CN112214931B - Electromagnetic force feedback device and method for virtual interventional operation system - Google Patents
Electromagnetic force feedback device and method for virtual interventional operation system Download PDFInfo
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Abstract
The invention discloses an electromagnetic force feedback device and method for a virtual interventional operation system, wherein the device comprises an electromagnetic coil array and a surgical instrument; the electromagnetic coil array consists of four electromagnetic coils which are distributed on the same plane in a specific topological structure and have the same size; the surgical instrument consists of two long cylindrical permanent magnets and a rigid rod-like operating rod. Meanwhile, the invention provides an electromagnetic force feedback method suitable for the device, which comprises a basic operation principle of the device, an optimal current distribution strategy and a torque-current regression prediction model and is used for generating circumferential rotating force feedback in a virtual intervention operation in a concise, efficient, real-time and accurate manner. The virtual interventional operation system greatly restores the operation mode of the real interventional operation, improves the immersion feeling of an operator, and can improve the preoperative training effect of the virtual interventional operation system.
Description
Technical Field
The invention belongs to the technical field of virtual reality, and relates to an electromagnetic force feedback device and method for virtual intervention surgery, in particular to an electromagnetic coil array topological structure designed based on a magnetic suspension principle, a corresponding surgical instrument and an electromagnetic force feedback method using a computer simulation technology and a machine learning technology, which are used for accurately generating circumferential rotating force feedback in the virtual intervention surgery in real time.
Background
In a virtual vascular interventional surgery system, a user interacts with a virtual vascular scene by operating a surgical instrument highly similar to a guide wire catheter, thereby obtaining multi-sensory feedback of vision and touch and experiencing the interventional surgery performing process with high immersion (document 1). The difficulty of the virtual interventional operation system is to accurately generate a feedback force in an interventional operation process in real time, particularly a circumferential rotation feedback force in a guide wire twisting process (document 2). However, most of the force feedback modules in the existing virtual interventional surgical systems are designed by contact type mechanical guide rails and pulleys ([ document 3] [ document 4 ]). Due to the existence of the mechanical guide rail, the operation freedom is greatly limited, and the difference from the practical implementation situation of the actual interventional operation is large, so that the training effect of the virtual operation system is not ideal. With the maturity of magnetic levitation technology, its many advantages are gradually embodied, not only can obtain more flexible operation space, but also has the advantages of precision motion control and low energy consumption, in addition, friction and dynamic nonlinear hysteresis etc. in other driving methods are eliminated (document 5).
On the electromagnetic force feedback device based on magnetic levitation, Berkelman (document 6, document 7) et al firstly use the electromagnetic coil array with specific topology composed of single electromagnetic coil as basic unit and the corresponding operating rod with permanent magnet to obtain the contactless force tactile perception, but the basis of the placement of the electromagnetic coil is not explained too much. The yuanhan university random problem group ([ document 8]) applies an electromagnetic force feedback technique to a force feedback module of a virtual surgery system, and particularly to an elastically deformed organ tissue such as a kidney. Experimental results show that the operational experience of electromagnetic based force feedback modules is stronger than mechanical immersion, but the study focuses on the perception of stiffness of virtual tissues. At present, the electromagnetic force feedback in a relatively complex virtual interventional surgical system is still lack of system research, and the technical difficulty is that the surgical operation mode is reproduced with high reduction degree and the force feedback in the surgical process is accurately generated in real time.
In order to meet the real-time performance and accuracy of electromagnetic force feedback in a complex virtual access operation, a fast and efficient calculation model between the electromagnetic force and each coil excitation current needs to be established. According to the characteristics of the topological structure and the operating instrument, a simple and accurate calculation model is created by combining methods such as model fusion and the like, and the instantaneity and the accuracy of force feedback generation are ensured.
Reference documents:
[ document 1] Omisore O M, Han S P, Ren L X, et al, war charaterization and Adaptive Compensation of background in a Novel Robotic Filter System for Cardiovascular events [ J ]. IEEE Transactions on biological Circuits & Systems,2018, PP (4):1-15.
Shi Y, Zhou C, Xie L, et al, research of the master-slave Robot support system with the function of force feedback [ J ]. Int J Med Robot,2017: e1826.
[ document 3] Guo J, Jin X, Guo S, et al.A vacuum Interactive scientific System Based on Force-Visual Feedback [ J ]. IEEE Sensors Journal,2019,19(23):11081-11089.
[ document 4] Guo J, Yu Y, Guo S, et al.design and performance evaluation of a novel master manager for the robot-assist system [ C ]// IEEE International Conference on mechanics & Automation. IEEE,2016: 937-.
[ document 5] Kim Y, Parada G A, Liu S, et al.Ferromagnetic soft continuum robots [ J ]. Science Robotics,2019,4(33): eaax7329.
Document 7, Berkelman P, Dzadovsky M. magnetic preference conversion and Rotation Ranges in All Directions [ J ]. IEEE/ASME transformations on mechanics, 2013,18(1):44-52.
[ document 8] Tong Q, Yuan Z, Liao X, et al, magnetic differentiation Haptical evaluation for visual Tissue characterization [ J ]. IEEE Transactions on Visualization and Computer Graphics,2018,24(12):3123-3136.
Disclosure of Invention
Aiming at the problem that a force feedback module in the existing virtual interventional operation system is difficult to generate immersive and vivid operation feeling, the invention designs a set of device comprising a highly symmetrical electromagnetic coil array and a multi-degree-of-freedom operation operating rod to reproduce the key force feedback-circumferential rotating force feedback in the interventional operation by researching the magnetic field characteristics of the electrified coil array and analyzing the operation mode of the vascular interventional operation. In addition, aiming at the problem that the electromagnetic force touch module is difficult to dynamically generate real-time accurate force feedback, the electromagnetic force feedback method suitable for the device is provided, and is used for simply, efficiently, real-time and accurately generating circumferential rotating force feedback in a virtual intervention operation.
