An osteoporosis treatment device and feedback method based on the fusion of vibration and magnetic field

Abstract

The present invention discloses an osteoporosis treatment device and a feedback method based on the fusion of vibration and magnetic field. The device includes: an electromagnetic field generator, a low-frequency vibration foot pedal, a vertical bracket, a physiological acquisition module, a control module, and an armrest. The physiological acquisition module is used to collect a set of physiological parameter information of a user during the process of using the osteoporosis treatment device for osteoporosis treatment. The electromagnetic field generator is slidably connected to the vertical bracket, generates an electromagnetic field for osteoporosis treatment, and measures a set of magnetic field information. The low-frequency vibration foot pedal is arranged at the lower part of the vertical bracket and is used to generate vibration for osteoporosis treatment according to vibration command information. The control module is used to perform feedback calculation and processing on the set of physiological parameter information and the set of magnetic field information to obtain magnetic field command information and vibration command information.

Description

Technical Field

[0001] The present invention relates to the field of orthopedic medicine and signal processing, and particularly to an osteoporosis treatment device and feedback method based on the fusion of vibration and magnetic field. Background Art

[0002] Osteoporosis is a systemic bone disease caused by various reasons, resulting in a decrease in bone density and bone mass, destruction of bone microstructure, increased bone fragility, and thus prone to fractures. Vibration therapy and magnetic therapy are two commonly used physical therapy methods for osteoporosis.

[0003] Vibration therapy provides vibration by a low-frequency vibration foot pedal to apply mechanical stimulation to the user, which can well control the frequency and intensity and play a good mechanical stimulation role on the bones; the pulsed electromagnetic field provided by the electromagnetic field generator can enhance bone metabolism, and its stimulating effect on osteoblasts is stronger than that on osteoclasts, increasing the expression of osteogenic factors in the body and playing a good preventive and therapeutic effect on osteoporosis.

[0004] In existing osteoporosis treatment devices, most adopt a single treatment method, lacking the fusion of multiple treatment methods and the adjustment of treatment factors according to the user's reaction, which affects the treatment effect and efficiency. Summary of the Invention

[0005] The present invention mainly solves the problems of single treatment method and lack of feedback in existing osteoporosis treatment devices, and discloses an osteoporosis treatment device and feedback method based on the fusion of vibration and magnetic field.

[0006] In the first aspect of the embodiments of the present invention, an osteoporosis treatment device based on the fusion of vibration and magnetic field is disclosed, including: an electromagnetic field generator, a low-frequency vibration foot pedal, a vertical bracket, a physiological acquisition module, a control module, and an armrest;

[0007] The physiological acquisition module is used to collect a set of physiological parameter information of the user during the osteoporosis treatment using the osteoporosis treatment device; the set of physiological parameter information includes a body temperature information sequence, a pulse information sequence, a blood pressure information sequence, and a blood oxygen saturation information sequence:

[0008] The electromagnetic field generator is slidably connected to the vertical bracket and is used to generate an electromagnetic field for osteoporosis treatment according to magnetic field command information and measure a set of magnetic field information;

[0009] The low-frequency vibration foot pedal is arranged at the lower part of the vertical bracket and is used to generate vibration for osteoporosis treatment according to vibration command information;

[0010] The control module is respectively connected to the electromagnetic field generator, the low-frequency vibration foot pedal, and the physiological acquisition module, and is configured to perform feedback calculation processing on the physiological parameter information set and the magnetic field information set to obtain magnetic field command information and vibration command information;

[0011] The armrest is arranged at the upper part of the vertical bracket; the physiological acquisition module is arranged on the armrest.

[0012] The control module performs feedback calculation processing on the physiological parameter information set and the magnetic field information set to obtain magnetic field command information and vibration command information, including:

[0013] Performing preprocessing on the physiological parameter information set and the magnetic field information set to obtain a preprocessing parameter information set;

[0014] Performing magnetic field feedback calculation processing on the preprocessing parameter information set to obtain magnetic field command information;

[0015] Performing vibration feedback calculation processing on the preprocessing parameter information set to obtain vibration command information.

[0016] The electromagnetic field generator includes a control unit, a magnetic field coil, a magnetic induction intensity sensor, a current sensor, and a voltage sensor; a magnetic induction intensity sensor is arranged inside the magnetic field coil, and the magnetic field coil is connected with a current sensor and a voltage sensor;

[0017] The magnetic induction intensity sensor, the current sensor, and the voltage sensor are respectively configured to measure and obtain a magnetic induction intensity information sequence, a current information sequence, and a voltage information sequence;

[0018] The control unit is respectively connected to the magnetic field coil, the magnetic induction intensity sensor, the current sensor, and the voltage sensor, and is configured to change the voltage and current of the magnetic field coil according to the magnetic field command information, collect a magnetic field information set, and send the magnetic field information set to the control module;

[0019] The magnetic field information set includes the measured magnetic induction intensity information sequence, current information sequence, and voltage information sequence.

