CN116779104A - Intelligent medical response method based on big data and intelligent medical cloud computing system - Google Patents
Intelligent medical response method based on big data and intelligent medical cloud computing system Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 25
- 230000004044 response Effects 0.000 title claims abstract description 16
- 235000013305 food Nutrition 0.000 claims abstract description 177
- 239000008280 blood Substances 0.000 claims abstract description 76
- 210000004369 blood Anatomy 0.000 claims abstract description 76
- 230000005540 biological transmission Effects 0.000 claims abstract description 62
- 230000037406 food intake Effects 0.000 claims abstract description 45
- 235000012631 food intake Nutrition 0.000 claims abstract description 45
- 230000036772 blood pressure Effects 0.000 claims abstract description 38
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- 239000011159 matrix material Substances 0.000 claims description 66
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- 238000011084 recovery Methods 0.000 claims description 10
- 150000002632 lipids Chemical class 0.000 claims description 9
- WQZGKKKJIJFFOK-GASJEMHNSA-N Glucose Natural products OC[C@H]1OC(O)[C@H](O)[C@@H](O)[C@@H]1O WQZGKKKJIJFFOK-GASJEMHNSA-N 0.000 claims description 8
- 238000004891 communication Methods 0.000 claims description 8
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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
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/60—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
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- G—PHYSICS
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L69/00—Network arrangements, protocols or services independent of the application payload and not provided for in the other groups of this subclass
- H04L69/30—Definitions, standards or architectural aspects of layered protocol stacks
- H04L69/32—Architecture of open systems interconnection [OSI] 7-layer type protocol stacks, e.g. the interfaces between the data link level and the physical level
- H04L69/322—Intralayer communication protocols among peer entities or protocol data unit [PDU] definitions
- H04L69/329—Intralayer communication protocols among peer entities or protocol data unit [PDU] definitions in the application layer [OSI layer 7]
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Abstract
The invention discloses an intelligent medical response method based on big data, which comprises the following steps: step one: deploying a doctor-patient APP at a session layer, constructing a rehabilitation regulation platform at a transmission layer, and accessing detection equipment at a physical layer, wherein the method comprises the following steps: the doctor sets the rehabilitation stage, the food contraindication, the blood sugar blood pressure and the blood fat parameter range of the patient to the transmission layer, and the patient looks over various information stored in the transmission layer, and the third step is that: the doctor sets physical sign parameters to the transmission layer at the session layer, and corresponds to food intake and contraindications at different rehabilitation stages, and the step four: the physical sign information is measured by the patient by using the physical sign detection equipment, the physical sign information of the patient is analyzed by the rehabilitation regulation platform, the food contraindications and food intake in the rehabilitation stage are intelligently regulated, and the analysis result is sent to the session layer by the transmission layer.
Description
Technical Field
The invention relates to the technical field of cloud computing, in particular to an intelligent medical response method based on big data and an intelligent medical cloud computing system.
Background
With the high-speed development of the internet of things technology, computer technology and communication technology, the internet of things technology, communication technology and medical system are combined in the modern society, numerous intelligent medical response methods and intelligent medical systems are formed, more convenience is brought to patient treatment in gradually replacing the traditional medical mode, a convenient function is provided for doctor to treat patients, after doctor treats patients, patients are recovered at home, the patients basically need to take medicines or relieve illness, and the patients basically need to have food contraindications and are regulated for food intake, but in the existing technology in this aspect, most of the systems intelligently recommend the food contraindications and food intake for the patients according to the illness of the patients, but the problems are that the system cannot verify the actual physical condition of the patients every day, whether the recommended food contraindications and food intake are suitable for the patients, blindly and uniformly according to the illness types of the patients, the patients are not required to advance the food contraindications and food intake for the patients, and the illness state of the patients is possibly unfavorable for the recovery of the patients, and even the illness state of the patients is aggravated. Therefore, it is necessary to design and apply matrix technology, and analyze the intelligent medical response method and intelligent medical cloud computing system based on big data of food contraindications and food intake suitable for the actual situation of the patient according to the daily actual physical condition of the patient and the rehabilitation stage.
