A method and device for monitoring hemodynamics of experimental animals

Abstract

The present invention discloses a hemodynamic monitoring method and device for experimental animals, the method comprising: obtaining a hemodynamic parameter set of the experimental animal before skin transplantation and a hemodynamic parameter set after skin transplantation; performing statistical data processing on the hemodynamic parameter set before skin transplantation and the hemodynamic parameter set after skin transplantation to obtain a first statistical data set and a second statistical data set; performing comprehensive evaluation processing on the hemodynamic parameter set after skin transplantation, the first statistical data set and the second statistical data set to obtain the vital sign detection result value of the experimental animal. The present invention realizes an effective evaluation of the health status of the experimental animal after skin transplantation by fusion analysis of the blood flow stability analysis result and the difference analysis result of the experimental animal.

Description

Technical Field

[0001] The invention relates to the fields of health monitoring and skin transplantation, and in particular to a hemodynamic monitoring method and device for experimental animals. Background Art

[0002] In the field of skin transplantation, in order to verify the safety of skin transplantation methods, it is necessary to monitor the health status of users after skin transplantation. Early trials of skin transplantation methods are often completed by using animal experiments. The safety of skin transplantation methods is evaluated by monitoring the vital signs of experimental animals, such as experimental mice, before and after skin transplantation. In the process of animal testing, richer blood characteristic parameters than those of the human body can be obtained. How to effectively evaluate the status of the experimental animals after skin transplantation based on the blood characteristic parameters obtained from the experimental animals is a problem that needs to be solved urgently. Summary of the invention

[0003] The present invention mainly solves the existing problem of how to effectively evaluate the state of a test animal after skin transplantation based on the obtained blood characteristic parameters of the test animal. The present invention discloses a hemodynamic monitoring method and device for test animals.

[0004] In a first aspect of the embodiments of the present application, a hemodynamic monitoring method for experimental animals is disclosed, comprising:

[0005] S1, obtaining a set of hemodynamic parameters of the experimental animal before skin transplantation and a set of hemodynamic parameters after skin transplantation; the set of hemodynamic parameters includes a blood pressure data sequence, a blood flow velocity data sequence, a blood flow volume data sequence, a heart rate data sequence, a pulse data sequence, and a blood oxygen data sequence;

[0006] S2, performing statistical processing on the hemodynamic parameter set before skin transplantation and the hemodynamic parameter set after skin transplantation to obtain a first statistical data set and a second statistical data set;

[0007] S3, comprehensively evaluating and processing the hemodynamic parameter set, the first statistical data set and the second statistical data set after the skin transplantation to obtain the vital sign detection result values ​​of the experimental animals.

[0008] The data statistical processing is to obtain the median, mode, range, mean, variance, and quartile of each type of data sequence of the hemodynamic parameter set, and to construct a statistical value sequence corresponding to the data sequence using the median, mode, range, mean, variance, and quartile of each type of data sequence;

[0009] The first statistical data set includes a statistical value sequence corresponding to each data sequence of the hemodynamic parameter set before skin transplantation;

[0010] The second statistical data set includes a statistical value sequence corresponding to each data sequence of the hemodynamic parameter set after skin transplantation.

[0011] The comprehensive evaluation and processing of the hemodynamic parameter set, the first statistical data set and the second statistical data set after the skin transplantation to obtain the vital sign detection result value of the experimental animal includes:

[0012] S31, performing a stability evaluation process on the hemodynamic parameter set after the skin transplantation to obtain a first evaluation result;

[0013] S32, performing difference evaluation processing on the first statistical data set and the second statistical data set to obtain a second evaluation result;

[0014] S33, performing weighted sum processing on the first evaluation result and the second evaluation result to obtain the vital sign detection result value of the experimental animal.

[0015] The step of performing a stability evaluation process on the hemodynamic parameter set after the skin transplantation to obtain a first evaluation result includes:

[0016] S311, calculating the median and mode of each data sequence of the hemodynamic parameter set after skin transplantation, constructing a mode vector using all the modes, and normalizing the mode vector to obtain a normalized mode vector;

[0017] S312, constructing a hemodynamic matrix using the hemodynamic parameter set after skin transplantation; the row vector of the hemodynamic matrix is ​​a data sequence of the hemodynamic parameter set after skin transplantation;

[0018] S313, performing dynamic modeling processing on the hemodynamic matrix to obtain a dynamic approximation polynomial;

[0019] S314, performing deviation analysis on the hemodynamic matrix to obtain a deviation sequence value set;

[0020] S315, performing weighted summation on the deviation sequence number value set and the normalized mode vector to obtain a first evaluation result.