The technical scheme adopted by the device of the invention is as follows: an electromagnetic force feedback device for a virtual interventional surgery system is characterized in that: comprises an electromagnetic coil array and a surgical instrument; the electromagnetic coil array comprises four identical electromagnetic coils, four protection bases and a chassis slide rail; the four identical electromagnetic coils are arranged on the same plane, the circle centers of the bottom surfaces with close distances in each electromagnetic coil are sequentially connected to form a square, and the center of the square is the intersection point of the two pairs of bottom surface circle centers of the diagonal coils; the four identical electromagnetic coils are respectively and fixedly arranged on the protection base; the four protection bases are all arranged on the chassis slide rail and can move on the chassis slide rail; the surgical instrument is a surgical operating rod with multiple degrees of freedom.
Preferably, the angle of the protection base is adjustable. The angle is the included angle of the bottom surface of the electromagnetic coil and the horizontal plane, the angle adjusting range is 0-90 degrees, and the secondary development performance and the flexibility of the device can be improved.
Preferably, the surgical instrument comprises a rigid operating rod, a first permanent magnet and a second permanent magnet; the first permanent magnet is arranged at the top of the upper end of the rigid operating rod, and the second permanent magnet is fixedly arranged at the middle upper part of the first permanent magnet and is crossed with the first permanent magnet. The two are mutually matched, so that the mechanical characteristics of the guide wire in the actual interventional operation can be highly simulated and restored.
Preferably, the first permanent magnet and the second permanent magnet are both long cylindrical permanent magnets, and the limitation of the manufacturing process of the permanent magnets on the market enables the long cylindrical permanent magnets to meet the requirement that the magnetized surface is a smaller surface.
Preferably, the rigid operating rod is made of polyethylene, and the radius of the bottom surface of the rigid operating rod is 9mm, and the height of the rigid operating rod is 200 mm. The parameters can be adjusted according to actual conditions, and the operating rod should be as slender as possible and should be made of a material with lower density so as to be more consistent with the properties of the catheter in the actual interventional operation.
Preferably, the radius of the bottom surface of the first permanent magnet is 8mm, and the height of the bottom surface of the first permanent magnet is 15 mm. These parameters can be adjusted according to the actual conditions, and the first permanent magnet should be as light as possible and be inosculated with the tip of the guide wire in the actual intervention operation, thereby keeping the pureness of force feedback.
Preferably, the radius of the bottom surface of the second permanent magnet is 6mm, and the height of the bottom surface of the second permanent magnet is 35 mm. These parameters can be adjusted according to actual conditions, and the second permanent magnet should be as slender as possible, so as to keep light weight while obtaining stronger circumferential feedback force.
Preferably, the material of the electromagnetic coil is Copper, the distance between the electromagnetic coil pairs which are diagonal to each other is 74mm, and the number of coil turns of a single electromagnetic coil is 1024. The parameters can be adjusted according to actual conditions, and according to the Bio Saval law, the closer the current source is, the larger the magnetic field intensity is; the larger the cross-section current of the electromagnetic coil is, the larger the magnetic field intensity is. Therefore, the distance between the coil pairs is as small as possible and is slightly larger than the length of the second permanent magnet, the cross-section current is larger when the number of turns of the coil is calculated to be about 1000, and therefore stronger electromagnetic feedback force is generated under the common promotion of the two factors.
The method adopts the technical scheme that: an electromagnetic force feedback method for a virtual interventional surgical system is characterized by comprising the following steps:
step 1: modeling simulation of materials with equal proportion and size is carried out on an electromagnetic coil and a second permanent magnet in the electromagnetic force feedback device to obtain an electromagnetic force feedback model;
determining the basic operation principle of the electromagnetic force feedback device: the electromagnetic coils at the diagonal positions give excitation currents in the same direction;
determining an optimal current distribution strategy of the electromagnetic force feedback device: providing a three-dimensional tuple (X, y, z) for an included angle theta in the positive direction of the X axis in a rectangular coordinate system formed by connecting the N pole of the second permanent magnet and the centers of the bottom surfaces of the coils which are diagonal to each other so as to determine the optimal distribution strategy of the current in the electromagnetic coil array;
x＝[θ/90]mod2
y＝|(45·[θ/45])mod2-θmod45|
z＝[θ/180]
in the three-dimensional tuple (x, y, z), x determines a solenoid coil pair applying current, y is an included angle of equivalent mapping in a minimum symmetric interval, and z is used for indicating the current direction in the coil pair; each theta corresponds to a unique triplet, namely a unique optimal current distribution strategy;
step 2: constructing a torque-current regression prediction model;
adjusting the positive direction included angle theta between the N pole of the second permanent magnet and the X axis of the rectangular coordinate system in the electromagnetic force feedback model established in the step 1 and the exciting current value I of the electromagnetic coil, and calculating the torque value T of the second permanent magnet rotating around the shaft; thereby obtaining a plurality of groups of offline data to form an offline data set;
training a BPNN (binary phase noise network) and a GRNN (generalized regression neural network) for regression prediction by using an offline data set, taking a neural network with optimal performance as a sub-model, and constructing a strong moment-current prediction model by using a model fusion method, so that an excitation current value I of a coil array can be quickly and accurately calculated according to a positive included angle theta of an N pole of a second permanent magnet and an X axis of a rectangular coordinate system and a moment value T;
and step 3: generating a current distribution pattern for the electromagnetic coil array;
and calculating a triad (x, y, z) according to theta, inputting the y and moment values T in the triad through a moment-current regression prediction model to solve an excitation current value I, finally forming a new triad (x, I, z), and guiding the distribution of the current of each electromagnetic coil in the electromagnetic coil array by using the triad so as to generate corresponding circumferential rotating force feedback.