Disclosure of Invention
The invention aims to provide a smart medical response method and a smart medical cloud computing system based on big data, so as to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: an intelligent medical response method based on big data, the method comprising the steps of:
step one: developing a C/S architecture system, deploying a doctor-patient APP at a session layer, applying an HTTP protocol at a network layer, constructing a rehabilitation regulation platform and a cloud database at a transmission layer, and accessing physical sign detection equipment at a physical layer;
step two: the doctor sets the parameter ranges of rehabilitation stage, food contraindication, blood sugar, blood pressure and blood fat of the patient to the transmission layer at the session layer, and the patient checks various information stored in the transmission layer at the session layer;
step three: the doctor sets physical sign parameters to the transmission layer at the session layer, and corresponds to food intake in different rehabilitation stages;
step four: the physical sign detection equipment of the physical layer is used for measuring the physical sign information of the patient, the rehabilitation regulation and control platform analyzes the physical sign information of the patient, the food contraindications and food intake in the rehabilitation stage are intelligently regulated and controlled, and the transmission layer sends the analysis result to the session layer.
According to the above technical scheme, the developing a C/S architecture system deploys a doctor-patient APP at a session layer, applies an HTTP protocol at a network layer, constructs a rehabilitation regulation platform and a cloud database at a transmission layer, and accesses a physical sign detection device at a physical layer, including:
the system is developed and deployed mainly by a Client/Server architecture;
deploying a doctor-patient APP at a session layer;
constructing a rehabilitation regulation platform and a cloud database on a transmission layer;
the data interaction between the session layer and the transmission layer is mainly realized by applying the HTTP protocol as a main communication protocol in the network layer;
accessing physical sign detection equipment at a physical layer;
the data interaction between the physical layer and the transmission layer is mainly realized by applying a TCP/UDP protocol as a main communication protocol at the network layer;
the physical layer network is formed by a plurality of physical layer network detection devices, so that nodes are formed, and the plurality of physical layer network detection devices in the nodes share detection data and report the detection data uniformly.
According to the above technical scheme, the doctor sets the rehabilitation stage, the food contraindication, the blood sugar, the blood pressure and the blood fat parameter range of the patient to the transmission layer at the session layer, and the patient checks each item of information stored in the transmission layer at the session layer, comprising the following steps:
a doctor uses a doctor-patient APP at a session layer, and sets parameter ranges of rehabilitation stages, food contraindications, blood sugar, blood pressure and blood fat of patients to a rehabilitation regulation platform according to the disease condition, physical condition and physical state characteristics of each patient;
the setting mode is as follows:
at a stage of patient rehabilitation:
the foods of a11, a12, a 13..a 1n are prohibited, the foods of a11, a12, a 13..a 1n are not eaten, the foods of B11, B12, B13..b 1n are properly eaten, the foods of B11, B12, B13..b 1n are not eaten, the foods of c11, c12, c 13..c1n are not eaten, and the blood sugar concentration range is controlled to be: in the range of k11-k12, mg/dL, the blood pressure range is controlled in: L11-L12, mmHg, blood lipid range is controlled in: m11-m12, mmol/L;
in the patient rehabilitation phase:
the foods of a21, a22, d 23..a 2n are prohibited, the foods of a21, a22, a 23..a 2n are not eaten, the foods of B21, B22, B23..b 2n are properly eaten, the foods of B21, B22, B23..b 2n are not eaten, the foods of c21, c22, c 23..c2n are not eaten, and the blood sugar concentration range is controlled to be within the following range: in the range of k21-k22, mg/dL, the blood pressure range is controlled to be: in the range of L21-L22 and mmHg, the blood fat range is controlled to be: m21-m22, mmol/L;
in three phases of patient recovery:
the foods of a31, a32, a 33..a 3n are prohibited, the foods of a31, a32, a 33..a 3n are not eaten, the foods of B31, B32, B33..b 3n are properly eaten, the foods of B31, B32, B33..b 3n are not eaten, the foods of c31, c32, c 33..c3n are not eaten, and the blood sugar concentration range is controlled to be within the following range: in the range of k31-k32, mg/dL, the blood pressure range is controlled in: in the range of L31-L32 and mmHg, the blood fat range is controlled to be: m31-m32, mmol/L.