[0020] In a second aspect of the embodiments of the present invention, a feedback method for osteoporosis treatment based on the fusion of vibration and magnetic field is disclosed, which is implemented by using the osteoporosis treatment device based on the fusion of vibration and magnetic field, and includes:

[0021] S1, using the physiological acquisition module to collect a physiological parameter information set of a user during the process of using the osteoporosis treatment device for osteoporosis treatment;

[0022] S2, using the electromagnetic field generator to measure and obtain a magnetic field information set;

[0023] S3. Using the control module, perform feedback calculation and processing on the physiological parameter information set and the magnetic field information set to obtain magnetic field command information and vibration command information;

[0024] S4. According to the magnetic field command information, use the electromagnetic field generator to generate an electromagnetic field for osteoporosis treatment;

[0025] S5. According to the vibration command information, use the low-frequency vibration foot pedal to generate vibration for osteoporosis treatment.

[0026] The performing feedback calculation and processing on the physiological parameter information set and the magnetic field information set to obtain magnetic field command information and vibration command information includes:

[0027] Perform preprocessing on the physiological parameter information set and the magnetic field information set to obtain a preprocessing parameter information set;

[0028] Perform magnetic field feedback calculation and processing on the preprocessing parameter information set to obtain magnetic field command information;

[0029] Perform vibration feedback calculation and processing on the preprocessing parameter information set to obtain vibration command information.

[0030] The performing preprocessing on the physiological parameter information set and the magnetic field information set to obtain a preprocessing parameter information set includes:

[0031] Perform time alignment processing on the physiological parameter information set and the magnetic field information set to obtain a first information set;

[0032] Perform pattern discrimination processing on the first information set to obtain a preprocessing parameter information set.

[0033] The performing magnetic field feedback calculation and processing on the preprocessing parameter information set to obtain magnetic field command information includes:

[0034] Obtain a standard physiological parameter information set; the standard physiological parameter information set includes a body temperature standard value, a pulse standard value, a blood pressure standard value, and a blood oxygen saturation standard value;

[0035] Subtract the standard value of each category from each information sequence in the physiological parameter information set in the preprocessing parameter information set to obtain a difference sequence of the corresponding category;

[0036] Use the difference sequences of all categories to construct a physiological difference matrix A; the row vector of the physiological difference matrix is a difference sequence of one category;

[0037] Construct a magnetic field information matrix B using the magnetic field information set in the preprocessing parameter information set; the row vectors of the magnetic field information matrix are the magnetic induction intensity information sequence, the current information sequence, and the voltage information sequence;

[0038] Calculate the covariance matrices for the physiological difference matrix A and the magnetic field information matrix B respectively to obtain the physiological covariance matrix S A and the magnetic field covariance matrix S B ;

[0039] Calculate the cross-covariance matrix for the physiological difference matrix A and the magnetic field information matrix B to obtain the cross-covariance matrix S AB ;

[0040] Perform matrix decomposition on the physiological covariance matrix S A and the magnetic field covariance matrix S B respectively to obtain the corresponding eigenvector matrices X and Y;

[0041] Perform fusion calculation on the physiological covariance matrix S A , the magnetic field covariance matrix S B , the cross-covariance matrix S AB and the eigenvector matrix to obtain the fusion feature matrix;

[0042] Solve to obtain the eigenvalue set of the fusion feature matrix;

[0043] Sort the eigenvalue set in descending order of the values to obtain the eigenvalue sequence;

[0044] Construct magnetic field command information using the first element and the second element in the eigenvalue sequence; the magnetic field command information includes a voltage adjustment value and a current adjustment value; the first element and the second element in the eigenvalue sequence correspond to the voltage adjustment value and the current adjustment value respectively.

[0045] The expression for the fusion calculation process is:

[0046]

[0047] where T is the fusion feature matrix.

