CN116414179A - Radio frequency control method, electronic device and computer readable storage medium - Google Patents
Radio frequency control method, electronic device and computer readable storage medium Download PDFInfo
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Abstract
A radio frequency control method, an electronic device and a computer readable storage medium, wherein the method comprises: selecting N learning resistors from a preset resistor range according to a preset sampling rule; selecting Y test voltages from a preset voltage range according to a preset sampling method; for each learning resistor, setting the resistor of the simulation device for simulating the target object as the learning resistor, taking each test voltage as the input voltage of the ablation device, and respectively determining S output powers corresponding to each test voltage to obtain Y multiplied by S data samples corresponding to the learning resistor; and fitting Y multiplied by S data samples corresponding to each learning resistor to obtain target fitting curves respectively corresponding to each learning resistor. The target fitting curve obtained by the method is used for determining the input voltage, so that the deviation of the output voltage can be reduced, and the deviation of the output power can be further reduced.
Description
Technical Field
The embodiment of the application relates to the technical field of data processing, in particular to a radio frequency control method, an electronic device and a computer readable storage medium.
Background
The ablation device carries out radio frequency ablation on the target object by outputting radio frequency energy so as to achieve the aim of treatment. During the radio frequency ablation process, the output power of the ablation device is generally required to be controlled, for example, the radio frequency ablation is performed by adopting a rated power method. In the related art, a fixed multiple is generally used as a voltage amplification factor of the ablation device, however, the fixed multiple is not accurate due to large differences of internal devices of the respective ablation devices, thereby resulting in a large difference between the power actually output by the ablation device and the required output power.
Disclosure of Invention
According to the radio frequency control method, the electronic device and the computer readable storage medium, the target fitting curve obtained by the method is adopted to determine the input voltage, so that the deviation of the output voltage can be reduced, and the deviation of the output power is further reduced.
In one aspect, an embodiment of the present application provides a radio frequency control method, where the method includes:
selecting N learning resistors from a preset resistor range according to a preset sampling rule;
selecting Y test voltages from a preset voltage range according to a preset sampling method;
setting a resistor of a simulation device for simulating the target object as the learning resistor for each learning resistor, respectively determining S output powers corresponding to each test voltage by taking each test voltage as an input voltage of the ablation device, and obtaining Y multiplied by S data samples corresponding to the learning resistor; wherein each data sample comprises one test voltage and one output power corresponding to the test voltage;
fitting Y multiplied by S data samples corresponding to each learning resistor to obtain target fitting curves respectively corresponding to each learning resistor; the target fitting curve is used for indicating the corresponding relation between the input voltage and the output power under the learning resistance, and the target fitting curve is used for controlling the ablation equipment to output radio-frequency energy to the target object.
An aspect of the embodiments of the present application further provides a radio frequency control device, including:
the first sampling module is used for selecting N learning resistors from a preset resistor range according to a preset sampling rule;
the second sampling module is used for selecting Y test voltages from a preset voltage range according to a preset sampling method;
the acquisition module is used for setting the resistance of the simulation device for simulating the target object as the learning resistance, taking each test voltage as the input voltage of the ablation device, respectively determining S output powers corresponding to each test voltage, and obtaining Y multiplied by S data samples corresponding to the learning resistance; wherein each data sample comprises one test voltage and one output power corresponding to the test voltage;
the fitting module is used for fitting Y multiplied by S data samples corresponding to each learning resistor to obtain target fitting curves respectively corresponding to each learning resistor; the target fitting curve is used for indicating the corresponding relation between the input voltage and the output power under the learning resistance, and the target fitting curve is used for controlling the ablation equipment to output radio-frequency energy to the target object.
An aspect of an embodiment of the present application further provides an electronic device, including: a memory and a processor;
the memory stores executable program code;
the processor, coupled to the memory, invokes the executable program code stored in the memory to perform the radio frequency control method as provided by the above embodiments.
An aspect of the embodiments of the present application further provides a non-transitory computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements a radio frequency control method as provided in the above embodiments.