Preferably, the specific implementation of step 2 comprises the following sub-steps:
step 2.1: continuously adjusting the rotation angle theta of the second permanent magnet and the exciting current value I of the electromagnetic coil, and solving to obtain corresponding torque data T so as to obtain a plurality of groups of offline data to form an offline data set;
step 2.2: constructing a BPNN network comprising an input layer, a hidden layer and an output layer; the input value of the network is a torque value T to which the second permanent magnet should be subjected and an included angle theta between the N pole of the second permanent magnet on the surgical instrument and the positive direction of the X axis of the rectangular coordinate system, and the output value is an electromagnetic coil excitation current value I;
step 2.3: building a GRNN network comprising an input layer, a mode layer, a summation layer and an output layer; the input value of the network is a torque value T to which the second permanent magnet should be subjected and an included angle theta between the N pole of the second permanent magnet on the surgical instrument and the positive direction of the X axis of the rectangular coordinate system, and the output value is an electromagnetic coil excitation current value I;
step 2.4: training a BPNN network and a GRNN network;
in the off-line training process of the BPNN, after off-line data sets are subjected to normalization processing, dividing the off-line data sets into a training set and a verification set by using a k-fold training method and carrying out network training; then, taking the mean square error of the exciting current of the electromagnetic coil as a loss function, stopping training and storing the BPNN as one of the model fusion submodels when the error of the network on the verification set is smaller than a threshold value after training, and marking the model fusion submodel as a BPNN prediction submodel;
in the off-line training process of the GRNN, selecting a proper amount of training data according to the running time of a machine and randomly generating a super-parameter initial value so as to determine the network structure and parameters of the GRNN, and simultaneously selecting a plurality of pieces of data out of a training set in a data set as a verification set; carrying out GRNN network training by using a verification set and dynamically adjusting the value of the hyper-parameter according to an error in the training process; when the mean square error of the network on the verification set is smaller than a threshold value after training, storing the hyper-parameters and the training set as a sub-model fused with another model, and recording as a GRNN network prediction sub-model;
step 2.5: taking M brand new data as a prediction set and respectively inputting the data into the two submodels for current prediction;
by using an extreme value thought in mathematical statistics, solving a sub-model weight value which enables the variance of the deviation between the predicted value and the actual value to be minimum, and finally obtaining a moment-current regression prediction model as follows:
k 1 +k 2 ＝1
wherein
And
respectively corresponding predicted values of the BPNN network prediction submodel and the GRNN network prediction submodel, theta is an included angle between the N pole of the second permanent magnet (203) and the positive direction of the X axis in a rectangular coordinate system, t is a moment numerical value of the second permanent magnet (203), and k is 1 And k 2 The weight values of the results are predicted corresponding to the two submodels,
and the prediction value of the final strong prediction model is obtained.
The basic operation principle of the device extracted by analyzing the motion principle of the rigid body rotating around the fixed shaft ensures the feasibility of the method; analyzing the summarized optimal current distribution strategy by using a finite element technology, and ensuring the high efficiency and the simplicity of the method; a torque-current prediction model based on a neural network is constructed, dynamic excitation current is calculated quickly and accurately, and the fact that the circumferential rotating force feedback in an interventional operation can be generated accurately in real time by an electromagnetic force feedback method is guaranteed.
Compared with the prior art, the invention has the following innovation and advantages:
(1) the magnetic suspension-based electromagnetic force feedback technology is used for generating key force feedback in a virtual interventional operation, so that the energy consumption of a system can be effectively reduced, mechanical friction interference, dynamic nonlinear hysteresis and the like in the operation process can be almost completely eliminated, and precise motion control is completed.
(2) Compared with the existing mechanical force feedback module based on the guide rail and the pulley, the device gives the operator more free operating space instead of sliding back and forth on the guide rail, increases the immersion feeling of the operator and improves the preoperative training effect.
(3) The electromagnetic force feedback method provided according to the electromagnetic force feedback device has strong universality, and is still suitable when the parameters (the size and the material of an electromagnetic coil and the size and the position of a long cylindrical permanent magnet of an operating rod) of the established electromagnetic force feedback device are changed.
(4) Compared with the existing three-dimensional analytic calculation method, the proposed torque-current regression prediction model is simpler and more efficient, a large number of intermediate deduction calculation processes are omitted, and the relation between two key physical quantities of torque and current is directly established, so that the real-time and accurate circumferential rotating force feedback is possible.
Drawings
FIG. 1 is a schematic diagram of a solenoid array according to an embodiment of the present invention;
FIG. 2 is a cross-sectional view of a solenoid coil according to an embodiment of the present invention;
FIG. 3 is a schematic view of a surgical instrument according to an embodiment of the present invention;
FIG. 4 is a flowchart of the operation of an embodiment of the present invention;
FIG. 5 is a schematic view of circumferential rotational force feedback according to an embodiment of the present invention;
FIG. 6 is a graph of experimental data demonstrating basic operating principles of the apparatus according to an embodiment of the present invention;
FIGS. 7 and 8 are graphs of experimental data for determining an optimal current allocation strategy according to an embodiment of the present invention;
fig. 9 is a schematic structural diagram of a torque-current regression prediction model according to an embodiment of the present invention.