According to the above technical scheme, the step that the doctor sets sign parameters to the transmission layer at the session layer, and corresponds to food intake and food contraindications at different rehabilitation stages comprises:
the doctor sets up the food intake that sign parameter high-low range corresponds different rehabilitation stages to the rehabilitation regulation platform at the transmission layer at the session layer, and its mode is:
if at a stage of patient recovery:
the blood glucose concentration range exceeds: k11-k12, mg/dL, blood pressure range exceeds: L11-L12, mmHg, blood lipid range exceeded: m11-m12, mmol/L;
the foods of the a11, a12, a13, A1n and the c13, B12 are forbidden to eat, the foods of the a11, a12, a13, A1n and the c12, B13 are not eaten, the foods of the B11, B13, B14, B1n are properly eaten, the foods of the B11, B12, B14, B1n and the foods of the c14 are eaten more, and the foods of the c11, c15, c1n are not eaten;
if at a stage of patient recovery:
the blood glucose concentration range is below: k11-k12, mg/dL, blood pressure range below: L11-L12, mmHg, blood lipid range is lower than: m11-m12, mmol/L;
it is forbidden to eat foods of the a11, a12, a 13..a 1n and B12, foods of the a12, a 14..a 1n and B14 are not eaten, foods of the B11, B12, B13, B15..b 1n and B11, c12 are properly eaten, foods of the B13, B14..b 1n and a11, a13 are not eaten, and foods of the c11, c 13..c 1n are not eaten.
According to the above technical solution, the step of setting food intake and food contraindications in different rehabilitation stages includes:
if in the patient rehabilitation phase:
when the blood sugar, blood pressure and blood fat exceed the set ranges, the foods of the a21, a22 and a23, the A2n type, the foods of the A22 and B21 type, the foods of the A21, the A23, the A2n type, the foods of the B24 and the B21 type are forbidden to eat, the foods of the B22, the B23 and the B25 type, the foods of the B2n type, the foods of the B22, the B24 type, the foods of the B2n type and the c24 type are forbidden to eat, and the foods of the c21, the c22, the c23, the c25 type, the c2n type and the B23 type are forbidden to eat;
the same doctor sets the food contraindication and intake of the blood sugar, the blood pressure and the blood fat in the rehabilitation stage lower than the set range;
the change of food contraindications and intake corresponding to the change of the physical sign range in the rehabilitation three stages is set in the same way;
and storing all the data into a cloud database in a matrix form on a rehabilitation regulation platform of a transmission layer, and marking diagonal lines, first rows and first columns of the matrix.
According to the above technical scheme, physical sign information is measured to physical sign detection equipment of patient application physical layer, and recovered regulation and control platform analysis patient's physical sign information, and food in the recovered stage of intelligent regulation and control is contraindicated and food intake, and the step of session layer is sent to the analysis result to the transmission layer includes:
the patient uses physical sign detection equipment deployed on a physical layer to measure the magnitude of each physical sign parameter of the patient:
blood glucose k, blood pressure L and blood fat m;
after the detection equipment detects all physical sign data of the patient, uploading the data to a transmission layer;
the physical sign information data of the patient is converted into a matrix { B };
the platform converts information data of different food contraindications and food intake amounts, which are set by doctors for patients and correspond to different rehabilitation stages, into a matrix { A };
comparing the matrix { B } with the matrix { A } through marked diagonal lines, matrix head rows and matrix head columns of the matrix { A }, and filling row-column elements in the matrix { A } which are not in the matrix { B } with 1 to obtain a matrix { C };
multiplying { C }, { A } matrix, and transposed to obtain { CA } T ；
Then, the inverse { A } of the { A } matrix is calculated -1 Will { CA } T Matrix sum { A }, matrix sum { A } -1 The matrix { CA }, is analyzed by comparing each row with each column of elements in the matrix T Lambda of (2);
each element of the matrix { C } is analyzed one by one according to lambda, and finally, the solution is as follows:
during the rehabilitation stage N, patients should avoid eating aN1, aN2, aN3, AN2, AN4, bN1 and BN2 foods, eat less AN1, AN5, bN3, BN5 and cN2 foods, eat bN2, bN4, bN5, aN4 and AN6 foods properly, eat more BN1, BN3 and AN3 foods and must eat more cN1, cN3, cN4 and bN6 foods because blood sugar k is high/low/normal in the set range, blood pressure L is high/low/normal in the set range and blood fat m is high/low/normal in the set range;
the result solved by the rehabilitation control platform is sent to a session layer;
the patient looks at APP at what phase of the rehabilitation phase the day is, which food is contraindicated for, the size of the food intake.
According to the above technical solution, the session layer includes:
the patient end APP is used for a patient to check daily food contraindications, food intake and rehabilitation stages;
and the doctor terminal APP is used for setting the food contraindication and the food intake corresponding to each rehabilitation stage, and setting the change of the corresponding food contraindication and food intake when the change of the sign parameters is abnormal.
