Smart medical response method and smart medical cloud computing system based on big data

Abstract

The present invention discloses a smart medical response method based on big data, which includes the following steps: Step 1: deploy a medical and patient APP at the session layer, build a rehabilitation regulation and control platform at the transmission layer, and access the detection equipment at the physical layer; Step 2: the doctor sets the patient's rehabilitation stage, food taboos, blood sugar, blood pressure, and blood lipid parameter ranges to the transmission layer, and the patient views the various information stored in the transmission layer; Step 3: the doctor sets the high and low physical sign parameters to the transmission layer at the session layer, corresponding to the food intake and taboos at different rehabilitation stages; Step 4: the patient uses the physical sign detection equipment to measure the physical sign information, the rehabilitation regulation and control platform analyzes the patient's physical sign information, and intelligently regulates the food taboos and food intake at the rehabilitation stage, and the transmission layer sends the analysis results to the session layer. According to the present invention, it has the ability to analyze the patient's actual physical condition and the rehabilitation stage, and formulate food taboos and food intake for the patient according to the actual situation and stage.

Description

Technical Field

[0001] The present invention relates to the field of cloud computing technology, and in particular to a smart medical response method and a smart medical cloud computing system based on big data. Background Art

[0002] With the rapid development of Internet of Things technology, computer technology, and communication technology, in today's society, Internet of Things technology, communication technology, and medical systems have long been combined, and many smart medical response methods and smart medical systems have been formed. They are gradually replacing the traditional medical model, bringing more convenience to patients and providing convenient functions for doctors to treat patients. After the doctor sees the patient, the patient needs to take medicine or relieve the condition. The patient basically needs to have food taboos and prescribed food intake. At present, among the existing technologies in this regard, most of them are systems that intelligently recommend food taboos and food intake for patients according to the patient's condition. However, the problem is that the system cannot verify the patient's actual physical condition every day, whether it is suitable for the recommended food taboos and food intake. Blindly following the patient's illness type without referring to the patient's actual physical condition, it promotes food taboos and food intake for the patient, which may be detrimental to the patient's recovery and even aggravate the patient's condition. Therefore, it is necessary to design and use matrix technology to analyze the food taboos and food intake suitable for the patient's actual situation according to the patient's actual physical condition and the stage of rehabilitation. A smart medical response method based on big data and a smart medical cloud computing system. Summary of the invention

[0003] The purpose of the present invention is to provide a smart medical response method and a smart medical cloud computing system based on big data to solve the problems raised in the above background technology.

[0004] In order to solve the above technical problems, the present invention provides the following technical solutions: a smart medical response method based on big data, the method comprising the following steps:

[0005] Step 1: Develop a C / S architecture system, deploy doctor-patient APP at the session layer, use HTTP protocol at the network layer, build a rehabilitation control platform and cloud database at the transport layer, and access vital sign detection equipment at the physical layer;

[0006] Step 2: The doctor sets the patient's recovery stage, food restrictions, blood sugar, blood pressure, and blood lipid parameter ranges to the transport layer at the session layer, and the patient views the information stored in the transport layer at the session layer;

[0007] Step 3: The doctor sets the high and low vital sign parameters to the transmission layer at the session layer, corresponding to the food intake at different recovery stages;

[0008] Step 4: The patient uses the physical layer's vital sign detection equipment to measure vital sign information. The rehabilitation control platform analyzes the patient's vital sign information and intelligently controls food taboos and food intake during the rehabilitation phase. The transport layer sends the analysis results to the session layer.

[0009] According to the above technical solution, the steps of developing a C / S architecture system, deploying a doctor-patient APP at the session layer, using the HTTP protocol at the network layer, building a rehabilitation control platform and a cloud database at the transport layer, and accessing a vital sign detection device at the physical layer include:

[0010] The system is mainly developed and deployed based on the Client / Server architecture;

[0011] Deploy the doctor-patient APP at the session layer;

[0012] Build a rehabilitation control platform and cloud database at the transport layer;

[0013] The data exchange between the session layer and the transport layer is mainly through the use of HTTP protocol as the main communication protocol in the network layer;

[0014] Access vital sign detection equipment at the physical layer;

[0015] The data exchange between the physical layer and the transport layer is mainly through the use of TCP / UDP protocol as the main communication protocol in the network layer;

[0016] Multiple vital sign detection devices are networked at the physical layer to form a node. Multiple detection devices within the node share detection data and report the data in a unified manner.