Detailed Description
In order to facilitate the understanding and implementation of the present invention for those of ordinary skill in the art, the present invention is further described in detail with reference to the accompanying drawings and examples, it is to be understood that the embodiments described herein are merely illustrative and explanatory of the present invention and are not restrictive thereof.
Referring to fig. 1, fig. 2 and fig. 3, the electromagnetic force feedback device for a virtual interventional surgical system according to the present invention includes an electromagnetic coil array 1 and a surgical instrument 2; the electromagnetic coil array comprises four identical electromagnetic coils 101, four protection bases 102 and a chassis slide rail 103; four identical electromagnetic coils 101 are arranged on the same plane, the circle centers of the bottom surfaces of the electromagnetic coils 101 which are close to each other are sequentially connected to form a square, and the center of the square is the intersection point of the two pairs of bottom surface circle centers of the coils which are diagonal to each other; four identical electromagnetic coils 101 are respectively and fixedly arranged on the protection base 102; the four protection bases 102 are all arranged on the chassis slide rails 103 and can move on the chassis slide rails 103; the surgical instrument 2 is a surgical operation rod with multiple degrees of freedom.
The solenoid array 1 of the present embodiment includes four identical solenoids 101 and their associated adjustable bases 102, and chassis slide rails 103 for sliding the solenoids in diagonal directions. The electromagnetic coil framework, the adjustable coil base and the chassis with the sliding rails are all made of aluminum alloy materials. The material of the electromagnetic coil winding is Copper, the distance between the diagonal coil pairs is 74mm, the number of coil turns of a single coil is 1024, and the cross section is shown in FIG. 2. The protection base 102 of the present embodiment is angularly adjustable. The angle is the included angle between the bottom surface of the electromagnetic coil and the horizontal plane, and the angle adjusting range is 0-90 degrees. When the electromagnetic coil array is electrified according to a specific principle, a corresponding magnetic field can be generated to interact with a surgical instrument to generate force feedback in virtual intervention operation.
Referring to fig. 3, the surgical instrument 2 of the present embodiment includes a rigid operating rod 201, a first permanent magnet 202, and a second permanent magnet 203; the first permanent magnet 202 is arranged at the top end of the rigid operating rod 201, and the second permanent magnet 203 is fixedly arranged at the middle upper part of the first permanent magnet 202 and is crossed with the first permanent magnet 202. The first permanent magnet 202 and the second permanent magnet 203 are both long cylindrical permanent magnets.
The surgical instrument 2 of the present embodiment is integrated into a rigid bamboo dragonfly-shaped operation rod, and although the real guide wire catheter is made of a non-rigid material, it is considered that the guide wire catheter does not significantly deform in the portion in contact with the blood vessel during the operation, with respect to the strength of the in vivo environment such as the blood vessel, and therefore the rigid operation rod 201 is made of polyethylene, and has a bottom surface with a radius of 9mm and a height of 200 mm. The first permanent magnet 202 at the tip of the operating rod is made of NdFe35, the radius of the bottom surface of the operating rod is 8mm, the height of the operating rod is 15mm, and when the operating rod interacts with a magnetic field excited by a single coil or a three coil, the operating rod can generate a feedback force in the axial direction of the surgical instrument 2; the second permanent magnet 203 with two magnetized surfaces (the rectangular permanent magnet cannot form two magnetic poles on the narrow surface due to the limitation of the manufacturing process) has the material brand of NdFe35, the radius of the bottom surface is 6mm, the height is 35mm, the degree of freedom of the surgical instrument 2 in the circumferential direction can be provided, and the second permanent magnet interacts with a specific magnetic field excited by the electromagnetic coil array 1 to generate circumferential rotation feedback force.
The working flow of the whole virtual interventional operation system in this example is shown in fig. 4, wherein the working flow of the electromagnetic force feedback device is as follows:
(1) the user operates the surgical instrument 2 to move to the position shown in fig. 5, that is, the center of the body of the second permanent magnet 203 on the surgical instrument coincides with the center of the electromagnetic coil array 1, and it is assumed that the surgical instrument 2 and the virtual scene are deformed interactively at this time, resulting in a rotation feedback force in the counterclockwise direction around the Z axis.
(2) The PC terminal calculates the torque and the direction of the surgical instrument 2 rotating around the Z axis according to the deformation degree, the edge embedded terminal with the binocular vision positioning function obtains the included angle theta between the N pole of the second permanent magnet 203 in the surgical instrument and the positive direction of the X axis of the rectangular coordinate system at the moment, and transmits the parameters to the PC terminal.
(3) And transmitting the torque value T and the angle y subjected to optimal current strategy mapping into a torque-current regression prediction model constructed in advance as input in a PC terminal, quickly and accurately obtaining the excitation current of each electromagnetic coil 101 in the electromagnetic coil array 1 and transmitting the excitation current to a bottom layer embedded type in a triple form.
(4) The bottom layer embedded end controls a driving circuit of the electromagnetic coil 101 to generate corresponding electromagnetic coil exciting current according to the received current data, so that the electromagnetic coil array 1 generates a corresponding magnetic field, and the second permanent magnet 203 on the surgical instrument generates circumferential rotation feedback force.
In order to meet the requirement of generating feedback of circumferential rotating force in a virtual intervention operation simply, efficiently, in real time and accurately, an electromagnetic force feedback method suitable for the device is provided. The electromagnetic force feedback method respectively guarantees the feasibility, high efficiency, simplicity and real-time accuracy of the device on the basis of the basic operation principle, the optimal current distribution strategy and the moment-current calculation model of the device. In general, the electromagnetic force feedback method can be used as an algorithm, and can be based on two input data at the PC terminal: the moment value T and the positive direction included angle theta between the N pole of the second permanent magnet 203 and the X axis of the rectangular coordinate system are used for obtaining the optimal distribution method of the exciting current in the whole electromagnetic coil array 1, so that the requirement of circumferential rotating force feedback is met.
