Orofacial muscle function training system and method for oral patients

Abstract

The present application relates to a method, device, computer equipment, storage medium and computer program product for oral patients' orofacial muscle function training. The method includes: waiting for and obtaining an oral muscle in place signal, and continuing to obtain pre-stored training standard data after obtaining the oral muscle in place signal; after outputting a training start prompt signal, continuously obtaining a real-time lip spacing signal, and judging whether the lip spacing signal enters a preset lip spacing interval in the training standard data; if so, continuously obtaining an angular displacement signal, and inputting the angular displacement signal into a preset bite force evaluation algorithm to calculate the bite force data; storing the bite force data in a historical bite force change data table, and generating and outputting the next stage training plan based on the historical bite force change data table. By obtaining the training data of the current orofacial muscle rehabilitation training, and comparing the calculated bite force data with the preset standard bite force data, the user's current rehabilitation progress has been confirmed, and a new training plan has been generated based on the new rehabilitation progress, thereby achieving reasonable changes in rehabilitation training, thereby improving the efficiency of the user's rehabilitation training.

Description

Technical Field

[0001] The present application relates to the field of medical device technology, and in particular to a method, device, computer equipment, storage medium and computer program product for orofacial muscle function training for oral patients. Background Art

[0002] The orofacial muscle trainer mainly trains the muscles of the upper and lower lips to improve the strength of the lip muscles. It is aimed at people with abnormalities in the oral and facial muscles and their functions. By re-educating their oral and maxillofacial nerves and muscles, it establishes a new correct muscle balance and acts on the dental arch, promoting the reconstruction of the alveolar bone and the normal growth and development of the maxillofacial structure.

[0003] The Chinese invention patent with publication number provides an orofacial muscle function training device, including a roughly C-shaped barrier screen. When worn, the barrier screen at least blocks the contact between the lip muscles and the jaw; the lingual side surface of the anterior tooth area of ​​the barrier screen is provided with a functional accessory that is detachably connected to the barrier screen, and the functional accessory is at least one of a flat guide plate, a tongue protrusion, and a tongue grid.

[0004] However, with the help of the above-mentioned oral and facial muscle function training device through traditional training methods, the following problems still exist: the patient's visit to the doctor's cycle is affected by many factors, resulting in the inability to frequently feedback the training effect, and the inability to adjust the training movements in time according to the existing training situation, resulting in a decrease in rehabilitation efficiency. Summary of the invention

[0005] Based on this, it is necessary to provide an orofacial muscle function training method, device, computer equipment, computer-readable storage medium and computer program product for oral patients that can improve the patient's rehabilitation efficiency in response to the above technical problems.

[0006] In a first aspect, the present application provides an orofacial muscle function training method for an oral patient, the method comprising:

[0007] Waiting for and obtaining a mouth muscle in place signal, and continuing to obtain pre-stored training standard data after obtaining the mouth muscle in place signal;

[0008] After outputting the training start prompt signal, continuously acquiring the real-time lip distance signal, and determining whether the lip distance signal enters the lip distance interval preset in the training standard data;

[0009] If yes, then the angular displacement signal is continuously acquired and input into a preset bite force evaluation algorithm to calculate the bite force data;

[0010] The bite force data is stored in a historical bite force change data table, and a next stage training plan is generated and output based on the historical bite force change data table.

[0011] In one embodiment, after the training start prompt signal is output, the specific steps of continuously acquiring the real-time lip distance signal and determining whether the lip distance signal enters the lip distance interval preset in the training standard data include:

[0012] The Hall voltage signal is obtained and input into a preset lip distance algorithm to calculate a real-time lip distance signal.

[0013] In one embodiment, the specific steps of continuously acquiring the angular displacement signal and inputting the angular displacement signal into a preset bite force evaluation algorithm to calculate the bite force data include:

[0014] Sampling the angular displacement signal at a preset frequency to obtain a sampled angular displacement signal and a corresponding timestamp signal;

[0015] Angular acceleration data is calculated based on the angular displacement signal and its corresponding time stamp signal;

[0016] The angular acceleration data is input into the bite force assessment algorithm to calculate bite force data.

[0017] In one embodiment, the specific steps of storing the bite force data in a historical bite force change data table, and generating and outputting the next stage training plan according to the historical bite force change data table include:

[0018] matching the bite force data with a preset bite force level range to obtain a current bite force level corresponding to the bite force data;

[0019] Determine whether the current bite force level is consistent with the bite force level corresponding to the previous bite force data stored in the historical bite force change data table;

[0020] If not, the bite force data, the current bite force level and the timestamp information of obtaining the bite force data are stored in the historical bite force change data table, and the bite force data is marked as phased growth bite force data.