[0017] According to the above technical solution, the doctor sets the patient's recovery stage, food taboos, blood sugar, blood pressure, and blood lipid parameter ranges to the transmission layer at the session layer, and the patient views the various information stored in the transmission layer at the session layer, including:

[0018] Doctors use the doctor-patient APP at the conversation layer to set the patient's rehabilitation stage, food taboos, blood sugar, blood pressure, and blood lipid parameter ranges to the rehabilitation control platform based on each patient's illness, physical condition, and body characteristics;

[0019] The setting method is:

[0020] During the first stage of recovery:

[0021] Avoid eating a11, a12, a13...a1n foods, eat less A11, A12, A13...A1n foods, eat b11, b12, b13...b1n foods appropriately, eat more B11, B12, B13...B1n foods, must eat c11, c12, c13...c1n foods, control blood sugar concentration within the range of k11-k12, mg / dL, control blood pressure within the range of L11-L12, mmHg, control blood lipids within the range of m11-m12, mmol / L;

[0022] In the second stage of patient recovery:

[0023] Avoid eating a21, a22, d23...a2n foods, eat less A21, A22, A23...A2n foods, eat b21, b22, b23...b2n foods appropriately, eat more B21, B22, B23...B2n foods, must eat c21, c22, c23...c2n foods, control blood sugar concentration within the range of k21-k22, mg / dL, control blood pressure within the range of L21-L22, mmHg, control blood lipids within the range of m21-m22, mmol / L;

[0024] There are three stages of patient recovery:

[0025] Avoid eating a31, a32, a33...a3n foods, eat less A31, A32, A33...A3n foods, eat b31, b32, b33...b3n foods appropriately, eat more B31, B32, B33...B3n foods, must eat c31, c32, c33...c3n foods, blood sugar concentration range should be controlled within the range of k31-k32, mg / dL, blood pressure range should be controlled within the range of L31-L32, mmHg, blood lipid range should be controlled within the range of m31-m32, mmol / L.

[0026] According to the above technical solution, the doctor sets the level of the physical sign parameters to the transmission layer at the session layer, and the steps of corresponding food intake and food taboos at different recovery stages include:

[0027] The doctor, at the session layer, sets the high and low ranges of the physical sign parameters corresponding to the food intake at different recovery stages to the rehabilitation control platform at the transmission layer in the following manner:

[0028] If during the first stage of recovery:

[0029] Blood glucose concentration range exceeds: k11-k12, mg / dL, blood pressure range exceeds: L11-L12, mmHg, blood lipid range exceeds: m11-m12, mmol / L;

[0030] Then avoid eating a11, a12, a13...a1n and c13, b12 foods, eat less A11, A12, A13...A1n and c12, B13 foods, eat b11, b13, b14...b1n foods appropriately, eat more B11, B12, B14...B1n and c14 foods, and must eat c11, c15...c1n foods;

[0031] If during the first stage of recovery:

[0032] Blood glucose concentration range is lower than: k11-k12, mg / dL, blood pressure range is lower than: L11-L12, mmHg, blood lipid range is lower than: m11-m12, mmol / L;

[0033] Then avoid eating a11, a12, a13...a1n and B12 foods, eat less A12, A14...A1n and b14 foods, eat b11, b12, b13, b15...b1n and B11, c12 foods appropriately, eat more B13, B14...B1n and A11, A13 foods, and must eat c11, c13...c1n foods.

[0034] According to the above technical solution, the step of setting food intake and food taboos at different recovery stages includes:

[0035] If in the second stage of patient recovery:

[0036] If blood sugar, blood pressure and blood lipids exceed the set range, avoid eating a21, a22, a23...a2n and A22, b21 foods, eat less A21, A23...A2n and b24, B21 foods, eat b22, b23, b25...b2n foods appropriately, eat more B22, B24...B2n and c24 foods, and must eat c21, c22, c23, c25...c2n and B23 foods;

[0037] Similarly, doctors set food taboos and intake limits for blood sugar, blood pressure, and blood lipids in the second stage of recovery when they are below the set range;

[0038] Similarly, the changes in food taboos and intake corresponding to the changes in the range of physical signs in the three stages of recovery are set;

[0039] In the rehabilitation control platform of the transmission layer, all the above data are stored in the cloud database in the form of a matrix, and the diagonal of the matrix, the first row of the matrix, and the first column of the matrix are marked.