The invention designs a corresponding electromagnetic force feedback generation method aiming at the provided electromagnetic force feedback device, which is used for concisely, efficiently, real-timely and accurately generating circumferential rotating force feedback in a virtual intervention operation, and comprises the following steps:
step 1: modeling simulation of materials such as the electromagnetic coil 101 and the second permanent magnet 203 in the electromagnetic force feedback device in an equal proportion size is carried out, and an electromagnetic force feedback model is obtained;
in the present embodiment, firstly, finite element analysis software is used to perform modeling operation on electromagnetic coil 101 and second permanent magnet 203 in the electromagnetic force feedback device (other parts in the device are not magnetically conductive and can be ignored), and geometric models of electromagnetic coil 101 and second permanent magnet 203 are established and their materials are respectively Copper and NdFe 35. Then, setting the air space of the whole model to be 50% offset in the x and y directions and 100% offset in the Z direction, adopting the boundary condition of zero tangent vector, setting the cross section of the electromagnetic coil 101 as an excitation current conducting surface, and taking the electromagnetic force of the second permanent magnet 203 and the moment of the second permanent magnet rotating around the positive direction of the Z axis as solving parameters.
Determining the basic operation principle of the electromagnetic force feedback device: the electromagnetic coils 101 at diagonal positions give excitation currents in the same magnitude and direction;
when the device operates according to the principle, two conditions generated by circumferential rotation feedback force can be met:
(1) the second permanent magnet 203 is entirely subjected to the electromagnetic force resultant of 0, so that the second permanent magnet is ensured not to generate movement except the circumferential rotation around the shaft, and the pureness of the circumferential rotating force touch sense is ensured.
(2) The second permanent magnet 203 rotates around the fixed axis Z axis with a moment not equal to 0 and with a considerable value, so that the effectiveness of the circumferential rotating force touch sense is ensured.
Determining an optimal current distribution strategy of the electromagnetic force feedback device;
the current distribution strategy in the electromagnetic coil array 1 is further refined on the basis of determining the basic operation principle of the electromagnetic force feedback device, so that the strategy has high efficiency and simplicity at the same time:
(1) high efficiency: when the excitation current with the same magnitude passes, the electromagnetic coil pair generating larger moment is selected as a field source.
(2) Simplicity: the topology of the solenoid array 1 is analyzed and the characteristics of relative position and absolute position are used to map the whole working area of the device into the minimum symmetrical interval.
Based on the above description of the two characteristics of the optimal current distribution strategy, the following mathematical expression of the optimal current distribution strategy is proposed: for an included angle theta in the positive direction of the X axis in a rectangular coordinate system formed by connecting the N pole of the second permanent magnet 203 and the centers of the bottom surfaces of the coils which are diagonal to each other, a three-dimensional tuple (X, y, z) is proposed to determine an optimal distribution strategy of the current in the electromagnetic coil array 1, and the calculation method of the three elements is as follows:
x＝[θ/90]mod2
y＝|(45·[θ/45])mod2-θmod45|
z＝[θ/180]
in the three-dimensional tuple, x determines the electromagnetic coil pair applying current, y is an included angle of equivalent mapping in the minimum symmetric interval, and z is used for indicating the current direction in the coil pair. Each theta corresponds to a unique triplet, i.e. a unique optimal current distribution strategy.
The correctness of the basic operation principle is further verified in the embodiment;
and (2) using the electromagnetic force feedback model established in the step (1), distributing excitation currents with the same magnitude and direction to the electromagnetic coils 101 which are diagonal to each other according to the basic operation principle of the electromagnetic force feedback device, and analyzing the resultant force value of the electromagnetic force borne by the second permanent magnet 203 and the torque value around the rotating shaft after solving, thereby verifying the correctness of the basic operation principle.
In this embodiment, when the included angle between the N pole of the second permanent magnet 203 on the surgical instrument 2 and the positive direction of the X axis of the rectangular coordinate system is 0, the excitation currents with the initial value of 0, the cutoff value of 2048A and the step length of 204.8A are respectively led to the coil pairs 1 and 3 according to the basic operation principle of the device, and the result shown in fig. 6 is obtained after the finite element calculation software is used for solving. It can be seen that the simulation result satisfies two conditions of rigid body rotation around the fixed axis within the error range: the resultant force of the electromagnetic force exerted on the second permanent magnet 203 is 0, and the value of the torque of the second permanent magnet around the shaft is considerable. And the feasibility of the basic operation principle is verified.
The optimal current distribution strategy is further determined in the embodiment;
continuing with the electromagnetic force feedback model established in step 1, the angular range for which each pair of coils meets high efficiency will be determined and the simplicity of the optimal current distribution strategy will be verified.
Determination of the efficiency: two pairs of electromagnetic coils (1, 3 and 2, 4 coil pairs) which are diagonal to each other are respectively led to excitation currents with the same magnitude in all ranges of any minimum symmetric interval, the torque values of the second permanent magnet 203 around the rotating shaft when different coil pairs work are compared after simulation solution, the working angle range of the two pairs of coils is determined in the minimum symmetric interval, and the high efficiency of the strategy is guaranteed.
And (3) verification of conciseness: when the second permanent magnet 203 rotates to the theta position, a torque value T generated according to the basic operation principle of the electromagnetic force feedback device and a torque value T generated under the guidance of a triad determined by an optimal current distribution strategy are respectively solved, and the two data are compared to verify the simplicity of the strategy.