According to the above technical solution, the transmission layer includes:
the rehabilitation regulation and control platform is used for converting the data sent by the session layer and the physical layer into determinant of a matrix, and solving the actual food contraindications, the food intake and the rehabilitation stage of the patient according to the physical sign information of the patient;
and the cloud database stores various data of the reservation system.
According to the above technical solution, the physical layer includes:
the physical sign detection equipment is used for detecting daily physical sign parameters of a patient, detecting blood pressure, blood sugar concentration and blood fat parameter information of the patient, and reporting the parameter information to the rehabilitation regulation platform of the transmission layer.
Compared with the prior art, the invention has the following beneficial effects: according to the invention, a doctor APP is deployed on a session layer, a rehabilitation regulation platform is constructed on a transmission layer, a detection device is accessed on a physical layer, a doctor sets a rehabilitation stage, a food contraindication, blood sugar blood pressure and blood fat parameter range of a patient to the transmission layer, the patient looks up various information stored on the transmission layer, the doctor sets physical sign parameters to the transmission layer on the session layer, the patient measures the physical sign information corresponding to food intake and contraindication in different rehabilitation stages by using the physical sign detection device, the rehabilitation regulation platform analyzes the physical sign information of the patient, the food contraindication and food intake in the rehabilitation stage are intelligently regulated, and the transmission layer sends an analysis result to the session layer, so that the traditional system pushes the food contraindication and the food intake not only according to the illness state of the patient, but also more importantly, pushes the food contraindication and the food intake for the patient according to the actual condition of the patient on a daily body and the rehabilitation stage of the patient on the current day.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
FIG. 1 is a flowchart of a smart medical response method based on big data according to an embodiment of the present invention;
fig. 2 is a schematic diagram of module components of an intelligent medical cloud computing system according to a second embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Embodiment one: fig. 1 is a flowchart of a big data-based intelligent medical response method according to an embodiment of the present invention, where the method may be implemented by the big data-based intelligent medical response method according to the embodiment, and the method specifically includes the following steps:
step one: developing a C/S architecture system, deploying a doctor-patient APP at a session layer, applying an HTTP protocol at a network layer, constructing a rehabilitation regulation platform and a cloud database at a transmission layer, and accessing physical sign detection equipment at a physical layer;
in the embodiment of the invention, the system is mainly developed and deployed by a Client/Server architecture, a doctor-patient APP is deployed in a session layer, a rehabilitation regulation platform and a cloud database are constructed in a transmission layer, data interaction between the session layer and the transmission layer is mainly realized by using an HTTP protocol as a main communication protocol in a network layer, physical sign detection equipment is accessed in a physical layer, data interaction between the physical layer and the transmission layer is mainly realized by using a TCP/UDP protocol as a main communication protocol in the network layer, a plurality of sign detection equipment are networked in the physical layer to form a node, and a plurality of detection equipment in the node share detection data and uniformly report the data.
Step two: the doctor sets the parameter ranges of rehabilitation stage, food contraindication, blood sugar, blood pressure and blood fat of the patient to the transmission layer at the session layer, and the patient checks various information stored in the transmission layer at the session layer;
s21: in the embodiment of the invention, a doctor uses a doctor APP at a session layer, and sets the parameter ranges of rehabilitation stage, food contraindication, blood sugar, blood pressure and blood fat of a patient to a rehabilitation regulation platform according to the illness condition, physical condition and physical state characteristics of each patient in the following setting modes: at a stage of patient rehabilitation: the foods of a11, a12, a 13..a 1n are prohibited, the foods of a11, a12, a 13..a 1n are not eaten, the foods of B11, B12, B13..b 1n are properly eaten, the foods of B11, B12, B13..b 1n are not eaten, the foods of c11, c12, c 13..c1n are not eaten, and the blood sugar concentration range is controlled to be: in the range of k11-k12, mg/dL, the blood pressure range is controlled in: L11-L12, mmHg, blood lipid range is controlled in: m11-m12, mmol/L;
s22: in the patient rehabilitation phase: the foods of a21, a22, d 23..a 2n are prohibited, the foods of a21, a22, a 23..a 2n are not eaten, the foods of B21, B22, B23..b 2n are properly eaten, the foods of B21, B22, B23..b 2n are not eaten, the foods of c21, c22, c 23..c2n are not eaten, and the blood sugar concentration range is controlled to be within the following range: in the range of k21-k22, mg/dL, the blood pressure range is controlled to be: in the range of L21-L22 and mmHg, the blood fat range is controlled to be: m21-m22, mmol/L;
s23: in three phases of patient recovery: the foods of a31, a32, a 33..a 3n are prohibited, the foods of a31, a32, a 33..a 3n are not eaten, the foods of B31, B32, B33..b 3n are properly eaten, the foods of B31, B32, B33..b 3n are not eaten, the foods of c31, c32, c 33..c3n are not eaten, and the blood sugar concentration range is controlled to be within the following range: in the range of k31-k32, mg/dL, the blood pressure range is controlled in: in the range of L31-L32 and mmHg, the blood fat range is controlled to be: m31-m32, mmol/L.
