Wearable intelligent non-invasive closed-loop deep brain regulation and control system and method, equipment and medium

Abstract

The invention provides a wearable intelligent non-invasive closed-loop deep brain regulation and control system and method, equipment and a medium, and the system comprises an acquisition stimulation module and a high-precision acquisition stimulation controller. The high-precision acquisition stimulation controller comprises a personalized electrical conduction modeling and simulation optimization module, a double-stage intelligent regulation and control system, a self-adaptive closed-loop regulation and control module and a three-dimensional stacked hardware architecture design module. Through three technical innovations of multi-physics field simulation driving design, three-dimensional heterogeneous integration and intelligent closed-loop control, the problems of open-loop regulation unidirectivity, limited equipment microminiaturization, dependence on artificial experience and the like of a traditional deep brain stimulation system are solved, a portable and wearable 64-channel closed-loop deep brain regulation system in a natural state is realized, and space environment limitation is eliminated.

Description

Technical Field

[0001] The present invention relates to the field of time-interference electrical stimulation neural regulation technology, and in particular to a wearable intelligent non-invasive closed-loop deep brain regulation system and method, equipment, and medium. Background Art

[0002] Currently, electrical stimulation systems include time-interferometric electrical stimulation, transcranial electrical stimulation, and transcranial magnetic stimulation. Time-interferometric electrical stimulation uses two high-frequency currents to form a low-frequency envelope electric field deep in the brain, selectively activating deep neurons. Transcranial electrical stimulation includes transcranial alternating current stimulation (tACS) and transcranial direct current stimulation (tDCS), which apply low-frequency currents through the scalp to regulate cortical excitability. Transcranial magnetic stimulation uses a pulsed magnetic field to penetrate the skull to generate induced currents, non-invasively regulating cortical neuron activity, with a stimulation depth of up to 2-3 cm.

[0003] Transcranial electrical stimulation and transcranial magnetic stimulation have shallow stimulation depths and cannot stimulate deep brain areas. Temporal interferometric electrical stimulation can only stimulate a single target, and the target changes during the regulation process, requiring dynamic optimization of the target stimulation parameters. Existing stimulation regulation systems cannot adaptively adjust stimulation parameters, rely on manual experience, are large in size, and cannot be used in a closed-loop manner. At the same time, some diseases require the patient to wear a stimulation regulation system for a long time. Existing stimulation systems require patients to remain seated for long periods of time, affecting their daily lives. Summary of the Invention

[0004] In order to achieve the above-mentioned objectives and other advantages of the present invention, the first objective of the present invention is to provide a wearable intelligent non-invasive closed-loop deep brain control system, including an acquisition stimulation module and a high-precision acquisition stimulation controller, wherein the high-precision acquisition stimulation controller includes a personalized electrical conduction modeling and simulation optimization module, a two-stage intelligent control system, and an adaptive closed-loop control module; wherein,

[0005] The personalized electrical conduction modeling and simulation optimization module is used to establish a high-precision bioelectromagnetic model, build a layered head model, set the conductivity of different brain tissues, use finite element meshing technology, simulate the electric field distribution according to the target location, set different electrical stimulation parameters for simulation optimization, and obtain simulated stimulation parameters;

[0006] The dual-stage intelligent control system is used to collect EEG signals of the subject through a host computer, perform imaging evaluation operations to obtain target locations, and then obtain stimulation parameters based on stimulation simulation; and set parameters of the acquisition stimulation module based on the stimulation parameters;

[0007] After the parameter setting is completed, the acquisition and stimulation module is physically separated from the host computer and is worn on the subject to achieve electrical stimulation control in a free state;

[0008] The adaptive closed-loop control module is used to continue collecting new EEG signals after the subject has been stimulated for a period of time to evaluate the brain state and update the stimulation parameters.

[0009] Furthermore, the personalized electrical conduction modeling and simulation optimization module realizes brain tissue segmentation based on T1 and T2MRI data, obtains segmentation results of scalp, skull, cerebrospinal fluid, gray matter, and white matter, calculates anisotropic conductivity, and establishes a high-precision bioelectromagnetic model.

[0010] Furthermore, the high-precision acquisition stimulation controller also includes a three-dimensional stacked hardware architecture design module, which includes a heterogeneous integrated chip system. The bottom layer of the heterogeneous integrated chip system uses high-density logic chips to perform stimulation parameter generation and dynamic time-sharing scheduling, and the middle layer uses a layered current source array to achieve multi-channel independent output.