[0021] In one embodiment, the specific steps of storing the bite force data in a historical bite force change data table, generating and outputting a next stage training plan according to the historical bite force change data table further include:

[0022] Inputting bite force level data corresponding to the bite force data marked as phased-increase bite force data into a preset bite force level-training content correspondence relationship to obtain training content corresponding to the bite force level;

[0023] The training content will be used as the training plan for the next stage and output.

[0024] In a second aspect, the present application also provides an orofacial muscle function training system for oral patients, the device comprising:

[0025] Mouth muscle in place detection module, used to obtain mouth muscle in place signals;

[0026] A lip distance detection module, used to continuously obtain a real-time lip distance signal and determine whether the lip distance signal enters a lip distance interval preset in the training standard data;

[0027] An angular displacement detection module, used for detecting angular displacement and outputting an angular displacement signal;

[0028] The data processing module is used to determine whether the lip distance signal enters the lip distance interval preset in the training standard data, and input the angular displacement signal into a preset bite force evaluation algorithm to calculate the bite force data.

[0029] The storage module is used to store pre-stored training standard data, bite force data, historical bite force change data table and the next stage training plan.

[0030] In one embodiment, the lip distance detection module includes:

[0031] The Hall voltage acquisition submodule is used to detect the magnetic induction intensity arranged near the Hall voltage acquisition submodule and convert the magnetic induction intensity into a Hall voltage signal.

[0032] In a third aspect, the present application further provides a computer device, the computer device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the following steps when executing the computer program:

[0033] Waiting for and obtaining a mouth muscle in place signal, and continuing to obtain pre-stored training standard data after obtaining the mouth muscle in place signal;

[0034] After outputting the training start prompt signal, continuously acquiring the real-time lip distance signal, and determining whether the lip distance signal enters the lip distance interval preset in the training standard data;

[0035] If yes, then the angular displacement signal is continuously acquired and input into a preset bite force evaluation algorithm to calculate the bite force data;

[0036] The bite force data is stored in a historical bite force change data table, and a next stage training plan is generated and output based on the historical bite force change data table.

[0037] In a fourth aspect, the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0038] Waiting for and obtaining a mouth muscle in place signal, and continuing to obtain pre-stored training standard data after obtaining the mouth muscle in place signal;

[0039] After outputting the training start prompt signal, continuously acquiring the real-time lip distance signal, and determining whether the lip distance signal enters the lip distance interval preset in the training standard data;

[0040] If yes, then the angular displacement signal is continuously acquired and input into a preset bite force evaluation algorithm to calculate the bite force data;

[0041] The bite force data is stored in a historical bite force change data table, and a next stage training plan is generated and output based on the historical bite force change data table.

[0042] In a fifth aspect, the present application further provides a computer program product, the computer program product comprising a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0043] Waiting for and obtaining a mouth muscle in place signal, and continuing to obtain pre-stored training standard data after obtaining the mouth muscle in place signal;

[0044] After outputting the training start prompt signal, continuously acquiring the real-time lip distance signal, and determining whether the lip distance signal enters the lip distance interval preset in the training standard data;

[0045] If yes, then the angular displacement signal is continuously acquired and input into a preset bite force evaluation algorithm to calculate the bite force data;

[0046] The bite force data is stored in a historical bite force change data table, and a next stage training plan is generated and output based on the historical bite force change data table.

[0047] This application obtains the training data of the current orofacial muscle rehabilitation training and compares the calculated bite force data with the preset standard bite force data to confirm the user's current rehabilitation progress and generate a new training plan based on the new rehabilitation progress, thereby achieving reasonable changes in rehabilitation training and improving the efficiency of the user's rehabilitation training. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 A diagram of an application environment of an orofacial muscle function training method for oral patients in one embodiment;

[0049] Figure 2 is a flow chart of an orofacial muscle function training method for oral patients in one embodiment;

[0050] Figure 3 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0052] The orofacial muscle function training method for oral patients provided in the embodiments of the present application can be applied to Figure 1 In the application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data that the server 104 needs to process. The data storage system can be integrated on the server 104, or it can be placed on the cloud or other network servers. Among them, the terminal 102 includes an oral area function training device for oral patients to wear, and may also include but is not limited to various personal computers, laptops, smart phones, tablets, Internet of Things devices and portable wearable devices. The Internet of Things devices can be smart speakers, smart TVs, smart air conditioners, smart car-mounted devices, etc. Portable wearable devices can be smart watches, smart bracelets, head-mounted devices, etc. The server 104 can be implemented with an independent server or a server cluster consisting of multiple servers.