In this embodiment, an angle range satisfying the high efficiency of the optimal current distribution strategy is determined, and according to the linear relationship between the current and the electromagnetic field generated by the current, the contribution of the excitation current to the moment in the two coil pairs only needs to be solved under a certain value of the current. And when the two groups of coil pairs are led to 2048A excitation current according to the basic operation principle of the device, simulation solution is carried out, and the result is shown in FIG. 7. In the present embodiment, it can be seen that θ is in the range of 0 ° to 45 °, and the value of the torque generated by the excitation current in the 1, 3 coil pairs farther from the second permanent magnet 203 is larger than the value of the torque generated by the excitation current in the 2, 4 coil pairs. The coil pair further from the second permanent magnet 203 is therefore selected in the subsequent current setting as the field source for current distribution.
In the process of simplicity verification, according to the theta and the triad (x, y, z) calculated by the theta, the model established in the step 1 is used for respectively solving and obtaining a moment value T which is obtained according to the basic operation principle of the device before mapping and the optimal current distribution strategy after mapping, and the moment value T is compared, wherein the specific result is shown in fig. 8. As can be seen from data in the graph, the theta takes any value from 0 degrees to 360 degrees, the triad (x, y, z) is solved through an optimal current distribution strategy, and the value T of the front moment is mapped under the drive of excitation current with random magnitude θ After mapping, the torque value T obtained by setting the working coil pairs and the current direction according to the triad (x, y, z) y Basically, the second permanent magnet 203 is shown in the whole working range, and the values of the torque, the current and the like can be mapped within the minimum symmetric interval of 0-45 degrees by using the symmetry of the coil array. The simplicity of the optimal current allocation strategy is thus verified.
The finite element software in the step 1 is used for calculation verification, the time cost is high, and online calculation cannot be performed, so that a small-scale calculation model needs to be constructed to perform relatively real-time accurate online calculation. Therefore, a regression prediction model based on a neural network is selected for prediction.
Step 2: constructing a torque-current regression prediction model;
adjusting the positive direction included angle theta between the N pole of the second permanent magnet 203 and the X axis of the rectangular coordinate system in the electromagnetic force feedback model established in the step 1 and the exciting current value I of the electromagnetic coil, and calculating the torque value T of the second permanent magnet 203 rotating around the axis; thereby obtaining a plurality of groups of offline data to form an offline data set;
training a BPNN (binary phase noise network) and a GRNN (generalized regression neural network) for regression prediction by using an offline data set, taking a neural network with optimal performance as a sub-model, and constructing a strong moment-current prediction model by using a model fusion method, so that an excitation current value I of a coil array can be rapidly and accurately calculated according to a positive direction included angle theta between the N pole of the second permanent magnet 203 and a rectangular coordinate system and a moment value T;
the method comprises the following substeps:
step 2.1: continuously adjusting the rotation angle theta of the second permanent magnet 203 and the excitation current value I of the electromagnetic coil 101, and solving to obtain corresponding torque data T so as to obtain a plurality of groups of offline data to form an offline data set; the number of data pieces in the offline dataset for this embodiment is 966.
Step 2.2: and constructing a BPNN network comprising an input layer, two hidden layers and an output layer. The input values of the network are a torque value T to which the second permanent magnet 203 should be subjected and an included angle theta between the N pole of the second permanent magnet 203 on the surgical instrument 2 and the positive direction of the X axis of the rectangular coordinate system, the numbers of front and rear nodes of the two layers of hidden layers are respectively 7 and 8, the activation functions are respectively Sigmoid and Relu, and the output value is an electromagnetic coil excitation current value I.
Step 2.3: and building a GRNN network comprising an input layer, a mode layer, a summation layer and an output layer. The input and output are the same as parameters in step 2.2, and through a large number of pre-experiments, the number of nodes in the mode layer is set to 322, and the number of nodes in the summation layer is the output dimension +1 and is 2.
Step 2.4: training a BPNN network and a GRNN network;
in the off-line training process of the BPNN, after off-line data sets are subjected to normalization processing, dividing the off-line data sets into a training set and a verification set by using a k-fold training method and carrying out network training; then, taking the mean square error of the exciting current of the electromagnetic coil as a loss function, stopping training and storing the BPNN when the error of the network on the verification set is smaller than a threshold value, and taking the BPNN as one of the model fusion submodels as a BPNN network prediction submodel;
in this example, k is 4. Then, taking the mean square error of the exciting current of the electromagnetic coil as a loss function, stopping training and saving the model when the error of the model on the verification set is less than 42A.
In the off-line training process of the GRNN, selecting a proper amount of training data according to the running time of a machine and randomly generating a super-parameter initial value so as to determine the network structure and parameters of the GRNN, and simultaneously selecting a plurality of pieces of data out of a training set in a data set as a verification set; carrying out GRNN network training by using a verification set and dynamically adjusting the value of the hyper-parameter according to an error in the training process; when the mean square error of the network on the verification set is smaller than a threshold value after training, the hyper-parameters and the training set are stored and used as a sub-model for fusing another model, and the sub-model is marked as a GRNN network prediction sub-model;
because of the particularity of the GRNN network, the network does not need to train the weights between nodes, in other words, the entire network structure is fixed after the training set and the hyper-parameter values are determined. Each time prediction is performed, the test data and the data in the training set need to be operated. In this embodiment, 322 pieces of data are uniformly taken out from the data set as a training set of the GRNN network, and another 100 pieces of data in the data set are taken as a verification set, and the value of the hyper-parameter is continuously adjusted, so that the mean square error is less than 42A. Experimentally, the hyperparameter δ was set to 0.5 here.