[0048] The vibration feedback calculation process for the preprocessing parameter information set to obtain vibration command information includes:

[0049] Obtain a standard physiological parameter information set; the standard physiological parameter information set includes a body temperature standard value, a pulse standard value, a blood pressure standard value, and a blood oxygen saturation standard value;

[0050] Subtract each type of information sequence in the physiological parameter information set in the preprocessing parameter information set from the standard value of the corresponding category to obtain the difference sequence of the corresponding category;

[0051] Use the difference sequences of all categories to construct a physiological difference matrix A; the row vector of the physiological difference matrix is the difference sequence of one category;

[0052] Use the magnetic field information set in the preprocessing parameter information set to construct a magnetic field information matrix B; the row vector of the magnetic field information matrix is the magnetic induction intensity information sequence, the current information sequence, and the voltage information sequence;

[0053] Perform a first eigen-transformation process on each row vector of the physiological difference matrix A to obtain a physiological transformation vector; the expression of the first eigen-transformation process is:

[0054]

[0055] where N is the column dimension of the physiological difference matrix A, A ij is the element in the i-th row and j-th column of the physiological difference matrix A, and α i is the i-th element of the physiological transformation vector,

[0056] Perform a normalized column mode process on the magnetic field information matrix B to obtain a magnetic field transformation vector;

[0057] The expression of the normalized column mode process is:

[0058]

[0059] where p i is the i-th element of the magnetic field transformation vector, b i is the mean value of the i-th row of the magnetic field information matrix B, and m is the column dimension of the magnetic field information matrix B;

[0060] Perform a feature fusion calculation process on the magnetic field transformation vector and the physiological transformation vector to obtain vibration command information.

[0061] The expression of the feature fusion calculation process is:

[0062]

[0063] where zd is the vibration command information, M1 is the length of the physiological transformation vector, M2 is the length of the magnetic field transformation vector, and L i () represents the i-th Laguerre polynomial, and T i () represents the i-th order polynomial of the first kind of Chebyshev polynomial; the vibration command information is the drive current value of the motor of the low-frequency vibration foot pedal.

[0064] The beneficial effects of the present invention are as follows:

[0065] The present invention discloses an osteoporosis treatment device and a feedback method based on the fusion of vibration and magnetic field, which solves the problems of single treatment method and lack of feedback in existing osteoporosis treatment devices.

[0066] The present invention performs feedback calculation processing on the physiological parameter information set and the magnetic field information set to obtain magnetic field command information and vibration command information, and uses the magnetic field command information and the vibration command information to perform feedback calculation processing to obtain magnetic field command information and vibration command information; in the feedback calculation processing, corresponding feedback calculation modules are respectively constructed for the physiological parameter information set and the magnetic field information set, realizing the effective extraction of corresponding types of information, suppressing irrelevant information, improving the accuracy of feedback processing, and optimizing the treatment effect.

[0067] In the magnetic field feedback calculation processing of the present invention, a fusion calculation processing algorithm is established, and a fusion feature matrix is constructed to solve the eigenvalue set of the fusion feature matrix. In the fusion calculation processing algorithm, the feature fusion of multiple types of data is realized.

[0068] When performing vibration feedback calculation processing, the present invention performs a first feature transformation processing on each row vector of the physiological difference matrix A to obtain a physiological transformation vector, and performs a normalized column mode processing on the magnetic field information matrix B to obtain a magnetic field transformation vector. Through the algorithms of the first feature transformation processing and the normalized column mode processing, the feature transformation extraction of different types of data is realized, and the accuracy of feedback processing is improved. Brief Description of the Drawings

[0069] Figure 1 It is a flowchart of the implementation of the method of the present invention. Detailed Embodiment

[0070] To better understand the content of the present invention, an embodiment is given here.

[0071] Figure 1 It is a flowchart of the implementation of the method of the present invention.

[0072] In the first aspect of the embodiment of the present invention, an osteoporosis treatment device based on the fusion of vibration and magnetic field is disclosed, including: an electromagnetic field generator, a low-frequency vibration foot pedal, a vertical bracket, a physiological acquisition module, a control module, and an armrest;

[0073] The physiological acquisition module is used to collect a set of physiological parameter information of the user during the osteoporosis treatment using the osteoporosis treatment device; the set of physiological parameter information includes a body temperature information sequence, a pulse information sequence, a blood pressure information sequence, and a blood oxygen saturation information sequence:

[0074] The electromagnetic field generator is slidably connected to the vertical bracket and is used to generate an electromagnetic field for osteoporosis treatment according to the magnetic field command information, and measure and obtain a magnetic field information set.

[0075] The low-frequency vibration footrest is arranged at the lower part of the vertical bracket and is used to generate vibration for osteoporosis treatment according to the vibration command information.

[0076] The control module is respectively connected to the electromagnetic field generator, the low-frequency vibration footrest and the physiological acquisition module, and is used to perform feedback calculation and processing on the physiological parameter information set and the magnetic field information set to obtain the magnetic field command information and the vibration command information.

[0077] The armrest is arranged at the upper part of the vertical bracket; the physiological acquisition module is arranged on the armrest.