According to the embodiments provided by the application, N learning resistors are selected from a preset resistor range according to a preset sampling rule; selecting Y test voltages from a preset voltage range according to a preset sampling method; for each learning resistor, setting the resistor of the simulation device for simulating the target object as the learning resistor, taking each test voltage as the input voltage of the ablation device, respectively determining S output powers corresponding to each test voltage, and obtaining Y multiplied by S data samples corresponding to the learning resistor; and fitting Y multiplied by S data samples corresponding to each learning resistor to obtain target fitting curves respectively corresponding to each learning resistor. The target fitting curve obtained by the method is used for determining the input voltage, so that the deviation of the output voltage can be reduced, and the deviation of the output power can be further reduced.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief description will be given below of the drawings that are needed in the embodiments or the prior art descriptions, it being obvious that the drawings in the following description are some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort to a person skilled in the art.
Fig. 1 is an application scenario diagram of an ablation device according to an embodiment of the present application;
fig. 2 is a flowchart of an implementation of a radio frequency control method according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of a radio frequency control device according to another embodiment of the present application;
fig. 4 is a schematic hardware structure of an electronic device according to an embodiment of the present application.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
As shown in fig. 1, when the ablation device works, after the input voltage passes through devices such as a power amplification board, the output voltage is amplified, and due to the difference of internal devices, the actual output voltage of each ablation device is different. In the related art, the ablation apparatus calculates the output voltage by amplifying a multiple, for example, three times, on the basis of the input voltage, takes the amplified voltage as the output voltage, and calculates the output power based on the output voltage and the measured resistance of the target object. The deviation of the output power obtained in this way is large, and it may take a long time to adjust from the output power to the target power, or a case where the output power is larger than the target power may occur. Therefore, it is necessary to provide a radio frequency control method to solve the problem of larger output power deviation.
Referring to fig. 2, fig. 2 is a flowchart illustrating an implementation of a radio frequency control method according to an embodiment of the present application, where the method may be implemented by an ablation device or other computer terminal connected thereto. But may also be implemented by other electronic intelligent devices. For convenience of explanation, the following embodiments use an ablation device as an execution body. The radio frequency control method comprises the following steps:
s101, selecting N learning resistors from a preset resistor range according to a preset sampling rule;
in this embodiment, N is an integer greater than 0, and may be, for example, 10, 15, 20, 23, 25, or the like.
In this embodiment, the predetermined sampling rule includes selecting a learning resistor from a predetermined range of resistors at each predetermined interval. The preset resistance range may be set according to the resistance range of the target object, for example, to 50-600Ω. One learning resistor may be selected every 25 Ω, 30 Ω, or 50 Ω interval.
S102, selecting Y test voltages from a preset voltage range according to a preset sampling method.
In this embodiment, the predetermined sampling method includes selecting a test voltage from a predetermined voltage range at each interval of a predetermined value. The preset voltage range may be set at a voltage value range commonly used for ablation devices, such as 0-48V. One test voltage may be selected every 2V, 4V or 6V interval.
S103, setting the resistor of the simulation device for simulating the target object as the learning resistor, taking each test voltage as the input voltage of the ablation device, and respectively determining S output powers corresponding to each test voltage to obtain Y multiplied by S data samples corresponding to the learning resistor; each data sample comprises a test voltage and an output power corresponding to the test voltage.
In the present embodiment, a simulation device may be used to simulate a target object, for example, a resistance-adjustable high-frequency electrotome device or the like. Thus, the analog device can be set as each learning resistance for that learning resistance. For example, for learning the resistance 50Ω, the resistance of the analog device may be set to 50Ω, and on the basis of this, according to the test voltages selected in step S102, the corresponding output power when each test voltage is taken as the input voltage may be measured, respectively.
As shown in fig. 1, the ablation device outputs power to the analog device, and the output power varies as the input voltage to the ablation device varies. Meanwhile, for analog devices with different resistances, the output power of the ablation device is also different.
In this embodiment, under the condition that the learning resistor is selected, each test voltage is used as an input voltage of the ablation device, and S output powers corresponding to each test voltage are respectively determined, including:
for each test voltage, setting the input voltage of the ablation device as the test voltage, and performing the following steps S times:
s1031, under the test voltage, measuring the output current passing through the analog device and the output voltage across the analog device.
S1032, determining an output power of the ablation device based on the output current and the output voltage, and taking the output power as one output power corresponding to the test voltage.