Step three: the doctor sets physical sign parameters to the transmission layer at the session layer, and corresponds to food intake and food contraindications at different rehabilitation stages;
s31: in the embodiment of the invention, a doctor sets food intake amounts corresponding to different rehabilitation stages in the high-low range of physical sign parameters to a rehabilitation regulation platform at a transmission layer at a session layer, and the mode is as follows: if at a stage of patient recovery: the blood glucose concentration range exceeds: k11-k12, mg/dL, blood pressure range exceeds: L11-L12, mmHg, blood lipid range exceeded: m11-m12, mmol/L, a11, a12, a13, A1n and c13, B12 foods are prohibited, a11, a12, a13, A1n and c12, B13 foods are taken less, B11, B13, B14, B1n foods are taken more properly, B11, B12, B14, B1n and c14 foods are taken more, c11, c15, c1n foods are taken more; if at a stage of patient recovery: the blood glucose concentration range is below: k11-k12, mg/dL, blood pressure range below: L11-L12, mmHg, blood lipid range is lower than: m11-m12, mmol/L, a11, a12, a13, A1n and B12 foods are prohibited, a12, a14, A1n and B14 foods are not taken, B11, B12, B13, B15, B1n and B11, c12 foods are properly taken, B13, B14, B1n and a11, a13, c11, c13 and c1n foods are not taken;
s32: if in the patient rehabilitation phase: when the blood sugar, blood pressure and blood fat exceed the set ranges, the foods of the a21, a22 and a23, the A2n type, the foods of the A22 and B21 type, the foods of the A21, the A23, the A2n type, the foods of the B24 and the B21 type are forbidden to eat, the foods of the B22, the B23 and the B25 type, the foods of the B2n type, the foods of the B22, the B24 type, the foods of the B2n type and the c24 type are forbidden to eat, and the foods of the c21, the c22, the c23, the c25 type, the c2n type and the B23 type are forbidden to eat; the same doctor sets the food contraindication and intake of the rehabilitation stage with blood sugar, blood pressure and blood fat lower than the setting range, and sets the food contraindication and intake corresponding to the change of the physical sign range of the rehabilitation stage with the same theory, and stores the data in the cloud database in a matrix form on a rehabilitation regulation platform of a transmission layer, and marks the diagonal line, the first row and the first column of the matrix.