[0078] The control module performs feedback calculation and processing on the physiological parameter information set and the magnetic field information set to obtain the magnetic field command information and the vibration command information, including:

[0079] Performing preprocessing on the physiological parameter information set and the magnetic field information set to obtain a preprocessing parameter information set;

[0080] Performing magnetic field feedback calculation and processing on the preprocessing parameter information set to obtain the magnetic field command information;

[0081] Performing vibration feedback calculation and processing on the preprocessing parameter information set to obtain the vibration command information;

[0082] The electromagnetic field generator includes a control unit, a magnetic field coil, a magnetic induction intensity sensor, a current sensor and a voltage sensor; a magnetic induction intensity sensor is arranged inside the magnetic field coil, and the magnetic field coil is connected with a current sensor and a voltage sensor.

[0083] The magnetic induction intensity sensor, the current sensor and the voltage sensor are respectively used to measure and obtain a magnetic induction intensity information sequence, a current information sequence and a voltage information sequence.

[0084] The control unit is respectively connected to the magnetic field coil, the magnetic induction intensity sensor, the current sensor and the voltage sensor, and is used to change the voltage and current of the magnetic field coil according to the magnetic field command information, collect and obtain a magnetic field information set, and send the magnetic field information set to the control module.

[0085] The magnetic field information set includes the measured magnetic induction intensity information sequence, current information sequence and voltage information sequence.

[0086] Preprocessing the physiological parameter information set and the magnetic field information set to obtain a preprocessing parameter information set, including:

[0087] Performing time alignment processing on the physiological parameter information set and the magnetic field information set to obtain a first information set;

[0088] Performing pattern discrimination processing on the first information set to obtain a preprocessing parameter information set;

[0089] The time alignment processing is to align the data of the physiological parameter information set and the magnetic field information set according to the acquisition time, and it can be implemented by using a time registration algorithm.

[0090] Performing magnetic field feedback calculation processing on the preprocessing parameter information set to obtain magnetic field command information, including:

[0091] Obtaining a standard physiological parameter information set; the standard physiological parameter information set includes a body temperature standard value, a pulse standard value, a blood pressure standard value, and a blood oxygen saturation standard value;

[0092] Subtracting each type of information sequence in the physiological parameter information set in the preprocessing parameter information set from the corresponding standard value to obtain a difference sequence of the corresponding type;

[0093] Using the difference sequences of all types to construct a physiological difference matrix A; the row vector of the physiological difference matrix is a difference sequence of one type;

[0094] Using the magnetic field information set in the preprocessing parameter information set to construct a magnetic field information matrix B; the row vectors of the magnetic field information matrix are the magnetic induction intensity information sequence, the current information sequence, and the voltage information sequence;

[0095] Performing covariance matrix calculation on the physiological difference matrix A and the magnetic field information matrix B respectively to obtain a physiological covariance matrix S A and a magnetic field covariance matrix S B ;

[0096] Performing cross-covariance matrix calculation on the physiological difference matrix A and the magnetic field information matrix B to obtain a cross-covariance matrix S AB ;

[0097] Performing matrix decomposition processing on the physiological covariance matrix S A and the magnetic field covariance matrix S B respectively to obtain corresponding eigenvector matrices X and Y;

[0098] Performing matrix decomposition processing on the physiological covariance matrix S A and the magnetic field covariance matrix S B and the cross-covariance matrix SAB Perform a fusion calculation process with the eigenvector matrix to obtain a fused feature matrix;

[0099] Solve to obtain the set of eigenvalues of the fused feature matrix;

[0100] Sort the set of eigenvalues in descending order of their values to obtain an eigenvalue sequence;

[0101] Use the first element and the second element in the eigenvalue sequence to construct magnetic field command information; the magnetic field command information includes a voltage adjustment value and a current adjustment value; the first element and the second element in the eigenvalue sequence respectively correspond to the voltage adjustment value and the current adjustment value;

[0102] The expression for the fusion calculation process is:

[0103]

[0104] where T is the fused feature matrix;

[0105] The vibration feedback calculation process for the set of preprocessing parameter information to obtain vibration command information includes:

[0106] Obtain a set of standard physiological parameter information; the set of standard physiological parameter information includes a body temperature standard value, a pulse standard value, a blood pressure standard value, and a blood oxygen saturation standard value;

[0107] Subtract the standard value of each category from the information sequence of each category in the set of physiological parameter information in the set of preprocessing parameter information to obtain a difference sequence for the corresponding category;

[0108] Use the difference sequences of all categories to construct a physiological difference matrix A; the row vector of the physiological difference matrix is a difference sequence of one category;

[0109] Use the set of magnetic field information in the set of preprocessing parameter information to construct a magnetic field information matrix B; the row vector of the magnetic field information matrix is a magnetic induction intensity information sequence, a current information sequence, and a voltage information sequence;