[0011] Furthermore, the three-dimensional stacked hardware architecture design module also includes an intelligent scheduling engine, which uses time division multiplexing to multiplex single-channel current into independent stimulation circuits.

[0012] A second object of the present invention is to provide a wearable intelligent non-invasive closed-loop deep brain control method, which is applied to the above-mentioned system and comprises the following steps:

[0013] Establish a high-precision bio-electromagnetic model based on T1 and T2MRI data;

[0014] A layered head model was constructed, the electrical conductivity of different brain tissues was set, finite element meshing technology was used to simulate the electric field distribution according to the target location, and different electrical stimulation parameters were set for simulation optimization to obtain the simulated stimulation parameters;

[0015] Collect the subject's EEG signals for imaging evaluation, obtain the target location, and obtain stimulation parameters based on stimulation simulation;

[0016] Setting parameters of an acquisition stimulation module according to the stimulation parameters;

[0017] After the subject has been stimulated for a period of time, new EEG signals are continuously collected to evaluate the brain state and update the stimulation parameters.

[0018] Furthermore, the step of establishing a high-precision bio-electromagnetic model based on T1 and T2 MRI data includes:

[0019] Based on T1 and T2MRI data, brain tissue segmentation is achieved, and the segmentation results of scalp, skull, cerebrospinal fluid, gray matter, and white matter are obtained;

[0020] Calculate anisotropic conductivity and establish high-precision bioelectromagnetic models.

[0021] Furthermore, the method further comprises the steps of:

[0022] Executes stimulation parameter generation and dynamic time-sharing scheduling, and performs multi-channel independent output.

[0023] Furthermore, the method further comprises the steps of:

[0024] Time division multiplexing is used to multiplex single-channel current into independent stimulation circuits.

[0025] A third object of the present invention is to provide a computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above method when executing the computer program.

[0026] A fourth object of the present invention is to provide a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the above method when executed by a processor.

[0027] Compared with the prior art, the present invention has the following beneficial effects:

[0028] The present invention provides a wearable intelligent non-invasive closed-loop deep brain regulation system and method. Through three major technological innovations: multi-physics field simulation-driven design, three-dimensional heterogeneous integration, and intelligent closed-loop control, it solves the core problems of traditional neural regulation equipment, such as large size, inability to use in a free state, non-personalization, and reliance on manual experience.

[0029] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention and to implement it according to the contents of the description, the following preferred embodiments of the present invention are described in detail with reference to the accompanying drawings. The specific implementation methods of the present invention are given in detail by the following embodiments and the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of this application. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0031] Figure 1 Schematic diagram of wearable intelligent non-invasive closed-loop deep brain control system Figure 1 ;

[0032] Figure 2 This is a flow chart of the wearable intelligent non-invasive closed-loop deep brain control system;

[0033] Figure 3 Schematic diagram of wearable intelligent non-invasive closed-loop deep brain control system Figure 2 ;

[0034] Figure 4 This is a flow chart of the wearable intelligent non-invasive closed-loop deep brain control method;

[0035] Figure 5 Establish a flow chart for high-precision bio-electromagnetic models;

[0036] Figure 6 It is a schematic diagram of computer equipment;

[0037] Figure 7 A schematic diagram of a computer-readable storage medium. DETAILED DESCRIPTION

[0038] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. It should be noted that, without conflict, the embodiments or technical features described below can be arbitrarily combined to form new embodiments.

[0039] Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative work shall fall within the scope of protection of the present invention.

[0040] The figure numbers in this application are only used to distinguish the various steps in the scheme and are not used to limit the execution order of the various steps. The specific execution order is subject to the description in the specification.

[0041] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention.

[0042] Time-interference electrical stimulation in the prior art is a non-invasive neuromodulation technology based on the principle of high-frequency current interference. Its core is to apply two high-frequency currents with similar frequencies but slight differences to form a low-frequency envelope electric field deep in the brain, thereby selectively activating deep neurons without interfering with superficial brain tissue. Considering that some diseases have multiple targets and the locations of the targets will change. Therefore, the present invention proposes a wearable intelligent non-invasive closed-loop deep brain control system to achieve multi-target stimulation. The specific scheme is as follows:

[0043] Example 1

[0044] A wearable intelligent non-invasive closed-loop deep brain control system, such as Figure 1-Figure 3 As shown, the system 100 includes a collection stimulation module 110 ( Figure 3The acquisition stimulation array in the embodiment of the present invention), a high-precision acquisition stimulation controller 120, wherein the high-precision acquisition stimulation controller 120 includes a personalized electrical conduction modeling and simulation optimization module 121, a two-stage intelligent control system 122, and an adaptive closed-loop control module 123; wherein,

[0045] The personalized electrical conduction modeling and simulation optimization module is used to establish a high-precision bioelectromagnetic model, build a layered head model, set the conductivity of different brain tissues, use finite element meshing technology, simulate the electric field distribution according to the target location, set different electrical stimulation parameters for simulation optimization, and obtain simulation stimulation parameters, including the selection of stimulation electrodes, current magnitude, frequency and other parameters;

[0046] Furthermore, the personalized electrical conduction modeling and simulation optimization module realizes brain tissue segmentation based on T1 and T2MRI data, obtains segmentation results of scalp, skull, cerebrospinal fluid, gray matter, and white matter, calculates anisotropic conductivity, and establishes a high-precision bioelectromagnetic model.

[0047] The dual-stage intelligent control system is used to collect EEG signals of the subject through a host computer, perform imaging evaluation operations to obtain target locations, and then obtain stimulation parameters based on stimulation simulation; and set parameters of the acquisition stimulation module based on the stimulation parameters calculated by the host computer;

[0048] After the parameter setting is completed, the host computer does not need to be involved. The subject can physically separate the acquisition and stimulation module from the host computer and wear it on the subject. For example, the subject can wear the acquisition and stimulation module on the arm to achieve electrical stimulation control in a free state.

[0049] The adaptive closed-loop control module is used to continuously collect new EEG signals after the subject has been stimulated for a period of time to assess their brain state and update the stimulation parameters. After the parameters are updated, the subject can physically separate the stimulation device from the host computer, achieving a portable, wearable, intelligent closed-loop control effect.

[0050] In some embodiments, the high-precision acquisition stimulation controller 120 also includes a three-dimensional stacked hardware architecture design module 124, which includes a heterogeneous integrated chip system. The bottom layer of the heterogeneous integrated chip system uses high-density logic chips to perform stimulation parameter generation and dynamic time-sharing scheduling, and the middle layer uses a layered current source array to achieve multi-channel independent output.

[0051] Furthermore, the three-dimensional stacked hardware architecture design module also includes an intelligent scheduling engine that uses time-division multiplexing to multiplex single-channel currents into independent stimulation circuits. This technology enables a compact size, low power consumption, and portability for extended use.

[0052] This invention breaks through the problems of the traditional deep brain stimulation system's open-loop control unidirectionality, limited equipment miniaturization, and reliance on artificial experience, and realizes a portable, wearable 64-channel closed-loop deep brain control system in a natural state, breaking free from spatial environmental limitations.

[0053] Example 2

[0054] A wearable intelligent non-invasive closed-loop deep brain control method is applied to the above system. For a detailed description of the system, please refer to the corresponding description in the embodiment of the wearable intelligent non-invasive closed-loop deep brain control system, which will not be repeated here. Figure 4 As shown, the method includes the following steps:

[0055] S200, build a high-precision bio-electromagnetic model based on T1 and T2MRI data;

[0056] Further, if Figure 5 As shown, the steps of establishing a high-precision bio-electromagnetic model based on T1 and T2 MRI data include:

[0057] S201. Based on T1 and T2 MRI data, brain tissue segmentation is performed to obtain the segmentation results of scalp, skull, cerebrospinal fluid, gray matter, and white matter;

[0058] S202. Calculate anisotropic conductivity and establish a high-precision bioelectromagnetic model.

[0059] S210: Build a layered head model, set the electrical conductivity of different brain tissues, use finite element meshing technology to simulate the electric field distribution according to the target location, set different electrical stimulation parameters for simulation optimization, and obtain simulation stimulation parameters, including the selection of stimulation electrodes, current magnitude, frequency, and other parameters;

[0060] S220, collecting the subject's EEG signal to perform imaging evaluation operations, obtain the target position, and obtain stimulation parameters based on stimulation simulation;

[0061] S230, setting parameters of the acquisition stimulation module according to the stimulation parameters;

[0062] Specifically, after the parameter setting is completed, the host computer does not need to be involved. The subject can physically separate the acquisition and stimulation module from the host computer and wear it on the subject. For example, the subject can wear the acquisition and stimulation module on the arm to achieve electrical stimulation control in a free state.