[0040] According to the above technical solution, the patient uses the physical layer's physical sign detection equipment to measure physical sign information, the rehabilitation control platform analyzes the patient's physical sign information, and intelligently controls food taboos and food intake during the rehabilitation stage. The transport layer sends the analysis results to the session layer, including:

[0041] Patients use the vital sign detection equipment deployed at the physical layer to measure the size of their various vital sign parameters:

[0042] Blood sugar k, blood pressure L, blood lipid m;

[0043] After the detection equipment measures all the patient's vital signs, it uploads the data to the transmission layer;

[0044] In the rehabilitation control platform of the transmission layer, the patient's vital sign information data is converted into a matrix {B};

[0045] The platform then converts the information data of different food taboos and food intake corresponding to different recovery stages set by the doctor for the patient into a matrix {A};

[0046] The platform compares matrix {B} with {A} by marking the diagonal, first row, and first column of matrix {A}, and fills the row and column elements of matrix {A} that are not in matrix {B} with 1 to obtain matrix {C};

[0047] Multiply the {C} and {A} matrices and then transpose them to get {CA} T ;

[0048] Then calculate the inverse matrix of the matrix {A} -1 , change {CA} T Matrix and {A} -1 By comparing the elements of each row and column in the matrix, the matrix {CA} T λ;

[0049] According to λ, each element of the matrix {C} is analyzed one by one, and finally the solution is:

[0050] During the recovery 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 appropriately, eat more BN1, BN3, and AN3 foods, and must eat cN1, cN3, cN4, and bN6 foods because their blood sugar k is higher / lower / normal than the set range, their blood pressure L is higher / lower / normal than the set range, and their blood lipid m is higher / lower / normal than the set range.

[0051] The results obtained by the rehabilitation control platform are sent to the session layer;

[0052] Patients can check on the APP which stage of recovery they are in that day, what food taboos they have, and how much food they eat.

[0053] According to the above technical solution, the session layer includes:

[0054] Patient-side APP is used for patients to check their daily food taboos, food intake, and recovery stage;

[0055] The doctor-side APP is used to set the corresponding food taboos and food intake amounts for each recovery stage, and to set the corresponding changes in food taboos and food intake amounts when the vital sign parameters change abnormally.

[0056] According to the above technical solution, the transport layer includes:

[0057] The rehabilitation control platform is used to convert the data sent from the session layer and the physical layer into the determinant of the matrix. Based on the patient's physical signs, it can determine the patient's actual daily dietary restrictions, food intake, and rehabilitation stage.

[0058] Cloud database, which stores and retains various system data.

[0059] According to the above technical solution, the physical layer includes:

[0060] The vital sign detection equipment is used to detect the patient's daily vital sign parameters, blood pressure, blood sugar concentration, and blood lipid parameter information, and report the parameter information to the rehabilitation control platform of the transmission layer.

[0061] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention deploys a medical-patient APP at the session layer, builds a rehabilitation regulation platform at the transmission layer, and accesses detection equipment at the physical layer. The doctor sets the patient's rehabilitation stage, food taboos, blood sugar, blood pressure, and blood lipid parameter ranges to the transmission layer, and the patient views the various information stored in the transmission layer. The doctor sets the high and low physical sign parameters to the transmission layer at the session layer, corresponding to the food intake and taboos at different rehabilitation stages. The patient uses the physical sign detection equipment to measure the physical sign information, and the rehabilitation regulation platform analyzes the patient's physical sign information, intelligently regulates the food taboos and food intake at the rehabilitation stage, and the transmission layer sends the analysis results to the session layer, so that the existing system not only pushes food taboos and food intake according to the patient's condition, but more importantly, pushes food taboos and food intake to the patient according to the patient's actual daily physical condition and the rehabilitation stage of the day. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0063] Figure 1 A flowchart of a smart medical response method based on big data provided in Embodiment 1 of the present invention;

[0064] Figure 2 A schematic diagram of the module composition of the smart medical cloud computing system provided in Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0065] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0066] Embodiment 1: Figure 1 This is a flow chart of a smart medical response method based on big data provided in Embodiment 1 of the present invention. This embodiment can be applied to the scenario of patient recovery. This method can be executed by the smart medical response method based on big data provided in this embodiment. Figure 1 As shown, the method specifically comprises the following steps:

[0067] Step 1: Develop a C / S architecture system, deploy doctor-patient APP at the session layer, use HTTP protocol at the network layer, build a rehabilitation control platform and cloud database at the transport layer, and access vital sign detection equipment at the physical layer;

[0068] In the embodiment of the present invention, the system is mainly developed and deployed with the Client / Server architecture, the medical and patient APP is deployed at the session layer, the rehabilitation control platform and the cloud database are constructed at the transport layer, the data interaction between the session layer and the transport layer is mainly through the use of the HTTP protocol as the main communication protocol at the network layer, the vital sign detection equipment is accessed at the physical layer, the data interaction between the physical layer and the transport layer is mainly through the use of the TCP / UDP protocol as the main communication protocol at the network layer, multiple vital sign detection devices are networked at the physical layer to form a node, and multiple detection devices within the node share detection data and report data in a unified manner.

[0069] Step 2: The doctor sets the patient's recovery stage, food restrictions, blood sugar, blood pressure, and blood lipid parameter ranges to the transport layer at the session layer, and the patient views the information stored in the transport layer at the session layer;

[0070] S21: In the embodiment of the present invention, the doctor uses the doctor-patient APP at the conversation layer to set the patient's rehabilitation stage, food taboos, blood sugar, blood pressure, and blood lipid parameter ranges to the rehabilitation control platform according to each patient's illness, physical condition, and body characteristics. The setting method is: in the first stage of patient rehabilitation: avoid eating a11, a12, a13...a1n foods, eat less A11, A12, A13...A1n foods, eat b11, b12, b13...b1n foods appropriately, eat more B11, B12, B13...B1n foods, must eat c11, c12, c13...c1n foods, the blood sugar concentration range is controlled within the range of k11-k12, mg / dL, the blood pressure range is controlled within the range of L11-L12, mmHg, and the blood lipid range is controlled within the range of m11-m12, mmol / L;

[0071] S22: In the second stage of patient recovery: avoid eating a21, a22, d23...a2n foods, eat less A21, A22, A23...A2n foods, eat b21, b22, b23...b2n foods appropriately, eat more B21, B22, B23...B2n foods, must eat c21, c22, c23...c2n foods, control blood sugar concentration within the range of k21-k22, mg / dL, control blood pressure within the range of L21-L22, mmHg, control blood lipids within the range of m21-m22, mmol / L;

[0072] S23: During the three stages of patient recovery: avoid eating a31, a32, a33...a3n foods, eat less A31, A32, A33...A3n foods, eat b31, b32, b33...b3n foods appropriately, eat more B31, B32, B33...B3n foods, must eat c31, c32, c33...c3n foods, blood sugar concentration range is controlled within the range of k31-k32, mg / dL, blood pressure range is controlled within the range of L31-L32, mmHg, blood lipid range is controlled within the range of m31-m32, mmol / L.

[0073] Step 3: The doctor sets the high and low physical sign parameters to the transmission layer at the session layer, corresponding to the food intake and food taboos at different recovery stages;

[0074] S31: In the embodiment of the present invention, the doctor sets the high and low ranges of the physical sign parameters corresponding to the food intake at different rehabilitation stages to the rehabilitation control platform at the transmission layer at the session layer, in the following manner: if at the first stage of the patient's rehabilitation: the blood sugar concentration range exceeds: k11-k12, mg / dL, the blood pressure range exceeds: L11-L12, mmHg, and the blood lipid range exceeds: m11-m12, mmol / L, then avoid eating a11, a12, a13...a1n and c13, b12 foods, eat less A11, A12, A13...A1n and c12, B13 foods, eat b11, b13, b14...b1n foods appropriately, and eat more B11, B12, B14. ..B1n and c14 foods, must eat c11, c15...c1n foods; if in the first stage of recovery: blood sugar concentration range is lower than: k11-k12, mg / dL, blood pressure range is lower than: L11-L12, mmHg, blood lipid range is lower than: m11-m12, mmol / L, then avoid eating a11, a12, a13...a1n and B12 foods, eat less A12, A14...A1n and b14 foods, eat b11, b12, b13, b15...b1n and B11, c12 foods appropriately, eat more B13, B14...B1n and A11, A13 foods, must eat c11, c13...c1n foods;