[0053] In one embodiment, Figure 2 As shown, a method for training oral and facial muscle function for oral patients is provided, comprising the following steps:

[0054] Step S100: Waiting for and acquiring a mouth muscle in place signal, and continuing to acquire pre-stored training standard data after acquiring the mouth muscle in place signal.

[0055] Step S200: After outputting the training start prompt signal, continuously acquiring the real-time lip distance signal, and determining whether the lip distance signal enters the lip distance interval preset in the training standard data.

[0056] Among them, the training start prompt signal is a prompt information for prompting the user that the wearing has been completed and the rehabilitation training can be started. The output method of the prompt information includes but is not limited to a prompt sound, or displaying the prompt information through other display devices or display modules that can communicate with the oral facial muscle function recovery system for cavity patients; the preset lip distance interval is a preset high-precision lip distance measurement range. The oral facial muscle function training system for oral patients disclosed in the present application includes a lip distance detection module for continuously acquiring a real-time lip distance signal and judging whether the lip distance signal enters the preset lip distance interval in the training standard data; the lip distance detection module includes a permanent magnet submodule and a Hollow magnet submodule. The Hall voltage acquisition submodule, the permanent magnet submodule and the Hall voltage acquisition submodule are respectively located at the upper and lower contact parts for the patient's upper and lower lips to contact, and are arranged relatively. The permanent magnet submodule is used to provide a constant magnetic field, and the Hall voltage acquisition submodule is used to detect the magnetic induction intensity arranged near the Hall voltage acquisition submodule, and convert the magnetic induction intensity into a Hall voltage signal; since the magnetic flux lines (that is, the magnetic induction intensity) of the permanent magnet submodule are unevenly distributed, and the closer to the permanent magnet submodule, the more uniform the magnetic flux lines are distributed, by setting a preset lip distance interval, the lip distance can be detected after the lip distance enters the area with ideal magnetic flux lines distribution, thereby improving the accuracy of lip distance measurement.

[0057] Step S210: Acquire a Hall voltage signal, and input the Hall voltage signal into a preset lip distance algorithm to calculate a real-time lip distance signal.

[0058] The preset lip spacing algorithm includes the following formula:

[0059]

[0060] Wherein, B0 is the magnetic induction intensity of the permanent magnet arranged in the orofacial muscle function training system, k is the output voltage-magnetic induction intensity relationship constant of the Hall element used to obtain the Hall voltage signal, and V is the voltage value of the Hall voltage signal.

[0061] Step S300: If not, continue to obtain the real-time lip distance signal, and determine whether the lip distance signal enters the lip distance interval preset in the training standard data.

[0062] Step S400: If yes, then continue to acquire the angular displacement signal, and input the angular displacement signal into a preset bite force evaluation algorithm to calculate the bite force data.

[0063] The specific steps of step S400 include:

[0064] Step S410: sampling the angular displacement signal at a preset frequency to obtain a sampled angular displacement signal and a corresponding time stamp signal.

[0065] Step S420: Calculate angular acceleration data according to the angular displacement signal and its corresponding timestamp signal;

[0066] Step S430: Inputting the angular acceleration data into the bite force evaluation algorithm to calculate the bite force

[0067] Data. Among them, the bite force evaluation algorithm includes the following equation:

[0068]

[0069] In the above formula, F is the bite force data, I is the moment of inertia of the preset orofacial muscle function training system, R is the curvature radius of the arc motion trajectory of the angular displacement sampling point in the preset orofacial muscle function training system, α1, α2, ···, α n They are several groups of calculated acceleration data.

[0070] Step S500: storing the bite force data into a historical bite force change data table, generating and outputting a next stage training plan based on the historical bite force change data table.

[0071] The specific steps of step S500 include:

[0072] Step S510: Matching the bite force data with a preset bite force level range to obtain a current bite force level corresponding to the bite force data.

[0073] Step S520: Determine whether the current bite force level is consistent with the bite force level corresponding to the previous bite force data stored in the historical bite force change data table.

[0074] Step S530: If not, store the bite force data, the current bite force level and the timestamp information of obtaining the bite force data into the historical bite force change data table, and mark the bite force data as phased growth bite force data.