[0063] S240. After the subject is stimulated for a period of time, new EEG signals are continuously collected to evaluate the brain state and update the stimulation parameters.

[0064] After updating the parameters, the subjects can physically separate the acquisition and stimulation equipment from the host computer, thereby achieving a portable, wearable intelligent closed-loop control effect.

[0065] In some embodiments, the steps further include:

[0066] Execute stimulation parameter generation and dynamic time-sharing scheduling, and perform multi-channel independent output;

[0067] Specifically, the wearable intelligent non-invasive closed-loop deep brain regulation system adopts a three-dimensional stacked hardware architecture design, including a heterogeneous integrated chip system: the bottom layer uses high-density logic chips to perform stimulation parameter generation and dynamic time-sharing scheduling, and the middle layer uses a layered current source array to achieve multi-channel independent output.

[0068] Time division multiplexing is used to multiplex single-channel current into independent stimulation circuits.

[0069] Specifically, the wearable intelligent non-invasive closed-loop deep brain regulation system utilizes a three-dimensional stacked hardware architecture, including an intelligent scheduling engine that uses time-division multiplexing to multiplex single-channel current into independent stimulation circuits. This technology enables compact size and low power consumption, enabling portable and long-term use.

[0070] This invention breaks through the problems of the traditional deep brain stimulation system's open-loop control unidirectionality, limited equipment miniaturization, and reliance on artificial experience, and realizes a portable, wearable 64-channel closed-loop deep brain control system in a natural state, breaking free from spatial environmental limitations.

[0071] Example 3

[0072] A computer device 300, such as Figure 6 As shown, the device includes a memory 310, a processor 320, and a computer program 330 stored in the memory and executable on the processor. When the processor executes the computer program, the steps of a wearable intelligent non-invasive closed-loop deep brain control method are implemented. For a detailed description of the method, please refer to the corresponding description in the above method embodiment and will not be repeated here.

[0073] Example 4

[0074] A computer-readable storage medium such as Figure 7 As shown, a computer program is stored thereon, and when the computer program is executed by the processor, the steps of a wearable intelligent non-invasive closed-loop deep brain control method are implemented. For a detailed description of the method, please refer to the corresponding description in the above method embodiment, and no further details will be given here.

[0075] The number of devices and processing scales described herein are intended to simplify the description of the present invention. Applications, modifications, and variations of the present invention will be readily apparent to those skilled in the art.

[0076] Although the embodiments of the present invention have been disclosed above, they are not limited to the applications listed in the description and implementation methods. They can be fully applied to various fields suitable for the present invention. For those familiar with the art, additional modifications can be easily implemented. Therefore, without departing from the general concept defined by the claims and the scope of equivalents, the present invention is not limited to the specific details and illustrations shown and described herein.

[0077] The apparatus, computer device, non-volatile computer storage medium, and method provided in the embodiments of this specification correspond to each other. Therefore, the apparatus, computer device, and non-volatile computer storage medium also have similar beneficial technical effects as the corresponding method. Since the beneficial technical effects of the method have been described in detail above, the beneficial technical effects of the corresponding apparatus, computer device, and non-volatile computer storage medium will not be repeated here.

[0078] Those skilled in the art will also appreciate that, in addition to implementing the controller in pure computer-readable program code, it is entirely possible to implement the same functionality by programming the method steps logically, such as through logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the devices included therein for implementing various functions can also be considered structures within the hardware component. Alternatively, the devices for implementing various functions can be considered both software units implementing the method and structures within the hardware component.

[0079] The systems, devices, or units described in the above embodiments can be implemented by computer chips or physical devices, or by products with certain functions. For ease of description, the above devices are described separately by function, with each unit described separately. Of course, when implementing one or more embodiments of this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware components.

[0080] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems, or computer program products. Therefore, the embodiments of this specification may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the embodiments of this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0081] This specification is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of this specification. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0082] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0083] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0084] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0085] This specification may be described in the general context of computer-executable instructions executed by a computer, such as program units. Generally, program units include routines, programs, objects, components, data structures, and the like that perform specific tasks or implement specific abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communications network. In a distributed computing environment, program units may be located in local and remote computer storage media, including storage devices.

[0086] The various embodiments in this specification are described in a progressive manner. Similar parts between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the system embodiments are generally similar to the method embodiments, so the description is relatively simple. For relevant parts, refer to the description of the method embodiments.