As shown in fig. 1, an input voltage (test voltage) is input to the ablation device, and an output current and an output voltage are input to the analog device (learning resistor) through the ablation device, and the output power of the ablation device is determined from the measured output current and output voltage, and is taken as one output power corresponding to the input voltage (test voltage).
It will be appreciated that, according to steps S1031-S1032, an output power of a test voltage can be determined, and S measurements can be performed while the input voltage is kept unchanged (i.e., the test voltage is set), so that S output powers can be obtained, which all correspond to the test voltage.
S104, fitting Y multiplied by S data samples corresponding to each learning resistor to obtain target fitting curves respectively corresponding to each learning resistor; the target fitting curve is used for indicating the corresponding relation between the input voltage and the output power under the learning resistance, and the target fitting curve is used for controlling the ablation equipment to output radio frequency energy to the target object.
In this embodiment, a target fitting curve is obtained by fitting the data samples corresponding to each learning resistor, that is, for N learning resistors, N target fitting curves corresponding to the learning resistors one to one may be obtained.
In the present embodiment, fitting is performed for each data sample corresponding to each learning resistor. Taking the learning resistance of 50Ω as an example, y×s data samples determined when the analog device is set to 50Ω can be fitted. Y is an integer greater than 0, and may be, for example, 10, 13, 15, or the like, and S is an integer greater than 0, and may be, for example, 3, 5, 7, 9, or the like. For example, if Y is 13 and s is 5, the number of data samples is 13×5.
According to the embodiment of the application, N learning resistors are selected from a preset resistor range according to a preset sampling rule; selecting Y test voltages from a preset voltage range according to a preset sampling method; for each learning resistor, setting the resistor of the simulation device for simulating the target object as the learning resistor, taking each test voltage as the input voltage of the ablation device, respectively determining S output powers corresponding to each test voltage, and obtaining Y multiplied by S data samples corresponding to the learning resistor; and fitting Y multiplied by S data samples corresponding to each learning resistor to obtain target fitting curves respectively corresponding to each learning resistor. The target fitting curve obtained by the method is used for determining the input voltage, so that the deviation of the output voltage can be reduced, and the deviation of the output power can be further reduced.
In a specific embodiment, the preset resistance range may be determined according to the target object, for example, the resistance range of the human tissue is generally 50-600Ω, and the preset resistance range may be set to 50-600Ω. In one embodiment, a learning resistor may be selected at every 25 Ω interval within the preset resistance range.
In a specific embodiment, the range of the preset voltage may be determined according to the capabilities of the ablation device and the output power required for the desired rf ablation, for example, the preset voltage value range may be set to 0-48V. In one embodiment, a test voltage may be selected at 4V intervals within the predetermined voltage range.
In the following, by way of example in table 1, 13 test voltages and 23 learning resistances can be determined as shown in table 1.
TABLE 1
Taking a 350 Ω learning resistor as an example, 5 measurements are respectively performed for each test voltage to obtain 5 sets of output currents and 5 sets of output voltages, and the corresponding output power (i.e. the product of the output current and the output voltage) is calculated for each measurement, as shown in table 2.
TABLE 2
In this embodiment, the learning resistor may be obtained by using standard source simulation such as a high-frequency electric knife device, and the output voltage and the output current may be directly measured by the standard source, and the output power may be obtained by calculating from the output voltage and the output current.
In an embodiment of the present application, fitting y×s data samples corresponding to each learning resistor to obtain a fitted curve corresponding to each learning resistor, includes:
s201, fitting Y multiplied by S data samples through at least one preset fitting method to obtain candidate fitting curves respectively corresponding to each preset fitting method; the preset fitting method comprises at least one of linear fitting, polynomial fitting and power function fitting.
S202, determining a target fitting curve from candidate fitting curves.
Further, the preset fitting method includes at least two of linear fitting, polynomial fitting and power function fitting, and the target fitting curve is determined from candidate fitting curves, including:
s203, comparing the fitting degree of each candidate fitting curve with respect to the candidate fitting curves respectively corresponding to each preset fitting method.
S204, determining the candidate fitting curve with the largest fitting degree as a target fitting curve.
Taking a polynomial fitting mode as an example, fitting 13×5 data samples in table 2, wherein each data sample comprises a test voltage and an output power, and obtaining a polynomial fitting curve under a 350 Ω learning resistance is as follows:
y＝-2E-08x 6 +4E-06x 5 -0.0003x 4 +0.0112x 3 -0.229x 2 +2.9998x+4.0376，
where x is the output power and y is the input voltage.