Step four: the physical sign detection equipment of the physical layer is used for measuring the physical sign information of the patient, the rehabilitation regulation and control platform analyzes the physical sign information of the patient, the food contraindications and food intake in the rehabilitation stage are intelligently regulated and controlled, and the transmission layer sends the analysis result to the session layer;
in the embodiment of the invention, the patient uses the physical sign detection equipment deployed on the physical layer to measure the magnitude of each physical sign parameter of the patient: after the detection equipment detects all sign data of a patient, the data are uploaded to a transmission layer, and the sign information data of the patient are converted into the rehabilitation regulation platform of the transmission layerThe matrix { B }, the platform converts information data of different food contraindications and food intake amounts, which are set by doctors for patients and correspond to different rehabilitation stages, into a matrix { A }, compares the matrix { B } with the matrix { A } through marked diagonal lines, matrix head rows and matrix head columns of the matrix { A }, supplements row and column elements in the matrix { A } which are not in the matrix { B } by 1 to obtain a matrix { C }, multiplies the matrix { A } by the matrix { C }, and then carries out transposition to obtain a matrix { CA } T Then, the inverse { A } of the { A } matrix is calculated -1 Will { CA } T Matrix sum { A }, matrix sum { A } -1 The matrix { CA }, is analyzed by comparing each row with each column of elements in the matrix T According to lambda of lambda, analyzing each element of the matrix { C } one by one, finally solving that, in the rehabilitation stage N, as the blood sugar k is high/low/normal in the set range, the blood pressure L is high/low/normal in the set range, and the blood fat m is high/low/normal in the set range, the patients should be prohibited from eating aN1, aN2, aN3, AN2, AN4, bN1 and BN2 foods, the AN1, AN5, bN3, BN5 and cN2 foods are not eaten, the bN2, bN4, bN5, aN4 and AN6 foods are properly eaten, the bN1, BN3 and AN3 foods are eaten more, the results solved by the rehabilitation regulation platform are sent to the session layer, and the patients check the stages of the rehabilitation stage on the APP, and the food is prevented from eating any food intake;
compared with the existing intelligent medical cloud computing system on the market, the system applies the matrix operation technology to convert the food contraindication and food intake information data corresponding to different rehabilitation stages of a patient into determinant of the matrix, and then solves the actual required food contraindication, food intake and rehabilitation stage of the patient on the same day according to the daily sign information matrix of the patient, and does not just input what kind of diseases the patient has on the system, and one-taste checks the food contraindication and food recommendation of the patient, so that the real purpose of refining the food contraindication and food recommendation of the patient on the same day is achieved.
Embodiment two: fig. 2 is a schematic diagram of module composition of the smart medical cloud computing system according to the second embodiment of the present invention, as shown in fig. 2, where the smart medical cloud computing system includes:
the session layer is used for providing a deployment environment for the APP and carrying out data interaction with the transmission layer;
the transmission layer is used for providing a deployment environment for the cloud platform and the cloud database and transmitting various data to the upper layer and the lower layer;
the physical layer is used for providing a deployment environment for each hardware equipment node, sending data to the upper layer and receiving the data sent by the upper layer;
in some embodiments of the invention, the session layer comprises:
the patient end APP is used for a patient to check daily food contraindications, food intake and rehabilitation stages;
the doctor terminal APP is used for setting the food contraindication and the food intake corresponding to each rehabilitation stage, and setting the change of the corresponding food contraindication and the food intake when the change of the sign parameters is abnormal;
in some embodiments of the invention, the transport layer comprises:
the rehabilitation regulation and control platform is used for converting the data sent by the session layer and the physical layer into determinant of a matrix, and solving the actual food contraindications, the food intake and the rehabilitation stage of the patient according to the physical sign information of the patient;
the cloud database stores various data of the reservation system;
in some embodiments of the invention, the physical layer comprises:
the physical sign detection equipment is used for detecting physical sign parameters of patients every day and reporting parameter information to a rehabilitation regulation platform of the transmission layer.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. The intelligent medical response method based on big data is characterized in that: the method comprises the following steps:
step one: developing a C/S architecture system, deploying a doctor-patient APP at a session layer, applying an HTTP protocol at a network layer, constructing a rehabilitation regulation platform and a cloud database at a transmission layer, and accessing physical sign detection equipment at a physical layer;
step two: the doctor sets the parameter ranges of rehabilitation stage, food contraindication, blood sugar, blood pressure and blood fat of the patient to the transmission layer at the session layer, and the patient checks various information stored in the transmission layer at the session layer;
step three: the doctor sets physical sign parameters to the transmission layer at the session layer, and corresponds to food intake in different rehabilitation stages;
step four: the physical sign detection equipment of the physical layer is used for measuring the physical sign information of the patient, the rehabilitation regulation and control platform analyzes the physical sign information of the patient, the food contraindications and food intake in the rehabilitation stage are intelligently regulated and controlled, and the transmission layer sends the analysis result to the session layer.
2. The big data based intelligent medical response method of claim 1, wherein: the developing a C/S architecture system, deploying a doctor-patient APP at a session layer, applying an HTTP protocol at a network layer, constructing a rehabilitation regulation platform and a cloud database at a transmission layer, and accessing physical sign detection equipment at a physical layer, wherein the developing comprises the following steps:
the system is developed and deployed mainly by a Client/Server architecture;
deploying a doctor-patient APP at a session layer;
constructing a rehabilitation regulation platform and a cloud database on a transmission layer;
the data interaction between the session layer and the transmission layer is mainly realized by applying the HTTP protocol as a main communication protocol in the network layer;
accessing physical sign detection equipment at a physical layer;
the data interaction between the physical layer and the transmission layer is mainly realized by applying a TCP/UDP protocol as a main communication protocol at the network layer;
the physical layer network is formed by a plurality of physical layer network detection devices, so that nodes are formed, and the plurality of physical layer network detection devices in the nodes share detection data and report the detection data uniformly.