[0021] The performing dynamic modeling processing on the hemodynamic matrix to obtain a dynamic approximation polynomial includes:

[0022] S3131, decomposing the hemodynamic matrix to obtain a left decomposition matrix, a characteristic matrix and a right decomposition matrix; the decomposition process is calculated as follows:

[0023] ,

[0024] in, is the left decomposition matrix, Y is the hemodynamic matrix, is the feature matrix, is the right factorization matrix, and are all orthogonal matrices, is a diagonal matrix

[0025] S3132, extracting the diagonal elements of the feature matrix to obtain a feature vector;

[0026] S3133, performing linear fitting processing on the elements and element sequence numbers of the characteristic vector to obtain a dynamic approximation polynomial.

[0027] The performing deviation analysis on the hemodynamic matrix to obtain a deviation sequence value set includes:

[0028] S3141, for each element in the row vector of the hemodynamic matrix, calculate its corresponding median The absolute value of the difference is determined as the offset of the element;

[0029] S3142, for each row vector of the hemodynamic matrix, find an element with a maximum offset, and determine the sequence number of the element in the row vector as the deviation sequence number of the row vector;

[0030] S3143, constructing a deviation sequence number value set using the deviation sequence number values ​​of all row vectors of the hemodynamic matrix.

[0031] The performing difference evaluation processing on the first statistical data set and the second statistical data set to obtain a second evaluation result includes:

[0032] S321, representing the first statistical data set and the second statistical data set as a first data matrix and a second data matrix, respectively; the row vectors of the first data matrix are the statistical value sequences corresponding to the data sequences of the hemodynamic parameter set before the skin transplantation; the row vectors of the second data matrix are the statistical value sequences corresponding to the data sequences of the hemodynamic parameter set after the skin transplantation;

[0033] S322, subtracting the first data matrix from the second data matrix to obtain a difference matrix;

[0034] S323, performing a first feature sequence extraction process and a second feature sequence extraction process on the difference matrix to obtain a first feature sequence and a second feature sequence respectively;

[0035] S324, performing feature distance calculation processing on the first feature sequence and the second feature sequence to obtain a second evaluation result.

[0036] In a second aspect of the embodiment of the present application, a hemodynamic monitoring device for experimental animals is disclosed, the device comprising:

[0037] A memory storing executable program code;

[0038] a processor coupled to the memory;

[0039] The processor calls the executable program code stored in the memory to execute the hemodynamic monitoring method for experimental animals.

[0040] In a third aspect of the embodiments of the present application, a computer storable medium is disclosed, wherein the computer storable medium stores computer instructions, and when the computer instructions are called by a computer, they are used to execute the hemodynamic monitoring method for experimental animals.

[0041] In a fourth aspect of the embodiments of the present application, an information data processing terminal is disclosed, wherein the information data processing terminal is used to implement the hemodynamic monitoring method for experimental animals.

[0042] The beneficial effects of the present invention are:

[0043] The present invention makes full use of the diversity of blood flow data collected in animal experiments, uses blood pressure data, blood flow velocity data, blood flow volume data, heart rate data, pulse data, and blood oxygen data to establish a hemodynamic matrix, performs dynamic modeling processing, obtains a dynamic approximation polynomial, and realizes the stability evaluation processing of the hemodynamic parameters of animals after skin transplantation.

[0044] The present invention collects blood flow data before and after skin transplantation, obtains diversified feature vectors by extraction, and realizes differential analysis of the blood flow data before and after skin transplantation by using the feature distance of the feature vector, thereby obtaining accurate and comprehensive blood flow analysis results.

[0045] The present invention realizes effective evaluation of the health status of the experimental animal after skin transplantation by fusing the analysis results of the stability of the blood flow of the experimental animal and the difference analysis results. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 It is a flow chart for implementing the method of the present invention. DETAILED DESCRIPTION

[0047] In order to better understand the content of the present invention, an embodiment is given here.

[0048] Figure 1 It is a flow chart for implementing the method of the present invention.

[0049] In order to solve the problem of how to effectively evaluate the state of the experimental animal after skin transplantation based on the obtained blood characteristic parameters of the experimental animal, the present invention discloses a hemodynamic monitoring method and device for the experimental animal.