[0075] Step S540: inputting the bite force level data corresponding to the bite force data marked as the phased increase bite force data into the preset bite force level-training content correspondence relationship to obtain the training content corresponding to the bite force level.

[0076] It should be understood that, although the various steps in the flowcharts involved in the above-mentioned embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-mentioned embodiments can include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0077] Based on the same inventive concept, the embodiment of the present application also provides an orofacial muscle function training system for oral patients for implementing the above-mentioned orofacial muscle function training method for oral patients. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above-mentioned method, so the specific limitations in one or more embodiments of the orofacial muscle function training system for oral patients provided below can refer to the limitations of the orofacial muscle function training method for oral patients above, and will not be repeated here.

[0078] In one embodiment, an orofacial muscle function training system for an oral patient is provided, comprising:

[0079] Mouth muscle in place detection module, used to obtain mouth muscle in place signals;

[0080] The lip distance detection module is used to continuously obtain the real-time lip distance signal and determine whether the lip distance signal enters the lip distance interval preset in the training standard data; the lip distance detection module includes a permanent magnet submodule and a Hall voltage acquisition submodule, the permanent magnet submodule and the Hall voltage acquisition submodule are respectively located at the upper and lower abutting parts for the upper and lower lips of the patient to abut, and are arranged relatively, the permanent magnet submodule is used to provide a constant magnetic field, and the Hall voltage acquisition submodule is used to detect the magnetic induction intensity set near the Hall voltage acquisition submodule, and convert the magnetic induction intensity into a Hall voltage signal;

[0081] An angular displacement detection module, used for detecting angular displacement and outputting an angular displacement signal;

[0082] The data processing module is used to determine whether the lip distance signal enters the lip distance interval preset in the training standard data, and input the angular displacement signal into a preset bite force evaluation algorithm to calculate the bite force data.

[0083] The storage module is used to store pre-stored training standard data, bite force data, historical bite force change data table and the next stage training plan.

[0084] Each module in the above-mentioned orofacial muscle function training system for oral patients can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0085] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 3 As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WI FI, a mobile cellular network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a method for training oral and facial muscle functions for oral patients is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a button, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse, etc.

[0086] Those skilled in the art will understand that the structure shown in FIG. Y is merely a block diagram of a partial structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different arrangement of components.

[0087] In one embodiment, a computer device is provided, including a memory and a processor, wherein a computer program is stored in the memory, and when the processor executes the computer program, the following steps are implemented:

[0088] Step S100: Waiting for and acquiring a mouth muscle in place signal, and continuing to acquire pre-stored training standard data after acquiring the mouth muscle in place signal.

[0089] Step S200: After outputting the training start prompt signal, continuously acquiring the real-time lip distance signal, and determining whether the lip distance signal enters the lip distance interval preset in the training standard data.

[0090] Step S210: Acquire a Hall voltage signal, and input the Hall voltage signal into a preset lip distance algorithm to calculate a real-time lip distance signal.

[0091] Step S300: If not, continue to obtain the real-time lip distance signal, and determine whether the lip distance signal enters the lip distance interval preset in the training standard data.

[0092] Step S400: If yes, then continue to acquire the angular displacement signal, and input the angular displacement signal into a preset bite force evaluation algorithm to calculate the bite force data. The specific steps of step S400 include:

[0093] Step S410: sampling the angular displacement signal at a preset frequency to obtain a sampled angular displacement signal and a corresponding time stamp signal.

[0094] Step S420: Calculate angular acceleration data according to the angular displacement signal and its corresponding timestamp signal;

[0095] Step S430: Inputting the angular acceleration data into the bite force evaluation algorithm to calculate the bite force data.

[0096] Step S500: storing the bite force data into a historical bite force change data table, generating and outputting a next stage training plan based on the historical bite force change data table. The specific steps of step S500 include:

[0097] Step S510: Matching the bite force data with a preset bite force level range to obtain a current bite force level corresponding to the bite force data.

[0098] Step S520: Determine whether the current bite force level is consistent with the bite force level corresponding to the previous bite force data stored in the historical bite force change data table.

[0099] Step S530: If not, store the bite force data, the current bite force level and the timestamp information of obtaining the bite force data into the historical bite force change data table, and mark the bite force data as phased growth bite force data.

[0100] Step S540: inputting the bite force level data corresponding to the bite force data marked as the phased increase bite force data into the preset bite force level-training content correspondence relationship to obtain the training content corresponding to the bite force level.

[0101] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0102] Step S100: Waiting for and acquiring a mouth muscle in place signal, and continuing to acquire pre-stored training standard data after acquiring the mouth muscle in place signal.