For other fitting methods, corresponding fitting curves may be obtained, which will not be described here.
In an embodiment of the present application, the method for calculating the fitting degree includes:
wherein y is i Representing the i-th measured output power in the Y x S data samples; f (f) i Representing the i-th predicted output power; SS (support System) reg Represents the sum of squares of regression, SS tot Representing the sum of the total squares; r is R 2 Representing the fitting degree, R is more than or equal to 0 2 ≤1。
Fitting a curve to the polynomial:
y＝-2E-08x 6 +4E-06x 5 -0.0003x 4 +0.0112x 3 -0.229x 2 +2.9998x+4.0376
the degree of fitting may be calculated and determined: r is R 2 ＝0.9993。
In an embodiment of the present application, after fitting y×s data samples corresponding to each of the learning resistances to obtain a target fitting curve corresponding to each of the learning resistances, the method includes:
s301, determining a learning resistance matched with a target object based on the resistance of the target object.
S302, according to the learning resistance matched with the target object, determining that a target fitting curve corresponding to the learning resistance is matched with the target object.
S303, determining input voltage corresponding to the output power according to the target fitting curve.
In this embodiment, when the ablation device performs the ablation operation, the resistor is not provided by using the simulation device any more, but the resistor of the target object is actually detected, the learning resistor corresponding to the resistor is matched, the corresponding target fitting line is selected according to the learning resistor, and then the adopted input voltage is determined according to the target fitting curve and the output power which is determined to be output.
In one embodiment, the resistance of the target object may be detected first, and then the learning resistance closest to the resistance of the target object may be found. For example, the absolute value of the difference between the resistance of the target object and the learning resistance may be calculated, and the learning resistance having the smallest absolute value is the closest learning resistance. Thus, the closest learning resistance may be determined to match the target object.
According to the embodiment of the application, N learning resistors are selected from a preset resistor range according to a preset sampling rule; selecting Y test voltages from a preset voltage range according to a preset sampling method; for each learning resistor, setting the resistor of the simulation device for simulating the target object as the learning resistor, taking each test voltage as the input voltage of the ablation device, respectively determining S output powers corresponding to each test voltage, and obtaining Y multiplied by S data samples corresponding to the learning resistor; and fitting Y multiplied by S data samples corresponding to each learning resistor to obtain target fitting curves respectively corresponding to each learning resistor. The target fitting curve obtained by the method is used for determining the input voltage, so that the deviation of the output voltage can be reduced, and the deviation of the output power can be further reduced.
Referring to fig. 3, a schematic structural diagram of a radio frequency control device according to an embodiment of the present application is provided. For convenience of explanation, only portions relevant to the embodiments of the present application are shown. The apparatus may be a computer terminal or a software module configured in the computer terminal. As shown in fig. 3, the apparatus includes: a first sampling module 101, a second sampling module 102, an acquisition module 103, and a fitting module 104.
The first sampling module 101 is configured to select N learning resistors from a preset resistor range according to a preset sampling rule;
the second sampling module 102 is configured to select Y test voltages from a preset voltage range according to a preset sampling method;
an obtaining module 103, configured to set, for each learning resistor, a resistor of a simulation device for simulating the target object as the learning resistor, and determine, with each test voltage as an input voltage of the ablation device, S output powers corresponding to each test voltage, respectively, to obtain y×s data samples corresponding to the learning resistor; wherein each data sample comprises one test voltage and one output power corresponding to the test voltage;
the fitting module 104 is configured to fit y×s data samples corresponding to each of the learning resistances, so as to obtain a target fitting curve corresponding to each of the learning resistances; the target fitting curve is used for indicating the corresponding relation between the input voltage and the output power under the learning resistance, and the target fitting curve is used for controlling the ablation equipment to output radio-frequency energy to the target object.
Further, the preset sampling rule includes: and selecting one learning resistor from a preset resistor range at intervals of a preset value.
Further, the preset sampling method comprises the following steps: selecting one test voltage from a preset voltage range at intervals of a preset value.