3. The big data based intelligent medical response method of claim 1, wherein: the doctor sets the rehabilitation stage, the food contraindication, the blood sugar, the blood pressure and the blood fat parameter range of the patient to the transmission layer at the session layer, and the patient checks each item of information stored in the transmission layer at the session layer, and the doctor comprises the following steps:
a doctor uses a doctor-patient APP at a session layer, and sets parameter ranges of rehabilitation stages, food contraindications, blood sugar, blood pressure and blood fat of patients to a rehabilitation regulation platform according to the disease condition, physical condition and physical state characteristics of each patient;
the setting mode is as follows:
at a stage of patient rehabilitation:
the foods of a11, a12, a 13..a 1n are prohibited, the foods of a11, a12, a 13..a 1n are not eaten, the foods of B11, B12, B13..b 1n are properly eaten, the foods of B11, B12, B13..b 1n are not eaten, the foods of c11, c12, c 13..c1n are not eaten, and the blood sugar concentration range is controlled to be: in the range of k11-k12, mg/dL, the blood pressure range is controlled in: L11-L12, mmHg, blood lipid range is controlled in: m11-m12, mmol/L;
in the patient rehabilitation phase:
the foods of a21, a22, d 23..a 2n are prohibited, the foods of a21, a22, a 23..a 2n are not eaten, the foods of B21, B22, B23..b 2n are properly eaten, the foods of B21, B22, B23..b 2n are not eaten, the foods of c21, c22, c 23..c2n are not eaten, and the blood sugar concentration range is controlled to be within the following range: in the range of k21-k22, mg/dL, the blood pressure range is controlled to be: in the range of L21-L22 and mmHg, the blood fat range is controlled to be: m21-m22, mmol/L;
in three phases of patient recovery:
the foods of a31, a32, a 33..a 3n are prohibited, the foods of a31, a32, a 33..a 3n are not eaten, the foods of B31, B32, B33..b 3n are properly eaten, the foods of B31, B32, B33..b 3n are not eaten, the foods of c31, c32, c 33..c3n are not eaten, and the blood sugar concentration range is controlled to be within the following range: in the range of k31-k32, mg/dL, the blood pressure range is controlled in: in the range of L31-L32 and mmHg, the blood fat range is controlled to be: m31-m32, mmol/L.
4. The big data based intelligent medical response method of claim 1, wherein: the doctor sets sign parameters to the transmission layer at the session layer, and corresponds to the food intake and food contraindications of different rehabilitation stages, comprising the following steps:
the doctor sets up the food intake that sign parameter high-low range corresponds different rehabilitation stages to the rehabilitation regulation platform at the transmission layer at the session layer, and its mode is:
if at a stage of patient recovery:
the blood glucose concentration range exceeds: k11-k12, mg/dL, blood pressure range exceeds: L11-L12, mmHg, blood lipid range exceeded: m11-m12, mmol/L;
the foods of the a11, a12, a13, A1n and the c13, B12 are forbidden to eat, the foods of the a11, a12, a13, A1n and the c12, B13 are not eaten, the foods of the B11, B13, B14, B1n are properly eaten, the foods of the B11, B12, B14, B1n and the foods of the c14 are eaten more, and the foods of the c11, c15, c1n are not eaten;
if at a stage of patient recovery:
the blood glucose concentration range is below: k11-k12, mg/dL, blood pressure range below: L11-L12, mmHg, blood lipid range is lower than: m11-m12, mmol/L;
it is forbidden to eat foods of the a11, a12, a 13..a 1n and B12, foods of the a12, a 14..a 1n and B14 are not eaten, foods of the B11, B12, B13, B15..b 1n and B11, c12 are properly eaten, foods of the B13, B14..b 1n and a11, a13 are not eaten, and foods of the c11, c 13..c 1n are not eaten.