Step 2.5: and taking another 15 brand new data as a prediction set to be respectively input into the two submodels for current prediction. And solving the submodel weight with the minimum variance of the deviation between the predicted value and the actual value by using an extreme value thought in mathematical statistics, wherein the final moment-current regression prediction model is as follows:
wherein
And
respectively corresponding predicted values of the BPNN network prediction submodel and the GRNN network prediction submodel, theta is an included angle between the N pole of the second permanent magnet 203 and the positive direction of the X axis in a rectangular coordinate system, t is a moment value of the second permanent magnet (203),
the structure of the whole strong torque-current regression prediction model is shown in fig. 9 as the final prediction value of the strong prediction model.
And step 3: generating a current distribution pattern for the electromagnetic coil array;
according to the electromagnetic force feedback method, after a position parameter theta and a moment parameter T of a surgical instrument 2 are obtained, an optimal current distribution strategy is substituted into theta to calculate a triple (x, y, z), a moment-current regression prediction model is used for inputting the y and moment values T in the triple to solve an excitation current value I, a new triple (x, I, z) is finally formed, the triple is transmitted to the distribution of the current of each electromagnetic coil 101 in a conductive magnetic coil array 1 in a bottom-layer embedded processor, and therefore corresponding circumferential rotating force feedback is generated.
In the embodiment, a set of electromagnetic coil array topological structure and surgical instruments are realized according to the structural characteristics of the electromagnetic force feedback device from the real-time property and the accuracy of the key force feedback in the virtual interventional operation system, a corresponding simple, efficient, real-time and accurate electromagnetic force feedback method is provided based on the electromagnetic force feedback device, and the verification is performed by utilizing AnsoftMaxwell simulation software. And then acquiring a large amount of simulation data in an off-line state by a finite element calculation method to train a plurality of regression prediction models, and finally constructing a strong moment-current prediction model by using a model fusion method to predict the current quickly and accurately. The experimental result of the embodiment shows that the prediction model can predict the current with the error of 3% and the frequency higher than 40Hz, and can accurately reduce the feedback of the key force in the interventional operation in real time by combining the electromagnetic force feedback method.
The electromagnetic force feedback method and the electromagnetic force feedback device for the virtual interventional operation system can not only accurately generate circumferential rotation feedback force in the interventional operation in real time, but also avoid the defects in a guide rail-pulley type force feedback module, such as errors caused by mechanical friction, overlarge equipment scale and high energy consumption. Particularly, the invention greatly improves the operation immersion, basically and completely reproduces the operation flow of the interventional operation in the operation space and the operation method, and greatly improves the preoperative training effect of the virtual interventional operation system by matching with the visual effect of the virtual scene and the tactile effect of electromagnetic force feedback.
It is worth mentioning that the electromagnetic force feedback method of the invention provides a novel physical quantity calculation method, which is different from the previous calculation method based on three-dimensional analysis, omits the middle complex derivation step, directly establishes the relation between the key physical quantity moment and the current by carrying out model fusion on the neural networks with different characteristics, has great credibility on the calculation accuracy, and greatly reduces the calculation time and the memory consumption.
It should be understood that portions of the specification not set forth in detail are not admitted to be prior art; the above description of the preferred embodiments is intended to be illustrative, and not to be construed as limiting the scope of the invention, which is defined by the appended claims, and all changes and modifications that fall within the metes and bounds of the claims, or equivalences of such metes and bounds are therefore intended to be embraced by the appended claims.
Claims (7)
1. An electromagnetic force feedback method facing a virtual interventional operation system adopts an electromagnetic force feedback device facing the virtual interventional operation system;
the method is characterized in that:
the device comprises an electromagnetic coil array (1) and a surgical instrument (2);
the electromagnetic coil array comprises four identical electromagnetic coils (101), four protection bases (102) and a chassis sliding rail (103); the four identical electromagnetic coils (101) are arranged on the same plane, the circle centers of the bottom surfaces of the electromagnetic coils (101) which are closer to each other are sequentially connected to form a square, and the center of the square is the intersection point of the two pairs of bottom surface circle center connecting lines of the diagonal coils; the four identical electromagnetic coils (101) are respectively and fixedly arranged on the protection base (102); the four protection bases (102) are all arranged on the chassis slide rail (103) and can move on the chassis slide rail (103);
the surgical instrument (2) is a surgical operating rod with multiple degrees of freedom;
the surgical instrument (2) comprises a rigid operating rod (201), a first permanent magnet (202) and a second permanent magnet (203);
the first permanent magnet (202) is arranged at the top of the upper end of the rigid operating rod (201), and the second permanent magnet (203) is fixedly arranged at the middle upper part of the first permanent magnet (202) and is crossed with the first permanent magnet (202);
the method comprises the following steps:
step 1: modeling simulation of materials with equal proportion and the like is carried out on an electromagnetic coil (101) and a second permanent magnet (203) in the electromagnetic force feedback device to obtain an electromagnetic force feedback model;
determining the basic operation principle of the electromagnetic force feedback device: the electromagnetic coils (101) which are arranged at the diagonal positions give excitation currents with the same magnitude and direction;
determining an optimal current distribution strategy of the electromagnetic force feedback device: a three-dimensional tuple (X, y, z) is provided for an included angle theta in the positive direction of the X axis in a rectangular coordinate system formed by connecting the N pole of the second permanent magnet (203) and the centers of the bottom surfaces of the coils which are diagonal to each other, so as to determine the optimal distribution strategy of the current in the electromagnetic coil array (1);
x＝[θ/90]mod2
y＝|(45·[θ/45])mod2-θmod45|
z＝[θ/180]