[0050] In a first aspect of the embodiments of the present application, a hemodynamic monitoring method for experimental animals is disclosed, comprising:

[0051] S1, obtaining a set of hemodynamic parameters of the experimental animal before skin transplantation and a set of hemodynamic parameters after skin transplantation; the set of hemodynamic parameters includes a blood pressure data sequence, a blood flow velocity data sequence, a blood flow volume data sequence, a heart rate data sequence, a pulse data sequence, and a blood oxygen data sequence;

[0052] S2, performing statistical processing on the hemodynamic parameter set before skin transplantation and the hemodynamic parameter set after skin transplantation to obtain a first statistical data set and a second statistical data set;

[0053] S3, comprehensively evaluating and processing the hemodynamic parameter set, the first statistical data set and the second statistical data set after the skin transplantation to obtain the vital sign detection result values ​​of the experimental animals.

[0054] The data statistical processing is to obtain the median, mode, range, mean, variance and quartile of each type of data sequence of the hemodynamic parameter set, and construct a statistical value sequence corresponding to the data sequence using the median, mode, range, mean, variance and quartile of each type of data sequence;

[0055] The first statistical data set includes a statistical value sequence corresponding to each data sequence before the skin transplantation;

[0056] The second statistical data set includes a statistical value sequence corresponding to each data sequence after the skin transplantation;

[0057] The comprehensive evaluation and processing of the hemodynamic parameter set, the first statistical data set and the second statistical data set after the skin transplantation to obtain the vital sign detection result value of the experimental animal includes:

[0058] S31, performing a stability evaluation process on the hemodynamic parameter set after the skin transplantation to obtain a first evaluation result;

[0059] S32, performing difference evaluation processing on the first statistical data set and the second statistical data set to obtain a second evaluation result;

[0060] S33, performing weighted sum processing on the first evaluation result and the second evaluation result to obtain a vital sign detection result value of the test animal;

[0061] The step of performing a stability evaluation process on the hemodynamic parameter set after the skin transplantation to obtain a first evaluation result includes:

[0062] S311, calculating the median and mode of each data sequence of the hemodynamic parameter set after skin transplantation, constructing a mode vector using all the modes, and normalizing the mode vector to obtain a normalized mode vector;

[0063] S312, constructing a hemodynamic matrix using the hemodynamic parameter set after skin transplantation; the row vector of the hemodynamic matrix is ​​a data sequence of the hemodynamic parameter set after skin transplantation;

[0064] S313, performing dynamic modeling processing on the hemodynamic matrix to obtain a dynamic approximation polynomial;

[0065] S314, performing deviation analysis on the hemodynamic matrix to obtain a deviation sequence value set;

[0066] S315, performing weighted summation using the deviation sequence value set and the normalized mode vector to obtain a first evaluation result;

[0067] The performing dynamic modeling processing on the hemodynamic matrix to obtain a dynamic approximation polynomial includes:

[0068] S3131, decomposing the hemodynamic matrix to obtain a left decomposition matrix, a characteristic matrix and a right decomposition matrix;

[0069] S3132, extracting the diagonal elements of the feature matrix to obtain a feature vector;

[0070] S3133, performing linear fitting processing on the elements and element sequence values ​​of the characteristic vector to obtain a dynamic approximation polynomial;

[0071] The decomposition process is calculated as follows:

[0072] ,

[0073] in, is the left decomposition matrix, Y is the hemodynamic matrix, is the feature matrix, is the right factorization matrix, and are all orthogonal matrices, is a diagonal matrix;

[0074] The performing deviation analysis on the hemodynamic matrix to obtain a deviation sequence value set includes:

[0075] S3141, for each element in the row vector of the hemodynamic matrix, calculate its corresponding median The absolute value of the difference is determined as the offset of the element;

[0076] S3142, for each row vector of the hemodynamic matrix, find an element with a maximum offset, and determine the sequence number of the element in the row vector as the deviation sequence number of the row vector;

[0077] S3143, constructing a deviation sequence number value set using the deviation sequence number values ​​of all row vectors of the hemodynamic matrix.

[0078] The performing difference evaluation processing on the first statistical data set and the second statistical data set to obtain a second evaluation result includes:

[0079] Representing the first statistical data set and the second statistical data set as a first data matrix and a second data matrix, respectively;

[0080] Subtracting the first data matrix from the second data matrix to obtain a difference matrix;

[0081] Performing a first feature sequence extraction process and a second feature sequence extraction process on the difference matrix to obtain a first feature sequence and a second feature sequence respectively;

[0082] A feature distance calculation process is performed on the first feature sequence and the second feature sequence to obtain a second evaluation result.