5. The step of setting food intake and food contraindications for different rehabilitation stages according to claim 4, comprising:
if in the patient rehabilitation phase:
when the blood sugar, blood pressure and blood fat exceed the set ranges, the foods of the a21, a22 and a23, the A2n type, the foods of the A22 and B21 type, the foods of the A21, the A23, the A2n type, the foods of the B24 and the B21 type are forbidden to eat, the foods of the B22, the B23 and the B25 type, the foods of the B2n type, the foods of the B22, the B24 type, the foods of the B2n type and the c24 type are forbidden to eat, and the foods of the c21, the c22, the c23, the c25 type, the c2n type and the B23 type are forbidden to eat;
the same doctor sets the food contraindication and intake of the blood sugar, the blood pressure and the blood fat in the rehabilitation stage lower than the set range;
the change of food contraindications and intake corresponding to the change of the physical sign range in the rehabilitation three stages is set in the same way;
and storing all the data into a cloud database in a matrix form on a rehabilitation regulation platform of a transmission layer, and marking diagonal lines, first rows and first columns of the matrix.
6. The big data based intelligent medical response method of claim 1, wherein: the patient utilizes physical sign detection equipment of physical layer to measure the physical sign information, and the recovered regulation and control platform analysis patient's physical sign information, intelligent regulation and control recovered stage's food is contraindicated and food is ingested, and the step of session layer is sent to the analysis result to the transmission layer includes:
the patient uses physical sign detection equipment deployed on a physical layer to measure the magnitude of each physical sign parameter of the patient:
blood glucose k, blood pressure L and blood fat m;
after the detection equipment detects all physical sign data of the patient, uploading the data to a transmission layer;
the physical sign information data of the patient is converted into a matrix { B };
the platform converts information data of different food contraindications and food intake amounts, which are set by doctors for patients and correspond to different rehabilitation stages, into a matrix { A };
comparing the matrix { B } with the matrix { A } through marked diagonal lines, matrix head rows and matrix head columns of the matrix { A }, and filling row-column elements in the matrix { A } which are not in the matrix { B } with 1 to obtain a matrix { C };
multiplying { C }, { A } matrix, and transposed to obtain { CA } T ；
Then, the inverse { A } of the { A } matrix is calculated -1 Will { CA } T Matrix sum { A }, matrix sum { A } -1 The matrix { CA }, is analyzed by comparing each row with each column of elements in the matrix T Lambda of (2);
each element of the matrix { C } is analyzed one by one according to lambda, and finally, the solution is as follows:
during the rehabilitation stage N, patients should avoid eating aN1, aN2, aN3, AN2, AN4, bN1 and BN2 foods, eat less AN1, AN5, bN3, BN5 and cN2 foods, eat bN2, bN4, bN5, aN4 and AN6 foods properly, eat more BN1, BN3 and AN3 foods and must eat more cN1, cN3, cN4 and bN6 foods because blood sugar k is high/low/normal in the set range, blood pressure L is high/low/normal in the set range and blood fat m is high/low/normal in the set range;
the result solved by the rehabilitation control platform is sent to a session layer;
the patient looks at APP at what phase of the rehabilitation phase the day is, which food is contraindicated for, the size of the food intake.
7. Wisdom medical cloud computing system, its characterized in that: the system comprises:
the session layer is used for providing a deployment environment for the APP and carrying out data interaction with the transmission layer;
the transmission layer is used for providing a deployment environment for the cloud platform and the cloud database and transmitting various data to the upper layer and the lower layer;
and the physical layer is used for providing a deployment environment for each hardware equipment node, sending data to the upper layer and receiving the data sent by the upper layer.
8. The smart medical cloud computing system of claim 7, wherein: the session layer includes:
the patient end APP is used for a patient to check daily food contraindications, food intake and rehabilitation stages;
and the doctor terminal APP is used for setting the food contraindication and the food intake corresponding to each rehabilitation stage, and setting the change of the corresponding food contraindication and food intake when the change of the sign parameters is abnormal.
9. The smart medical cloud computing system of claim 7, wherein: the transport layer includes:
the rehabilitation regulation and control platform is used for converting the data sent by the session layer and the physical layer into determinant of a matrix, and solving the actual food contraindications, the food intake and the rehabilitation stage of the patient according to the physical sign information of the patient;
and the cloud database stores various data of the reservation system.
10. The smart medical cloud computing system of claim 7, wherein: the physical layer includes:
the physical sign detection equipment is used for detecting daily physical sign parameters of a patient, detecting blood pressure, blood sugar concentration and blood fat parameter information of the patient, and reporting the parameter information to the rehabilitation regulation platform of the transmission layer.
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