus.
Further, computer device 900 may also include a display component 904. The display component 904 may be an LED (Light Emitting Diode) display, a liquid crystal display, a touch-sensitive liquid crystal display, an OLED (Organic Light Emitting Diode) touch panel, or the like. The display component 904 may also be referred to as a display device or display unit, among others, for displaying information processed in the computer device 900 and for displaying a visualized patient interface.
Further, the computer device 900 may also include a communication component 905, and the communication component 905 may optionally include a wired communication component and/or a wireless communication component (e.g., a WI-FI communication component, a bluetooth communication component, etc.), typically used for establishing a communication connection between the computer device 900 and other computer devices.
While FIG. 5 illustrates only a computer device 900 having components 901 and 905 and program instructions for implementing a multi-terminal data fusion analysis method, those skilled in the art will appreciate that the architecture illustrated in FIG. 5 is not intended to be limiting of computer device 900, and may include fewer or more components than those illustrated, or may combine certain components, or a different arrangement of components. Since the computer device 900 adopts all technical solutions of all the embodiments described above, at least all the advantages brought by the technical solutions of the embodiments described above are achieved, and are not described herein again.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product.
The multi-terminal data fusion analysis method comprises one or more program instructions. The procedures or functions according to embodiments of the invention are generated in whole or in part when the program instructions are loaded and executed on a device. The apparatus may be a general purpose computer, a special purpose computer, a network of computers, or other programmable device. The program instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another, for example, from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., coaxial cable, fiber optics, digital patient line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that a computer can store or a data storage device, such as a server, a data center, etc., that is integrated with one or more available media. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above described systems, apparatuses and units may refer to the corresponding processes in the above described method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the embodiment of the multi-terminal data fusion analysis method described above is merely illustrative, for example, the division of the unit is only one logic function division, and there may be other division manners in actual implementation, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a computer-readable storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method of the embodiments of the present application. And the aforementioned computer-readable storage media comprise: a U disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program instructions.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, insofar as these modifications and variations of the invention fall within the scope of the claims of the invention and their equivalents, the invention is intended to include these modifications and variations.
The above-mentioned embodiments are only examples of the present invention, which should not be construed as limiting the scope of the present invention, and therefore, the present invention is not limited by the claims.
Claims (10)
1. A multi-terminal data fusion analysis method is characterized by comprising the following steps:
the method comprises the steps that a local device acquires a first data packet and/or a second data packet, wherein the first data packet comprises a patient ID, first event information, a device SN and a first import ID, the first event information is a plurality of respiratory events monitored by a patient through a sleep monitoring device, the device SN is the serial number of the sleep monitoring device, the first import ID is a main key generated by the local device according to the time of acquiring the first event information, the second data packet comprises the patient ID, second event information, a second import ID and medical care information, the second event information is a plurality of respiratory events of the patient recorded by medical care personnel, and the second import ID is a main key generated by the local device according to the time of acquiring the second event information;
the local equipment judges whether the network is connected currently;
when the local equipment is networked, inquiring whether historical information associated with the patient ID exists in a cloud server according to the patient ID;
when history information associated with the patient ID exists in the cloud server, the local device downloads the history information from the cloud server and uploads the first data packet and/or the second data packet to the cloud server;
the local device acquires a sleep report generated by the cloud server according to the first data packet and/or the second data packet.
2. The multi-terminal data fusion analysis method of claim 1, wherein the respiratory events include obstructive apnea, central apnea, mixed apnea, hypopnea, flow limitation, periodic breathing, respiratory effort related arousals, cheyne-stokes breathing, oxygen deprivation, and/or snoring.
3. The multi-port data fusion analysis method according to claim 1, wherein the first data packet and the second data packet further include a sleep report, and after the local device acquires the first data packet and/or the second data packet, the method further includes:
the local equipment acquires a report generating instruction;
the local device generates the sleep report according to the first data packet and/or the second data packet.
4. The multi-end data fusion analysis method according to claim 3, before the local device acquires the sleep report generated by the cloud server according to the first data packet and/or the second data packet, further comprising:
the cloud server judges whether the first data packet and/or the second data packet comprises the sleep report or not;
when the first data packet and/or the second data packet do not comprise the sleep report, the cloud server generates the sleep report according to the first data packet and/or the second data; or
When the first data packet and/or the second data packet comprise the sleep report, the cloud server does not generate the sleep report any more.
5. The multi-end data fusion analysis method of claim 1, wherein after the local device obtains the sleep report generated by the cloud server according to the first data packet and/or the second data packet, the method further comprises:
the cloud server sends the sleep report to a mobile device bound to a patient ID.
6. The multi-terminal data fusion analysis method of claim 1, wherein the sleep monitoring device comprises a blood oxygen monitoring device and a sleep prescreening device.
7. The multi-end data fusion analysis method of claim 1, wherein the local device further encrypts the first data packet and/or the second data packet with an AES encryption algorithm before uploading the first data packet and/or the second data packet to the cloud server.
8. The multi-terminal data fusion analysis method according to claim 1, wherein a time unit of the time at which the first event information is acquired and the time at which the second event information is acquired is a second.
9. A multi-terminal data fusion analysis system, comprising:
a data acquisition module: the system comprises a first data packet and/or a second data packet, wherein the first data packet comprises a patient ID, first event information, a device SN and a first import ID, the first event information is a plurality of respiratory events monitored by a patient through a sleep monitoring device, the device SN is the serial number of the sleep monitoring device, the first import ID is a main key generated by the local device according to the time of acquiring the first event information, the second data packet comprises the patient ID, second event information, a second import ID and medical care information, the second event information is a plurality of respiratory events of the patient recorded by medical care personnel, and the second import ID is a main key generated by the local device according to the time of acquiring the second event information;
a network detection module: the local device is used for judging whether the local device is currently networked or not;
a communication module: when the local equipment is networked, inquiring whether historical information associated with the patient ID exists in a cloud server according to the patient ID; when history information associated with the patient ID exists in the cloud server, the local device downloads the history information from the cloud server and uploads the first data packet and/or the second data packet to the cloud server; the local device acquires a sleep report generated by the cloud server according to the first data packet and/or the second data packet.
10. A computer device, characterized in that the computer device comprises:
a memory for storing program instructions; and
a processor for executing the program instructions to cause the computer device to implement the multi-terminal data fusion analysis method according to any one of claims 1 to 8.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115361399A (en) * | 2022-10-24 | 2022-11-18 | 中国水利水电第七工程局有限公司 | Multi-terminal data synchronization method, device and system |
| CN116319718A (en) * | 2023-03-10 | 2023-06-23 | 北京振中电子技术有限公司 | Cloud data storage processing method, system, equipment and medium |
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2021
- 2021-12-27 CN CN202111618131.2A patent/CN114373555A/en active Pending
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115361399A (en) * | 2022-10-24 | 2022-11-18 | 中国水利水电第七工程局有限公司 | Multi-terminal data synchronization method, device and system |
| CN115361399B (en) * | 2022-10-24 | 2023-01-24 | 中国水利水电第七工程局有限公司 | Multi-terminal data synchronization method, device and system |
| CN116319718A (en) * | 2023-03-10 | 2023-06-23 | 北京振中电子技术有限公司 | Cloud data storage processing method, system, equipment and medium |
| CN116319718B (en) * | 2023-03-10 | 2023-12-12 | 北京振中电子技术有限公司 | Cloud data storage processing method, system, equipment and medium |
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