[0083] The first feature sequence extraction process is to extract the largest number in each column to form the first feature sequence ; The expression of the first characteristic sequence is:

[0084] ,

[0085] Among them, m and n are the row and column dimensions of the difference matrix respectively, is the element in the i-th row and j-th column of the difference matrix;

[0086] The second feature sequence extraction process is to extract the smallest number in each column to form the second feature sequence ; The expression of the second characteristic sequence is:

[0087] ,

[0088] The expression for the feature distance calculation process is:

[0089] ,

[0090] In the formula, is the second evaluation result, For the preset j Importance weights; , obtained by presetting, or by calculating the variance of each column of the difference matrix;

[0091] The method of performing weighted summation of the deviation sequence number set and the normalized mode vector to obtain the first evaluation result is to multiply the deviation sequence number value corresponding to each row by the normalized mode of the row to obtain the product, and then add all the products to obtain the first evaluation result;

[0092] For example, in the hemodynamic matrix, the row vector In the elements For the element with the largest offset, the sequence number value is determined to be j.

[0093] The decomposition process can be implemented by using a matrix singular value decomposition algorithm.

[0094] The linear fitting process is based on the characteristic vector element number value The known independent variable is taken as the known dependent variable, the element value of the eigenvector is taken as the known dependent variable, the known independent variable and the known dependent variable are used to construct the curve to be approximated, and the function approximation method is used to perform curve fitting on the curve to be approximated to obtain a dynamic approximation polynomial.

[0095] The feature vector is expressed as , , is the number of elements contained in the characteristic vector; the curve fitting of the curve to be approximated by using the function approximation method can adopt the best consistent linear approximation method. The dynamic approximation polynomial , whose expression is:

[0096] ,

[0097] in, Approximating the dynamics polynomial The order of Approximating the dynamics polynomial The coefficient of

[0098] The first evaluation result and the second evaluation result are weighted and summed to obtain the vital sign detection result value of the experimental animal, and the weight value thereof may be [0.5, 0.5] or [0.4, 0.6].

[0099] In a second aspect of the embodiment of the present application, a hemodynamic monitoring device for experimental animals is disclosed, the device comprising:

[0100] A memory storing executable program code;

[0101] a processor coupled to the memory;

[0102] The processor calls the executable program code stored in the memory to execute the hemodynamic monitoring method for experimental animals.

[0103] In a third aspect of the embodiments of the present application, a computer storable medium is disclosed, wherein the computer storable medium stores computer instructions, and when the computer instructions are called by a computer, they are used to execute the hemodynamic monitoring method for experimental animals.

[0104] In a fourth aspect of the embodiments of the present application, an information data processing terminal is disclosed, wherein the information data processing terminal is used to implement the hemodynamic monitoring method for experimental animals.

[0105] In a fifth aspect of the embodiments of the present application, a hemodynamic monitoring device for experimental animals is disclosed, comprising a sensor module and a monitoring module;

[0106] The sensor module includes a blood flow patch sensor and an ultrasonic sensor, which are used to collect a set of hemodynamic parameters of the experimental animal before skin transplantation and a set of hemodynamic parameters after skin transplantation; the set of hemodynamic parameters includes a blood pressure data sequence, a blood flow velocity data sequence, a blood flow volume data sequence, a heart rate data sequence, a pulse data sequence and a blood oxygen data sequence, and all the collected data sequences are sent to the monitoring module;

[0107] The monitoring module is used to perform data statistical processing on the hemodynamic parameter set before the skin transplantation and the hemodynamic parameter set after the skin transplantation, respectively, to obtain a first statistical data set and a second statistical data set; and to perform comprehensive evaluation processing on the hemodynamic parameter set after the skin transplantation, the first statistical data set and the second statistical data set to obtain the vital sign detection result values ​​of the experimental animals.