[0075] S32: If in the second stage of the patient's recovery: blood sugar, blood pressure, blood lipids exceed the set range, then avoid eating a21, a22, a23...a2n and A22, b21 foods, eat less A21, A23...A2n and b24, B21 foods, eat b22, b23, b25...b2n foods appropriately, eat more B22, B24...B2n and c24 foods, and must eat c21, c22, c23, c25...c2n and B23 foods; similarly, the doctor sets the food taboos and intake amounts when the blood sugar, blood pressure, and blood lipids in the second stage of recovery are lower than the set range, and similarly sets the changes in food taboos and intake amounts corresponding to the changes in the physical sign range in the third stage of recovery. In the rehabilitation control platform of the transmission layer, all the above data are stored in the cloud database in the form of a matrix, and the matrix diagonal, the first row, and the first column are marked.

[0076] Step 4: The patient uses the physical layer's physical sign detection equipment to measure physical sign information. The rehabilitation control platform analyzes the patient's physical sign information and intelligently controls food taboos and food intake during the rehabilitation stage. The transport layer sends the analysis results to the session layer.

[0077] In an embodiment of the present invention, the patient uses a vital sign detection device deployed in the physical layer to measure the size of his or her various vital sign parameters: blood sugar k, blood pressure L, and blood lipid m. After the detection device measures all the vital sign data of the patient, it uploads the data to the transmission layer. The rehabilitation control platform of the transmission layer converts the patient's vital sign information data into a matrix {B}. The platform then converts the information data of different food taboos and food intake corresponding to different rehabilitation stages set by the doctor for the patient into a matrix {A}. The platform compares the matrix {B} with {A} through the marked diagonal, first row, and first column of the matrix {A}, fills the row and column elements of the matrix {B} that are not in the matrix {A} with 1, and obtains the matrix {C}. The {C} and {A} matrices are multiplied and then transposed to obtain {CA}. T , and then calculate the inverse matrix of the matrix {A} -1 , change {CA} T Matrix and {A} -1 By comparing the elements of each row and column in the matrix, the matrix {CA} T λ, analyze each element of the matrix {C} one by one according to λ, and finally solve that in the rehabilitation stage N, the patient should avoid eating aN1, aN2, aN3, AN2, AN4, bN1, BN2 foods, eat less AN1, AN5, bN3, BN5, cN2 foods, eat bN2, bN4, bN5, aN4, AN6 foods appropriately, eat more BN1, BN3, AN3 foods, and must eat cN1, cN3, cN4, bN6 foods. The results solved by the rehabilitation control platform are sent to the session layer, and the patient can check on the APP which stage of rehabilitation he is in that day, what foods he is forbidden to eat, and the amount of food intake;

[0078] Compared with the existing smart medical cloud computing systems on the market, this system uses matrix operation technology to convert all the food taboos and food intake information data corresponding to the patient's different recovery stages into the determinant of the matrix, and then solves the patient's actual food taboos, food intake, and recovery stage for the day based on the patient's daily physical sign information matrix. It is no longer just that the patient enters what disease he has on the system and blindly checks his food taboos and food recommendations. It is truly refined to every day according to the patient's actual situation, and informs the patient of the day's food taboos and food recommendations.

[0079] Embodiment 2: Embodiment 2 of the present invention provides a smart medical cloud computing system. Figure 2 The module composition diagram of the smart medical cloud computing system provided in the second embodiment of the present invention is as follows: Figure 2 As shown, the system includes:

[0080] The session layer is used to provide a deployment environment for the APP and interact with the transport layer for data;

[0081] The transport layer is used to provide a deployment environment for the cloud platform and cloud database, and to transfer various data to the upper and lower layers;

[0082] The physical layer is used to provide a deployment environment for each hardware device node, send data to the upper layer, and receive data sent by the upper layer;

[0083] In some embodiments of the present invention, the session layer includes:

[0084] Patient-side APP is used for patients to check their daily food taboos, food intake, and recovery stage;

[0085] The doctor-side APP is used to set the food taboos and food intake corresponding to each recovery stage, and to set the corresponding changes in food taboos and food intake when the physical sign parameters change abnormally;

[0086] In some embodiments of the present invention, the transport layer includes:

[0087] The rehabilitation control platform is used to convert the data sent from the session layer and the physical layer into the determinant of the matrix. Based on the patient's physical signs, it can determine the patient's actual daily dietary restrictions, food intake, and rehabilitation stage.