[0110] Perform a first eigen-transformation process on each row vector of the physiological difference matrix A to obtain a physiological transformation vector; the expression for the first eigen-transformation process is:

[0111]

[0112] where N is the column dimension of the physiological difference matrix A, A ij is the element in the i-th row and j-th column of the physiological difference matrix A, and α i is the i-th element of the physiological transformation vector,

[0113] Perform column - normalization processing on the magnetic - field information matrix B to obtain a magnetic - field transformation vector;

[0114] The expression for the column - normalization processing is:

[0115]

[0116] where, p i is the i - th element of the magnetic - field transformation vector, b i is the mean value of the i - th row of the magnetic - field information matrix B, and m is the column dimension of the magnetic - field information matrix B;

[0117] Perform feature - fusion calculation processing on the magnetic - field transformation vector and the physiological transformation vector to obtain vibration command information;

[0118] The expression for the feature - fusion calculation processing is:

[0119]

[0120] where, zd is the vibration command information, M1 is the length of the physiological transformation vector, M2 is the length of the magnetic - field transformation vector, L i () represents the i - th Laguerre polynomial, T i () represents the i - th order polynomial of the first - kind Chebyshev polynomial; the vibration command information is the drive current value of the motor of the low - frequency vibration foot pedal;

[0121] For the matrix decomposition processing, matrix eigenvalue decomposition methods such as QR decomposition can be used;

[0122] Perform pattern discrimination processing on the first information set to obtain a pre - processing parameter information set, including:

[0123] For each type of information set in the first information set, construct an approximation matrix with each type of data sequence in the information set as row vectors; construct a collection matrix with the data acquisition information of each type of data sequence in the information set; the row vectors of the collection matrix are the data acquisition information of a type of data sequence; construct a pattern - matching model with the approximation matrix as the dependent variable and the collection matrix as the independent variable;

[0124] Solve the pattern - matching model to obtain the matching model for each type of information set; the expression of the matching model is f(x)=xA, where x is the input collection matrix of the matching model, and matrix A is obtained by solving the pattern - matching model;

[0125] Using the matching model of each type information set, calculate and process the data acquisition information of the data sequence of the corresponding type information set to obtain a solution matrix;

[0126] For each data in the solution matrix, subtract it from the corresponding data in the same row and column in the approximation matrix and take the absolute value to obtain the difference value of the data;

[0127] Delete the data with the difference value greater than the set difference threshold from the first information set;

[0128] Perform pattern discrimination on all type information sets in the first information set to obtain a preprocessing parameter information set.

[0129] The data acquisition information may be acquisition time information;

[0130] The pattern matching model has the following expression:

[0131] min|vA - R|,

[0132] subject to AA T = I A ,

[0133] where I A represents the identity matrix with the row dimension of matrix A as the dimension, matrix A represents the matrix to be solved, v represents the acquisition matrix, and R represents the approximation matrix;

[0134] The solution algorithm of the pattern matching model can adopt genetic algorithm and particle filter algorithm;

[0135] The low-frequency vibration foot pedal further includes a motor and a foot pedal; the motor is connected to the foot pedal and is used to drive the foot pedal to perform low-frequency vibration according to vibration command information; the vibration frequency of the low-frequency vibration is 5 - 30 Hz.

[0136] When in use, the user stands on the low-frequency vibration foot pedal and operates the control module to adjust the on / off and action states of the electromagnetic field generator and the low-frequency vibration foot pedal; the electromagnetic field generator is slidably connected to the vertical bracket and can conveniently adjust the height of the electromagnetic field generator according to the user's height. The sliding connection can be achieved through multiple adjustable jack-shaped structures.

[0137] In the second aspect of the embodiments of the present invention, a feedback method for osteoporosis treatment based on the fusion of vibration and magnetic field is disclosed, which is implemented by using the osteoporosis treatment device based on the fusion of vibration and magnetic field, and includes:

[0138] S1. Using the physiological data collection module, collect the set of physiological parameter information of the user during the osteoporosis treatment using the osteoporosis treatment device;

[0139] S2. Using the electromagnetic field generator, measure the set of magnetic field information;

[0140] S3. Using the control module, perform feedback calculation processing on the set of physiological parameter information and the set of magnetic field information to obtain magnetic field command information and vibration command information;

[0141] S4. According to the magnetic field command information, use the electromagnetic field generator to generate an electromagnetic field for osteoporosis treatment;

[0142] S5. According to the vibration command information, use the low-frequency vibration foot pedal to generate vibration for osteoporosis treatment.