Further, the obtaining module 103 is further configured to set, for each of the test voltages, an input voltage of the ablation device to the test voltage, and perform the following steps S times: measuring an output current through the analog device and an output voltage across the analog device at the test voltage; an output power of the ablation device is determined based on the output current and the output voltage, and the output power is taken as one output power corresponding to the test voltage.
Further, the fitting module 105 is further configured to fit y×s data samples by at least one preset fitting method, so as to obtain candidate fitting curves respectively corresponding to each preset fitting method; the preset fitting method comprises at least one of linear fitting, polynomial fitting and power function fitting; and determining the target fitting curve from the candidate fitting curves.
Further, the fitting module 105 is further configured to compare, for candidate fitting curves corresponding to each preset fitting method, the fitting degrees of the candidate fitting curves; and determining the candidate fitting curve with the largest fitting degree as a target fitting curve. .
Further, the calculating method of the fitting degree comprises the following steps:
wherein y is i Representing the i-th measured output power in the Y x S data samples; f (f) i Representing the i-th predicted output power; SS (support System) reg Represents the sum of squares of regression, SS tot Representing the sum of the total squares; r is R 2 Representing the fitting degree, R is more than or equal to 0 2 ≤1。
Further, the fitting module 105 is further configured to determine, based on the resistance of the target object, the learning resistance that matches the target object; determining that the target fitting curve corresponding to the learning resistance is matched with the target object according to the learning resistance matched with the target object; and determining the input voltage corresponding to the output power according to the target fitting curve.
According to the embodiment of the application, N learning resistors are selected from a preset resistor range according to a preset sampling rule; selecting Y test voltages from a preset voltage range according to a preset sampling method; for each learning resistor, setting the resistor of the simulation device for simulating the target object as the learning resistor, taking each test voltage as the input voltage of the ablation device, respectively determining S output powers corresponding to each test voltage, and obtaining Y multiplied by S data samples corresponding to the learning resistor; and fitting Y multiplied by S data samples corresponding to each learning resistor to obtain target fitting curves respectively corresponding to each learning resistor. The target fitting curve obtained by the method is used for determining the input voltage, so that the deviation of the output voltage can be reduced, and the deviation of the output power can be further reduced.
The specific process of implementing the respective functions of the above modules may refer to the relevant content in the embodiment shown in fig. 2, and will not be described herein.
Referring to fig. 4, a hardware structure of an electronic device according to an embodiment of the present application is shown.
By way of example, the electronic apparatus may be any of various types of computer system devices that are non-removable or portable and that perform wireless or wired communications. In particular, the electronic apparatus may be a desktop computer, a server, a mobile phone or a smart phone (e.g., an iPhone-based TM, an Android-based TM phone), a Portable game device (e.g., a Nintendo DS (TM), a PlayStation Portable TM, gameboy Advance TM, iPhone (TM)), a laptop computer, a PDA, a Portable internet device, a Portable medical device, a smart camera, a music player, and a data storage device, other handheld devices, and devices such as watches, headphones, pendants, headphones, etc., and the electronic apparatus may also be other wearable devices (e.g., devices such as electronic glasses, electronic clothing, electronic bracelets, electronic necklaces, and other head-mounted devices (HMDs)).
As shown in fig. 4, the electronic device 100 may include a control circuit, which may include a storage and processing circuit 300. The storage and processing circuit 300 may include memory, such as hard disk drive memory, non-volatile memory (e.g., flash memory or other electronically programmable limited delete memory used to form solid state drives, etc.), volatile memory (e.g., static or dynamic random access memory, etc.), and the like, as embodiments of the present application are not limited. Processing circuitry in the storage and processing circuitry 300 may be used to control the operation of the electronic device 100. The processing circuitry may be implemented based on one or more microprocessors, microcontrollers, digital signal processors, baseband processors, power management units, audio codec chips, application specific integrated circuits, display driver integrated circuits, and the like.
The storage and processing circuit 300 may be used to run software in the electronic device 100, such as internet browsing applications, voice over internet protocol (Voice over Internet Protocol, VOIP) telephone call applications, email applications, media playing applications, operating system functions, and the like. Such software may be used to perform some control operations, such as image acquisition based on a camera, ambient light measurement based on an ambient light sensor, proximity sensor measurement based on a proximity sensor, information display functions implemented based on status indicators such as status indicators of light emitting diodes, touch event detection based on a touch sensor, functions associated with displaying information on multiple (e.g., layered) displays, operations associated with performing wireless communication functions, operations associated with collecting and generating audio signals, control operations associated with collecting and processing button press event data, and other functions in electronic device 100, to name a few.