[0088] Cloud database, which stores and retains various system data;

[0089] In some embodiments of the present invention, the physical layer includes:

[0090] Vital sign detection equipment is used to detect the patient's daily vital sign parameters and report the parameter information to the rehabilitation control platform of the transmission layer.

[0091] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0092] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A smart medical response method based on big data, characterized by: The method comprises the following steps: Step 1: Develop a C / S architecture system, deploy doctor-patient APP at the session layer, use HTTP protocol at the network layer, build a rehabilitation control platform and cloud database at the transport layer, and access vital sign detection equipment at the physical layer; Step 2: The doctor sets the patient's recovery stage, food restrictions, blood sugar, blood pressure, and blood lipid parameter ranges to the transport layer at the session layer, and the patient views the information stored in the transport layer at the session layer; Step 3: The doctor sets the high and low vital sign parameters to the transmission layer at the session layer, corresponding to the food intake at different recovery stages; Step 4: The patient uses the physical layer's physical sign detection equipment to measure physical sign information. The rehabilitation control platform analyzes the patient's physical sign information and intelligently controls food taboos and food intake during the rehabilitation stage. The transport layer sends the analysis results to the session layer. The steps of developing a C / S architecture system, deploying a doctor-patient APP at the session layer, using the HTTP protocol at the network layer, building a rehabilitation control platform and a cloud database at the transport layer, and accessing a vital sign detection device at the physical layer include: The system is mainly developed and deployed based on the Client / Server architecture; Deploy doctor-patient APP at the session layer; Build a rehabilitation control platform and cloud database at the transport layer; The data exchange between the session layer and the transport layer is mainly through the use of HTTP protocol as the main communication protocol in the network layer; Access vital sign detection equipment at the physical layer; The data exchange between the physical layer and the transport layer is mainly through the use of TCP / UDP protocol as the main communication protocol in the network layer; Multiple vital sign detection devices are networked at the physical layer to form nodes. Multiple detection devices within the node share detection data and report data uniformly. The doctor sets the patient's recovery stage, food taboos, blood sugar, blood pressure, and blood lipid parameter ranges to the transport layer at the session layer, and the patient views the various information stored in the transport layer at the session layer, including: Doctors use the doctor-patient APP at the conversation layer to set the patient's rehabilitation stage, food taboos, blood sugar, blood pressure, and blood lipid parameter ranges to the rehabilitation control platform based on each patient's illness, physical condition, and body characteristics; The setting method is: During the first stage of recovery: Avoid eating a11, a12, a13...a1n foods, eat less A11, A12, A13...A1n foods, eat b11, b12, b13...b1n foods appropriately, eat more B11, B12, B13...B1n foods, must eat c11, c12, c13...c1n foods, control blood sugar concentration within the range of k11-k12, mg / dL, control blood pressure within the range of L11-L12, mmHg, control blood lipids within the range of m11-m12, mmol / L; In the second stage of patient recovery: Avoid eating a21, a22, d23...a2n foods, eat less A21, A22, A23...A2n foods, eat b21, b22, b23...b2n foods appropriately, eat more B21, B22, B23...B2n foods, must eat c21, c22, c23...c2n foods, control blood sugar concentration within the range of k21-k22, mg / dL, control blood pressure within the range of L21-L22, mmHg, control blood lipids within the range of m21-m22, mmol / L; There are three stages of patient recovery: Avoid eating a31, a32, a33...a3n foods, eat less A31, A32, A33...A3n foods, eat b31, b32, b33...b3n foods appropriately, eat more B31, B32, B33...B3n foods, must eat c31, c32, c33...c3n foods, control blood sugar concentration within the range of k31-k32, mg / dL, control blood pressure within the range of L31-L32, mmHg, control blood lipids within the range of m31-m32, mmol / L; The doctor sets the level of the physical sign parameters to the transmission layer at the session layer, and the steps of corresponding food intake and food taboos at different recovery stages include: The doctor, at the session layer, sets the high and low ranges of the physical sign parameters corresponding to the food intake at different recovery stages to the rehabilitation control platform at the transmission layer in the following manner: If during the first stage of recovery: Blood glucose concentration range exceeds: k11-k12, mg / dL, blood pressure range exceeds: L11-L12, mmHg, blood lipid range exceeds: m11-m12, mmol / L; Then avoid eating a11, a12, a13...a1n and c13, b12 