[0143] The performing feedback calculation processing on the set of physiological parameter information and the set of magnetic field information to obtain magnetic field command information and vibration command information includes:

[0144] Performing preprocessing on the set of physiological parameter information and the set of magnetic field information to obtain a set of preprocessing parameter information;

[0145] Performing magnetic field feedback calculation processing on the set of preprocessing parameter information to obtain magnetic field command information;

[0146] Performing vibration feedback calculation processing on the set of preprocessing parameter information to obtain vibration command information;

[0147] The performing preprocessing on the set of physiological parameter information and the set of magnetic field information to obtain a set of preprocessing parameter information includes:

[0148] Performing time alignment processing on the set of physiological parameter information and the set of magnetic field information to obtain a first set of information;

[0149] Performing pattern discrimination processing on the first set of information to obtain a set of preprocessing parameter information;

[0150] The time alignment processing is to align the data of the set of physiological parameter information and the set of magnetic field information according to the acquisition time, and it can be implemented by using a time registration algorithm.

[0151] The performing magnetic field feedback calculation processing on the set of preprocessing parameter information to obtain magnetic field command information includes:

[0152] Obtaining a set of standard physiological parameter information; the set of standard physiological parameter information includes standard values of body temperature, pulse, blood pressure, and blood oxygen saturation;

[0153] Subtract each information sequence in the physiological parameter information set in the preprocessing parameter information set from the standard value of the corresponding category to obtain the difference sequence of the corresponding category;

[0154] Use the difference sequences of all categories to construct a physiological difference matrix A; the row vector of the physiological difference matrix is the difference sequence of one category;

[0155] Use the magnetic field information set in the preprocessing parameter information set to construct a magnetic field information matrix B; the row vectors of the magnetic field information matrix are the magnetic induction intensity information sequence, the current information sequence, and the voltage information sequence;

[0156] Perform covariance matrix calculations on the physiological difference matrix A and the magnetic field information matrix B respectively to obtain a physiological covariance matrix S A and a magnetic field covariance matrix S B ;

[0157] Perform cross-covariance matrix calculations on the physiological difference matrix A and the magnetic field information matrix B to obtain a cross-covariance matrix S AB ;

[0158] Perform matrix decomposition processing on the physiological covariance matrix S A and the magnetic field covariance matrix S B respectively to obtain the corresponding eigenvector matrices X and Y;

[0159] Perform matrix decomposition processing on the physiological covariance matrix S A , the magnetic field covariance matrix S B , the cross-covariance matrix S AB and the eigenvector matrix for fusion calculation processing to obtain a fusion feature matrix;

[0160] Solve to obtain the eigenvalue set of the fusion feature matrix;

[0161] Sort the eigenvalue set in descending order of the values to obtain an eigenvalue sequence;

[0162] Use the first element and the second element in the eigenvalue sequence to construct magnetic field command information; the magnetic field command information includes a voltage adjustment value and a current adjustment value; the first element and the second element in the eigenvalue sequence correspond to the voltage adjustment value and the current adjustment value respectively;

[0163] The expression of the fusion calculation processing is:

[0164]

[0165] where T is the fusion feature matrix;

[0166] Performing vibration feedback calculation processing on the set of preprocessing parameter information to obtain vibration command information, including:

[0167] Obtaining a set of standard physiological parameter information; the set of standard physiological parameter information includes a body temperature standard value, a pulse standard value, a blood pressure standard value, and a blood oxygen saturation standard value;

[0168] Subtracting each type of information sequence in the physiological parameter information set in the preprocessing parameter information set from the corresponding standard value to obtain a difference sequence for the corresponding category;

[0169] Using the difference sequences of all categories to construct a physiological difference matrix A; the row vector of the physiological difference matrix is a difference sequence of one category;

[0170] Using the magnetic field information set in the preprocessing parameter information set to construct a magnetic field information matrix B; the row vectors of the magnetic field information matrix are a magnetic induction intensity information sequence, a current information sequence, and a voltage information sequence;

[0171] Performing a first eigen-transformation process on each row vector of the physiological difference matrix A to obtain a physiological transformation vector; the expression of the first eigen-transformation process is:

[0172]

[0173] where N is the column dimension of the physiological difference matrix A, A ij is the element in the i-th row and j-th column of the physiological difference matrix A, and α i is the i-th element of the physiological transformation vector,

[0174] Performing a normalized column mode process on the magnetic field information matrix B to obtain a magnetic field transformation vector;

[0175] The expression of the normalized column mode process is:

[0176]

[0177] where p i is the i-th element of the magnetic field transformation vector, b i is the mean value of the i-th row of the magnetic field information matrix B, and m is the column dimension of the magnetic field information matrix B;

[0178] Performing eigenfusion calculation processing on the magnetic field transformation vector and the physiological transformation vector to obtain vibration command information;