[0108] The above description is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent substitution, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A method for monitoring hemodynamics in experimental animals, characterized in that: include: S1, obtaining a set of hemodynamic parameters of the experimental animal before skin transplantation and a set of hemodynamic parameters after skin transplantation; the set of hemodynamic parameters includes a blood pressure data sequence, a blood flow velocity data sequence, a blood flow volume data sequence, a heart rate data sequence, a pulse data sequence, and a blood oxygen data sequence; S2, performing statistical processing on the hemodynamic parameter set before skin transplantation and the hemodynamic parameter set after skin transplantation to obtain a first statistical data set and a second statistical data set; S3, performing comprehensive evaluation processing on the hemodynamic parameter set after the skin transplantation, the first statistical data set, and the second statistical data set to obtain the vital sign detection result value of the experimental animal; The comprehensive evaluation and processing of the hemodynamic parameter set, the first statistical data set and the second statistical data set after the skin transplantation to obtain the vital sign detection result value of the experimental animal includes: S31, performing a stability evaluation process on the hemodynamic parameter set after the skin transplantation to obtain a first evaluation result; S32, performing difference evaluation processing on the first statistical data set and the second statistical data set to obtain a second evaluation result; S33, performing weighted sum processing on the first evaluation result and the second evaluation result to obtain a vital sign detection result value of the test animal; The step of performing a stability evaluation process on the hemodynamic parameter set after the skin transplantation to obtain a first evaluation result includes: S311, calculating the median and mode of each data sequence of the hemodynamic parameter set after skin transplantation, constructing a mode vector using all the modes, and normalizing the mode vector to obtain a normalized mode vector; S312, constructing a hemodynamic matrix using the hemodynamic parameter set after skin transplantation; the row vector of the hemodynamic matrix is ​​a data sequence of the hemodynamic parameter set after skin transplantation; S313, performing dynamic modeling processing on the hemodynamic matrix to obtain a dynamic approximation polynomial; S314, performing deviation analysis on the hemodynamic matrix to obtain a deviation sequence value set; S315, performing weighted summation using the deviation sequence value set and the normalized mode vector to obtain a first evaluation result; The performing dynamic modeling processing on the hemodynamic matrix to obtain a dynamic approximation polynomial includes: S3131, decomposing the hemodynamic matrix to obtain a left decomposition matrix, a characteristic matrix and a right decomposition matrix; the decomposition process is calculated as follows: ， in, is the left decomposition matrix, Y is the hemodynamic matrix, is the feature matrix, is the right factorization matrix, and are all orthogonal matrices, is a diagonal matrix S3132, extracting the diagonal elements of the feature matrix to obtain a feature vector; S3133, performing linear fitting processing on the elements and element sequence numbers of the characteristic vector to obtain a dynamic approximation polynomial.

2. The hemodynamic monitoring method for experimental animals according to claim 1, characterized in that: The data statistical processing is to obtain the median, mode, range, mean, variance, and quartile of each type of data sequence of the hemodynamic parameter set, and to construct a statistical value sequence corresponding to the data sequence using the median, mode, range, mean, variance, and quartile of each type of data sequence; The first statistical data set includes a statistical value sequence corresponding to each data sequence of the hemodynamic parameter set before skin transplantation; The second statistical data set includes a statistical value sequence corresponding to each data sequence of the hemodynamic parameter set after skin transplantation.

3. The hemodynamic monitoring method for experimental animals according to claim 1, characterized in that: The performing deviation analysis on the hemodynamic matrix to obtain a deviation sequence value set includes: S3141, for each element in the row vector of the hemodynamic matrix, calculate its corresponding median The absolute value of the difference is determined as the offset of the element; S3142, for each row vector of the hemodynamic matrix, find an element with a maximum offset, and determine the sequence number of the element in the row vector as the deviation sequence number of the row vector; S3143, constructing a deviation sequence number value set using the deviation sequence number values ​​of all row vectors of the hemodynamic matrix.

4. The hemodynamic monitoring method for experimental animals according to claim 1, characterized in that: The performing difference evaluation processing on the first statistical data set and the second statistical data set to obtain a second evaluation result includes: S321, representing the first statistical data set and the second statistical data set as a first data matrix and a second data matrix, respectively; the row vectors of the first data matrix are the statistical value sequences corresponding to the data sequences of the hemodynamic parameter set before the skin transplantation; the row vectors of the second data matrix are the statistical value sequences corresponding to the data sequences of the hemodynamic parameter set after the skin transplantation; S322, subtracting the first data matrix from the second data matrix to obtain a difference matrix; S323, performing a first feature sequence extraction process and a second feature sequence extraction process on the difference matrix to obtain a first feature sequence and a second feature sequence respectively; S324, performing feature distance calculation processing on the first feature sequence and the second feature sequence to obtain a second evaluation result.

5. A hemodynamic monitoring device for experimental animals, characterized in that: The device comprises: A memory storing executable program code; a processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the hemodynamic monitoring method for experimental animals according to any one of claims 1 to 4.

6. A computer storable medium, characterized in that: The computer storable medium stores computer instructions, and when the computer instructions are called by a computer, they are used to execute the hemodynamic monitoring method for experimental animals according to any one of claims 1 to 4.

7. An information data processing terminal, characterized in that: The information data processing terminal is used to implement the hemodynamic monitoring method for experimental animals as described in any one of claims 1 to 4.

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