Further, the memory stores executable program code, and a processor coupled to the memory invokes the executable program code stored in the memory to perform the radio frequency control method as described in the previous embodiments.
The executable program code includes various modules in the radio frequency control device as described in the embodiment shown in fig. 3, for example: a first sampling module 101, a second sampling module 102, an acquisition module 103, and a fitting module 104. The specific process of implementing the respective functions of the above modules may refer to the related description of fig. 2, and will not be repeated herein.
The electronic device 100 may also include input/output circuitry 420. The input/output circuit 420 is operable to enable the electronic apparatus 100 to input and output data, i.e., to allow the electronic apparatus 100 to receive data from an external device and also to allow the electronic apparatus 100 to output data from the electronic apparatus 100 to the external device. The input/output circuit 420 may further include a sensor 320. The sensors 320 may include ambient light sensors, light and capacitance based proximity sensors, touch sensors (e.g., light based touch sensors and/or capacitive touch sensors, where the touch sensors may be part of a touch display screen or may be used independently as a touch sensor structure), acceleration sensors, and other sensors, among others.
The input/output circuitry 420 may also include one or more displays, such as display 140. Display 140 may include one or a combination of several of a liquid crystal display, an organic light emitting diode display, an electronic ink display, a plasma display, and a display using other display technologies. Display 140 may include an array of touch sensors (i.e., display 140 may be a touch screen display). The touch sensor may be a capacitive touch sensor formed of an array of transparent touch sensor electrodes, such as Indium Tin Oxide (ITO) electrodes, or may be a touch sensor formed using other touch technologies, such as acoustic wave touch, pressure sensitive touch, resistive touch, optical touch, etc., as embodiments of the present application are not limited.
The electronic device 100 may also include an audio component 360. Audio component 360 may be used to provide audio input and output functionality for electronic device 100. The audio components 360 in the electronic device 100 may include speakers, microphones, buzzers, tone generators, and other components for generating and detecting sound.
The electronic device 100 may further include a battery, power management circuitry, and other input/output units 400. The input/output unit 400 may include buttons, levers, click wheels, scroll wheels, touch pads, keypads, keyboards, cameras, light emitting diodes, and other status indicators, etc.
A user may control the operation of the electronic device 100 by inputting commands through the input/output circuit 420, and may use output data of the input/output circuit 420 to enable receiving status information and other outputs from the electronic device 100.
Further, the embodiments of the present application also provide a non-transitory computer readable storage medium, which may be configured in the server in the foregoing embodiments, and a computer program is stored on the non-transitory computer readable storage medium, and the program is executed by a processor to implement the radio frequency control method described in the foregoing embodiments.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
Those of skill in the art will appreciate that the various illustrative modules/units and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus/terminal and method may be implemented in other manners. For example, the apparatus/terminal embodiments described above are merely illustrative, e.g., the division of modules or units is merely a logical functional division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present invention may implement all or part of the flow in the method of the above embodiment, and may also be implemented by a computer program to instruct related hardware. The computer program may be stored in a computer readable storage medium, which computer program, when being executed by a processor, may carry out the steps of the various method embodiments described above. Wherein the computer program comprises computer program code, which may be in the form of source code, object code, executable files or in some intermediate form, etc. The computer readable medium may include: any entity or device capable of carrying computer program code, a recording medium, a U disk, a removable hard disk, a magnetic disk, an optical disk, a computer Memory, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), an electrical carrier signal, a telecommunications signal, a software distribution medium, and so forth. It should be noted that the content of the computer readable medium can be appropriately increased or decreased according to the requirements of the jurisdiction's jurisdiction and the patent practice, for example, in some jurisdictions, the computer readable medium does not include electrical carrier signals and telecommunication signals according to the jurisdiction and the patent practice.
The above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, those skilled in the art will appreciate that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention.