[0179] The expression of the eigenfusion calculation processing is:

[0180]

[0181] wherein, zd is vibration instruction information, M1 is the length of the physiological transformation vector, M2 is the length of the magnetic field transformation vector, L i () represents the i-th Laguerre polynomial, T i () represents the i-th order polynomial of the first kind of Chebyshev polynomial; the vibration instruction information is the drive current value of the motor of the low-frequency vibration foot pedal;

[0182] For the matrix decomposition process, the matrix eigenvalue decomposition method can be used, such as QR decomposition, etc.;

[0183] Performing pattern discrimination processing on the first information set to obtain a preprocessing parameter information set, including:

[0184] For each type of information set in the first information set, using each type of data sequence in the information set as a row vector to construct an approximation matrix; using the data acquisition information of each type of data sequence in the information set to construct a collection matrix; the row vectors of the collection matrix are the data acquisition information of a type of data sequence; using the approximation matrix as the dependent variable and the collection matrix as the independent variable to construct a pattern matching model;

[0185] Solving the pattern matching model to obtain a matching model for each type of information set; the expression of the matching model is f(x) = xA, where x is the input collection matrix of the matching model, and matrix A is obtained by solving the pattern matching model;

[0186] Using the matching model of each type of information set to perform calculation processing on the data acquisition information of the data sequence of the corresponding type of information set to obtain a solution matrix;

[0187] For each data in the solution matrix, subtracting and taking the absolute value of the corresponding data in the same row and column of the approximation matrix as the data in the solution matrix to obtain the difference value of the data;

[0188] Deleting the data with the difference value greater than the set difference threshold from the first information set;

[0189] Performing pattern discrimination on all types of information sets in the first information set to obtain a preprocessing parameter information set.

[0190] The data acquisition information can be acquisition time information;

[0191] The expression of the pattern matching model is:

[0192] min|vA - R|,

[0193] subject to AA T= I A

[0194] wherein, I A represents an identity matrix with the row dimension of matrix A as the dimension, matrix A represents the matrix to be solved, v represents the acquisition matrix, and R represents the approximation matrix;

[0195] For the solution algorithm of the pattern matching model, a genetic algorithm and a particle filter algorithm can be adopted;

[0196] Before the magnetic field information set is measured by using the electromagnetic field generator, the electromagnetic field generator has been in a working state and has generated an electromagnetic field.

[0197] The above are only embodiments of the present invention and are not intended to limit the present invention. For those skilled in the art, the present invention can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the scope of the claims of the present invention.

Claims

1. An osteoporosis treatment device based on the fusion of vibration and magnetic field, characterized in that Including: An electromagnetic field generator, a low-frequency vibration foot pedal, a vertical bracket, a physiological data acquisition module, a control module, and an armrest; The electromagnetic field generator, which is slidably connected to the vertical bracket, is used to generate an electromagnetic field for osteoporosis treatment according to magnetic field command information and measure a set of magnetic field information; The low-frequency vibration foot pedal, which is arranged at the lower part of the vertical bracket, is used to generate vibration for osteoporosis treatment according to vibration command information; The physiological data acquisition module is used to acquire a set of physiological parameter information of the user during the osteoporosis treatment process using the osteoporosis treatment device; the set of physiological parameter information includes a body temperature information sequence, a pulse information sequence, a blood pressure information sequence, and a blood oxygen saturation information sequence: The control module is respectively connected to the electromagnetic field generator, the low-frequency vibration foot pedal, and the physiological data acquisition module, and is used to perform feedback calculation and processing on the set of physiological parameter information and the set of magnetic field information to obtain magnetic field command information and vibration command information, including: Performing preprocessing on the set of physiological parameter information and the set of magnetic field information to obtain a set of preprocessing parameter information; Performing magnetic field feedback calculation and processing on the set of preprocessing parameter information to obtain magnetic field command information; Performing vibration feedback calculation and processing on the set of preprocessing parameter information to obtain vibration command information, including: Obtaining a set of standard physiological parameter information; the set of standard physiological parameter information includes a body temperature standard value, a pulse standard value, a blood pressure standard value, and a blood oxygen saturation standard value; Subtracting each type of information sequence in the set of physiological parameter information in the set of preprocessing parameter information from the corresponding standard value to obtain a difference sequence of the corresponding category; Using the difference sequences of all categories to construct a physiological difference matrix A; the row vector of the physiological difference matrix is a difference sequence of one category; Using the set of magnetic field information in the set of preprocessing parameter information to construct a magnetic field information matrix B; the row vector of the magnetic field information matrix is a magnetic induction intensity information sequence, a current information sequence, and a voltage information sequence; Performing a first eigen transformation process on each row vector of the physiological difference matrix A to obtain a physiological transformation vector; the expression of the first eigen transformation process is: where N is the column dimension of the physiological difference matrix A, and A ij is the element at the i-th row and j-th column of the physiological difference matrix A, and α i is the i-th element of the physiological transformation vector Performing a normalized column mode process on the magnetic field information matrix B to obtain a magnetic field transformation vector; The expression of the normalized column mode process is: where p i is the i-th element of the magnetic field transformation vector, and b i is the mean of the i-th row of the magnetic field information matrix B, and m is the column dimension of the magnetic field information matrix B; Performing eigen fusion calculation and processing on the magnetic field transformation vector and the physiological transformation vector to obtain vibration command information; The expression of the eigen fusion calculation and processing is: Among them, zd is the vibration command information, M1 is the length of the physiological transformation vector, M2 is the length of the magnetic field transformation vector, L i (α i ) represents the i-th Laguerre polynomial, T i (p i ) represents the i-th order polynomial of the Chebyshev polynomial of the first kind; the vibration command information is the drive current value of the motor of the low-frequency vibration foot pedal; The armrest is arranged at the upper part of the vertical bracket; the physiological data acquisition module is arranged on the armrest.