foods, eat less A11, A12, A13...A1n and c12, B13 foods, eat b11, b13, b14...b1n foods appropriately, eat more B11, B12, B14...B1n and c14 foods, and must eat c11, c15...c1n foods; If during the first stage of recovery: Blood glucose concentration range is lower than: k11-k12, mg / dL, blood pressure range is lower than: L11-L12, mmHg, blood lipid range is lower than: m11-m12, mmol / L; Avoid a11, a12, a13...a1n and B12 foods, eat less A12, A14...A1n and b14 foods, eat b11, b12, b13, b15...b1n and B11, c12 foods appropriately, eat more B13, B14...B1n and A11, A13 foods, and must eat c11, c13...c1n foods; The steps of setting food intake and food taboos at different recovery stages include: If in the second stage of patient recovery: If blood sugar, blood pressure and blood lipids exceed the set range, avoid eating a21, a22, a23...a2n and A22, b21 foods, eat less A21, A23...A2n and b24, B21 foods, eat b22, b23, b25...b2n foods appropriately, eat more B22, B24...B2n and c24 foods, and must eat c21, c22, c23, c25...c2n and B23 foods; Similarly, doctors set food taboos and intake limits for blood sugar, blood pressure, and blood lipids in the second stage of recovery when they are below the set range; Similarly, the changes in food taboos and intake corresponding to the changes in the range of physical signs in the three stages of recovery are set; In the rehabilitation control platform of the transmission layer, all the above data are stored in the cloud database in the form of a matrix, and the diagonal line, the first row and the first column of the matrix are marked; The patient uses a physical layer physical sign detection device to measure physical sign information, the rehabilitation control platform analyzes the patient's physical sign information, and intelligently controls food taboos and food intake during the rehabilitation stage, and the transport layer sends the analysis results to the session layer, including: Patients use the vital sign detection equipment deployed at the physical layer to measure the size of their various vital sign parameters: Blood sugar k, blood pressure L, blood lipid m; After the detection equipment measures all the patient's vital signs, it uploads the data to the transmission layer; In the rehabilitation control platform of the transmission layer, the patient's vital sign information data is converted into a matrix {B}; The platform then converts the information data of different food taboos and food intake corresponding to different recovery stages set by the doctor for the patient into a matrix {A}; The platform compares matrix {B} with {A} by marking the diagonal, first row, and first column of matrix {A}, and fills the row and column elements of matrix {A} that are not in matrix {B} with 1 to obtain matrix {C}; Multiply the {C} and {A} matrices and then transpose them to get {CA} T ; Then calculate the inverse matrix of the matrix {A} -1 , change {CA} T Matrix and {A} -1 By comparing the elements of each row and column in the matrix, the matrix {CA} T λ; According to λ, each element of the matrix {C} is analyzed one by one, and finally the solution is: During the recovery 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 appropriately, eat more BN1, BN3, and AN3 foods, and must eat cN1, cN3, cN4, and bN6 foods because their blood sugar k is higher / lower / normal than the set range, their blood pressure L is higher / lower / normal than the set range, and their blood lipid m is higher / lower / normal than the set range. The results obtained by the rehabilitation control platform are sent to the session layer; Patients can check on the APP which stage of recovery they are in that day, what foods they are forbidden to eat, and how much food they eat; The system comprises: The session layer is used to provide a deployment environment for the APP and interact with the transport layer for data; The transport layer is used to provide a deployment environment for the cloud platform and cloud database, and to transfer various data to the upper and lower layers; The physical layer is used to provide a deployment environment for each hardware device node, send data to the upper layer, and receive data sent by the upper layer; The session layer includes: Patient-side APP is used for patients to check their daily food taboos, food intake, and recovery stage; The doctor-side APP is used to set the food taboos and food intake corresponding to each recovery stage, and to set the corresponding changes in food taboos and food intake when the physical sign parameters change abnormally; The transport layer includes: The rehabilitation control platform is used to convert the data sent from the session layer and the physical layer into the determinant of the matrix. Based on the patient's physical signs, it can determine the patient's actual daily dietary restrictions, food intake, and rehabilitation stage. Cloud database, which stores and retains various system data; The physical layer includes: The vital sign detection equipment is used to detect the patient's daily vital sign parameters, blood pressure, blood sugar concentration, and blood lipid parameter information, and report the parameter information to the rehabilitation control platform of the transmission layer.

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