in the three-dimensional tuple (x, y, z), x determines a solenoid coil pair applying current, y is an included angle of equivalent mapping in a minimum symmetric interval, and z is used for indicating the current direction in the coil pair; each theta corresponds to a unique triplet, namely a unique optimal current distribution strategy;
and 2, step: constructing a torque-current regression prediction model;
adjusting the positive direction included angle theta of the N pole of the second permanent magnet (203) in the electromagnetic force feedback model established in the step 1 and the X axis of the rectangular coordinate system and the exciting current value I of the electromagnetic coil, and calculating the torque value T of the second permanent magnet (203) rotating around the axis; thereby obtaining a plurality of groups of offline data to form an offline data set;
training a BPNN network and a GRNN network for regression prediction by using an offline data set, constructing a strong torque-current prediction model by using a neural network with optimal performance as a sub-model through a model fusion method, and thus quickly and accurately calculating an excitation current value I of a coil array according to an included angle theta between the N pole of a second permanent magnet (203) and the positive direction of the X axis of a rectangular coordinate system and a torque value T;
the specific implementation of the step 2 comprises the following sub-steps:
step 2.1: continuously adjusting the rotation angle theta of the second permanent magnet (203) and the excitation current value I of the electromagnetic coil (101), and solving to obtain corresponding torque data T so as to obtain a plurality of groups of offline data to form an offline data set;
step 2.2: constructing a BPNN network comprising an input layer, a hidden layer and an output layer; the input value of the network is a torque value T to which the second permanent magnet (203) is supposed to be subjected and an included angle theta between the N pole of the second permanent magnet (203) on the surgical instrument (2) and the positive direction of the X axis of the rectangular coordinate system, and the output value is an electromagnetic coil excitation current value I;
step 2.3: building a GRNN network comprising an input layer, a mode layer, a summation layer and an output layer; the input value of the network is a torque value T to which the second permanent magnet (203) is supposed to be subjected and an included angle theta between the N pole of the second permanent magnet (203) on the surgical instrument (2) and the positive direction of the X axis of the rectangular coordinate system, and the output value is an electromagnetic coil excitation current value I;
step 2.4: training a BPNN network and a GRNN network;
in the off-line training process of the BPNN, after off-line data sets are subjected to normalization processing, dividing the off-line data sets into a training set and a verification set by using a k-fold training method, and performing network training; then, taking the mean square error of the exciting current of the electromagnetic coil as a loss function, stopping training and storing the BPNN as one of the model fusion submodels when the error of the network on the verification set is smaller than a threshold value after training, and marking the model fusion submodel as a BPNN prediction submodel;
in the off-line training process of the GRNN, selecting a proper amount of training data according to the running time of a machine and randomly generating a super-parameter initial value so as to determine the network structure and parameters of the GRNN, and simultaneously selecting a plurality of pieces of data out of a training set in a data set as a verification set; carrying out GRNN network training by using a verification set and dynamically adjusting the value of the hyper-parameter according to an error in the training process; when the mean square error of the network on the verification set is smaller than a threshold value after training, the hyper-parameters and the training set are stored and used as a sub-model for fusing another model, and the sub-model is marked as a GRNN network prediction sub-model;
step 2.5: taking M brand new data as a prediction set and respectively inputting the data into the two submodels for current prediction;
by using an extreme value thought in mathematical statistics, solving a sub-model weight value which enables the variance of the deviation between the predicted value and the actual value to be minimum, and finally obtaining a moment-current regression prediction model as follows:
k 1 +k 2 ＝1
wherein
And
the BPNN network predictor model and the GRNN network predictor model correspond toTheta is an included angle between the N pole of the second permanent magnet (203) and the positive direction of the X axis in the rectangular coordinate system, t is a moment value of the second permanent magnet (203), and k is 1 And k 2 The weight values of the results are predicted corresponding to the two submodels,
the predicted value of the final strong prediction model is obtained;
and step 3: generating a current distribution pattern for the electromagnetic coil array;
and calculating a triad (x, y, z) according to theta, inputting the y and moment values T in the triad through a moment-current regression prediction model to solve an excitation current value I, finally forming a new triad (x, I, z), and guiding the current distribution of each electromagnetic coil (101) in the electromagnetic coil array (1) by using the triad so as to generate corresponding circumferential rotating force feedback.
2. The electromagnetic force feedback method for the virtual interventional surgical system as set forth in claim 1, wherein: the angle of the protection base (102) is adjustable, wherein the angle is an included angle between the bottom surface of the electromagnetic coil and the horizontal plane, and the angle adjusting range is 0-90 degrees.
3. The electromagnetic force feedback method for the virtual interventional surgical system as set forth in claim 1, wherein: the first permanent magnet (202) and the second permanent magnet (203) are both long cylindrical permanent magnets.
4. The electromagnetic force feedback method for virtual interventional surgery systems as defined in claim 1, characterized in that: the rigid operating rod (201) is made of polyethylene, the radius of the bottom surface is 9mm, and the height is 200 mm.
5. The electromagnetic force feedback method for the virtual interventional surgical system as set forth in claim 1, wherein: the radius of the bottom surface of the first permanent magnet (202) is 8mm, and the height of the first permanent magnet is 15 mm.
6. The electromagnetic force feedback method for virtual interventional surgery systems as defined in claim 1, characterized in that: the radius of the bottom surface of the second permanent magnet (203) is 6mm, and the height of the second permanent magnet is 35 mm.
7. The electromagnetic force feedback method for virtual interventional surgical systems as defined in any one of claims 1 to 6, wherein: the material of the electromagnetic coil (101) is Copper, the distance between the pair of the electromagnetic coils (101) which are diagonal to each other is 74mm, and the number of coil turns of a single electromagnetic coil (101) is 1024.
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