Claims (10)
1. A method of radio frequency control of an ablation device for outputting radio frequency energy to a target object, the method comprising:
selecting N learning resistors from a preset resistor range according to a preset sampling rule;
selecting Y test voltages from a preset voltage range according to a preset sampling method;
setting a resistor of a simulation device for simulating the target object as the learning resistor for each learning resistor, respectively determining S output powers corresponding to each test voltage by taking each test voltage as an input voltage of the ablation device, and obtaining Y multiplied by S data samples corresponding to the learning resistor; wherein each data sample comprises one test voltage and one output power corresponding to the test voltage;
fitting Y multiplied by S data samples corresponding to each learning resistor to obtain target fitting curves respectively corresponding to each learning resistor; the target fitting curve is used for indicating the corresponding relation between the input voltage and the output power under the learning resistance, and the target fitting curve is used for controlling the ablation equipment to output radio-frequency energy to the target object.
2. The method of claim 1, wherein the predetermined sampling rules comprise: and selecting one learning resistor from a preset resistor range at intervals of a preset value.
3. The method of claim 1, wherein the predetermined sampling method comprises: selecting one test voltage from a preset voltage range at intervals of a preset value.
4. The method of claim 1, wherein said determining S output powers for each of said test voltages, respectively, using each of said test voltages as an input voltage to said ablation device, comprises:
setting an input voltage of the ablation device as the test voltage for each of the test voltages, and performing the following steps S times:
measuring an output current through the analog device and an output voltage across the analog device at the test voltage;
an output power of the ablation device is determined based on the output current and the output voltage, and the output power is taken as one output power corresponding to the test voltage.
5. The method of claim 1, wherein said fitting Y x S data samples corresponding to each of said learned resistances to obtain a target fitted curve corresponding to each of said learned resistances, respectively, comprises:
fitting Y multiplied by S data samples through at least one preset fitting method to obtain candidate fitting curves respectively corresponding to each preset fitting method; the preset fitting method comprises at least one of linear fitting, polynomial fitting and power function fitting;
and determining the target fitting curve from the candidate fitting curves.
6. The method of claim 5, wherein the predetermined fitting method comprises at least two of a linear fit, a polynomial fit, and a power function fit, and wherein determining the target fit curve from the candidate fit curves comprises:
comparing the fitting degree of each candidate fitting curve with respect to the candidate fitting curves respectively corresponding to each preset fitting method;
and determining the candidate fitting curve with the largest fitting degree as a target fitting curve.
7. The method of claim 1, wherein said fitting Y x S data samples corresponding to each of said learned resistances, after obtaining a target fit curve corresponding to each of said learned resistances, further comprises:
determining the learning resistance matched with the target object based on the resistance of the target object;
determining that the target fitting curve corresponding to the learning resistance is matched with the target object according to the learning resistance matched with the target object;
and determining the input voltage corresponding to the output power according to the target fitting curve matched with the target object.
8. A radio frequency control apparatus, comprising:
the first sampling module is used for selecting N learning resistors from a preset resistor range according to a preset sampling rule;
the second sampling module is used for selecting Y test voltages from a preset voltage range according to a preset sampling method;
the acquisition module is used for setting the resistance of the simulation device for simulating the target object as the learning resistance, taking each test voltage as the input voltage of the ablation device, respectively determining S output powers corresponding to each test voltage, and obtaining Y multiplied by S data samples corresponding to the learning resistance; wherein each data sample comprises one test voltage and one output power corresponding to the test voltage;
the fitting module is used for fitting Y multiplied by S data samples corresponding to each learning resistor to obtain target fitting curves respectively corresponding to each learning resistor; the target fitting curve is used for indicating the corresponding relation between the input voltage and the output power under the learning resistance, and the target fitting curve is used for controlling the ablation equipment to output radio-frequency energy to the target object.
9. An electronic device, comprising:
a memory and a processor;
the memory stores executable program code;
the processor coupled to the memory, invoking the executable program code stored in the memory, performing the steps in the radio frequency control method of any of claims 1-7.
10. A non-transitory computer readable storage medium having stored thereon a computer program, which when executed by a processor, implements the radio frequency control method according to any of claims 1 to 7.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202111643696.6A CN116414179A (en) | 2021-12-29 | 2021-12-29 | Radio frequency control method, electronic device and computer readable storage medium |
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| CN202111643696.6A CN116414179A (en) | 2021-12-29 | 2021-12-29 | Radio frequency control method, electronic device and computer readable storage medium |
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| CN116414179A true CN116414179A (en) | 2023-07-11 |
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