[0087] The foregoing is merely an example of the present invention and is not intended to limit the present invention to one or more embodiments. It will be apparent to those skilled in the art that various modifications and variations may be made to the present invention to one or more embodiments. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention to one or more embodiments shall be included within the scope of the claims of the present invention to one or more embodiments.

Claims

1. A wearable intelligent non-invasive closed-loop deep brain control system, characterized by: It includes an acquisition stimulation module and a high-precision acquisition stimulation controller. The high-precision acquisition stimulation controller includes a personalized electrical conduction modeling and simulation optimization module, a two-stage intelligent control system, and an adaptive closed-loop control module. The personalized electrical conduction modeling and simulation optimization module is used to establish a high-precision bioelectromagnetic model, build a layered head model, set the conductivity of different brain tissues, use finite element meshing technology, simulate the electric field distribution according to the target location, set different electrical stimulation parameters for simulation optimization, and obtain simulated stimulation parameters; The dual-stage intelligent control system is used to collect EEG signals of the subject through a host computer, perform imaging evaluation operations to obtain target locations, and then obtain stimulation parameters based on stimulation simulation; and set parameters of the acquisition stimulation module based on the stimulation parameters; After the parameter setting is completed, the acquisition and stimulation module is physically separated from the host computer and is worn on the subject to achieve electrical stimulation control in a free state; The adaptive closed-loop control module is used to continue collecting new EEG signals after the subject has been stimulated for a period of time to evaluate the brain state and update the stimulation parameters.

2. A wearable intelligent non-invasive closed-loop deep brain control system according to claim 1, characterized in that: The personalized electrical conduction modeling and simulation optimization module implements brain tissue segmentation based on T1 and T2 MRI data, obtains segmentation results of the scalp, skull, cerebrospinal fluid, gray matter, and white matter, calculates anisotropic conductivity, and establishes a high-precision bioelectromagnetic model.

3. The wearable intelligent non-invasive closed-loop deep brain control system according to claim 1, characterized in that: The high-precision acquisition stimulation controller also includes a three-dimensional stacked hardware architecture design module, which includes a heterogeneous integrated chip system. The bottom layer of the heterogeneous integrated chip system uses a high-density logic chip to perform stimulation parameter generation and dynamic time-sharing scheduling, and the middle layer uses a layered current source array to achieve multi-channel independent output.

4. A wearable intelligent non-invasive closed-loop deep brain control system according to claim 3, characterized in that: The three-dimensional stacked hardware architecture design module also includes an intelligent scheduling engine, which uses time division multiplexing to multiplex single-channel current into independent stimulation circuits.

5. A wearable intelligent non-invasive closed-loop deep brain control method, applied to the system according to any one of claims 1 to 4, characterized in that: The following steps are involved: Establish a high-precision bio-electromagnetic model based on T1 and T2MRI data; A layered head model was constructed, the electrical conductivity of different brain tissues was set, finite element meshing technology was used to simulate the electric field distribution according to the target location, and different electrical stimulation parameters were set for simulation optimization to obtain the simulated stimulation parameters; Collect the subject's EEG signals for imaging evaluation, obtain the target location, and obtain stimulation parameters based on stimulation simulation; Setting parameters of an acquisition stimulation module according to the stimulation parameters; After the subject has been stimulated for a period of time, new EEG signals are continuously collected to evaluate the brain state and update the stimulation parameters.

6. A wearable intelligent non-invasive closed-loop deep brain control method as claimed in claim 5, characterized in that: The steps of establishing a high-precision bioelectromagnetic model based on T1 and T2 MRI data include: Based on T1 and T2MRI data, brain tissue segmentation is achieved, and the segmentation results of scalp, skull, cerebrospinal fluid, gray matter, and white matter are obtained; Calculate anisotropic conductivity and establish high-precision bioelectromagnetic models.

7. A wearable intelligent non-invasive closed-loop deep brain control method as claimed in claim 5, characterized in that: Also includes the steps: Executes stimulation parameter generation and dynamic time-sharing scheduling, and performs multi-channel independent output.

8. A wearable intelligent non-invasive closed-loop deep brain control method as claimed in claim 7, characterized in that: Also includes the steps: Time division multiplexing is used to multiplex single-channel current into independent stimulation circuits.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 5 to 8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 5 to 8 are implemented.

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