2. The osteoporosis treatment device based on the fusion of vibration and magnetic field according to claim 1, characterized in that, The electromagnetic field generator includes a control unit, a magnetic field coil, a magnetic induction intensity sensor, a current sensor, and a voltage sensor; a magnetic induction intensity sensor is arranged inside the magnetic field coil, and the magnetic field coil is connected with a current sensor and a voltage sensor; The magnetic induction intensity sensor, the current sensor, and the voltage sensor are respectively used to measure a magnetic induction intensity information sequence, a current information sequence, and a voltage information sequence; The control unit is respectively connected to the magnetic field coil, the magnetic induction intensity sensor, the current sensor and the voltage sensor, and is used to change the voltage and current of the magnetic field coil according to the magnetic field command information, collect a magnetic field information set, and send the magnetic field information set to the control module; The magnetic field information set includes a measured magnetic induction intensity information sequence, a current information sequence and a voltage information sequence.

3. The osteoporosis treatment device based on the fusion of vibration and magnetic field according to claim 1, characterized in that, The preprocessing of the physiological parameter information set and the magnetic field information set to obtain a preprocessing parameter information set includes: Performing time alignment processing on the physiological parameter information set and the magnetic field information set to obtain a first information set; Performing pattern discrimination processing on the first information set to obtain a preprocessing parameter information set.

4. The osteoporosis treatment device based on the fusion of vibration and magnetic field according to claim 1, characterized in that, The magnetic field feedback calculation processing of the preprocessing parameter information set to obtain magnetic field command information includes: Obtaining a standard physiological parameter information set; the standard physiological parameter information set includes a body temperature standard value, a pulse standard value, a blood pressure standard value and a blood oxygen saturation standard value; Subtracting each type of information sequence in the physiological parameter information set in the preprocessing parameter information set from the corresponding standard value to obtain a difference sequence of the corresponding type; Using the difference sequences of all types to construct a physiological difference matrix A; the row vector of the physiological difference matrix is a difference sequence of one type; Using the magnetic field information set in the preprocessing parameter information set to construct a magnetic field information matrix B; the row vector of the magnetic field information matrix is a magnetic induction intensity information sequence, a current information sequence and a voltage information sequence; For the physiological difference matrix A and the magnetic field information matrix B, covariance matrix calculations are respectively performed to obtain a physiological covariance matrix S A and a magnetic field covariance matrix S B ; Perform a cross-covariance matrix calculation on the physiological difference matrix A and the magnetic field information matrix B to obtain the cross-covariance matrix S AB ; For the physiological covariance matrix S A and the magnetic field covariance matrix S B perform matrix decomposition processing respectively to obtain the corresponding eigenvector matrices X and Y; For the physiological covariance matrix S A , the magnetic field covariance matrix S B , the cross-covariance matrix S AB and the eigenvector matrix are subjected to fusion calculation processing to obtain a fusion feature matrix; Solving to obtain an eigenvalue set of the fusion feature matrix; Sorting the eigenvalue set from largest to smallest in value to obtain an eigenvalue sequence; Using the first element and the second element in the eigenvalue sequence to construct magnetic field command information; the magnetic field command information includes a voltage adjustment value and a current adjustment value; the first element and the second element in the eigenvalue sequence respectively correspond to the voltage adjustment value and the current adjustment value.

5. The osteoporosis treatment device based on the fusion of vibration and magnetic field according to claim 4, characterized in that The expression of the fusion calculation processing is: where T is the fusion feature matrix.

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