[0103] Step S200: After outputting the training start prompt signal, continuously acquiring the real-time lip distance signal, and determining whether the lip distance signal enters the lip distance interval preset in the training standard data.

[0104] Step S210: Acquire a Hall voltage signal, and input the Hall voltage signal into a preset lip distance algorithm to calculate a real-time lip distance signal.

[0105] Step S300: If not, continue to obtain the real-time lip distance signal, and determine whether the lip distance signal enters the lip distance interval preset in the training standard data.

[0106] Step S400: If yes, then continue to acquire the angular displacement signal, and input the angular displacement signal into a preset bite force evaluation algorithm to calculate the bite force data. The specific steps of step S400 include:

[0107] Step S410: sampling the angular displacement signal at a preset frequency to obtain a sampled angular displacement signal and a corresponding time stamp signal.

[0108] Step S420: Calculate angular acceleration data according to the angular displacement signal and its corresponding timestamp signal;

[0109] Step S430: Inputting the angular acceleration data into the bite force evaluation algorithm to calculate the bite force data.

[0110] Step S500: storing the bite force data into a historical bite force change data table, generating and outputting a next stage training plan based on the historical bite force change data table. The specific steps of step S500 include:

[0111] Step S510: Matching the bite force data with a preset bite force level range to obtain a current bite force level corresponding to the bite force data.

[0112] Step S520: Determine whether the current bite force level is consistent with the bite force level corresponding to the previous bite force data stored in the historical bite force change data table.

[0113] Step S530: If not, store the bite force data, the current bite force level and the timestamp information of obtaining the bite force data into the historical bite force change data table, and mark the bite force data as phased growth bite force data.

[0114] Step S540: inputting the bite force level data corresponding to the bite force data marked as the phased increase bite force data into the preset bite force level-training content correspondence relationship to obtain the training content corresponding to the bite force level.

[0115] In one embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the following steps:

[0116] Step S100: Waiting for and acquiring a mouth muscle in place signal, and continuing to acquire pre-stored training standard data after acquiring the mouth muscle in place signal.

[0117] Step S200: After outputting the training start prompt signal, continuously acquiring the real-time lip distance signal, and determining whether the lip distance signal enters the lip distance interval preset in the training standard data.

[0118] Step S210: Acquire a Hall voltage signal, and input the Hall voltage signal into a preset lip distance algorithm to calculate a real-time lip distance signal.

[0119] Step S300: If not, continue to obtain the real-time lip distance signal, and determine whether the lip distance signal enters the lip distance interval preset in the training standard data.

[0120] Step S400: If yes, then continue to acquire the angular displacement signal, and input the angular displacement signal into a preset bite force evaluation algorithm to calculate the bite force data. The specific steps of step S400 include:

[0121] Step S410: sampling the angular displacement signal at a preset frequency to obtain a sampled angular displacement signal and a corresponding time stamp signal.

[0122] Step S420: Calculate angular acceleration data according to the angular displacement signal and its corresponding timestamp signal;

[0123] Step S430: Inputting the angular acceleration data into the bite force evaluation algorithm to calculate the bite force data.

[0124] Step S500: storing the bite force data into a historical bite force change data table, generating and outputting a next stage training plan based on the historical bite force change data table. The specific steps of step S500 include:

[0125] Step S510: Matching the bite force data with a preset bite force level range to obtain a current bite force level corresponding to the bite force data.

[0126] Step S520: Determine whether the current bite force level is consistent with the bite force level corresponding to the previous bite force data stored in the historical bite force change data table.

[0127] Step S530: If not, store the bite force data, the current bite force level and the timestamp information of obtaining the bite force data into the historical bite force change data table, and mark the bite force data as phased growth bite force data.

[0128] Step S540: inputting the bite force level data corresponding to the bite force data marked as the phased increase bite force data into the preset bite force level-training content correspondence relationship to obtain the training content corresponding to the bite force level.

[0129] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0130] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0131] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0132] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A method for training oral and facial muscle function for oral patients, characterized in that: The method comprises: Step S100: waiting and obtaining a mouth muscle in place signal, and continuing to obtain pre-stored training standard data after obtaining the mouth muscle in place signal; Step S200: After outputting the training start prompt signal, continuously acquiring the real-time lip distance signal, and determining whether the lip distance signal enters the lip distance interval preset in the training standard data; Step S210: Acquire a Hall voltage signal, and input the Hall voltage signal into a preset lip spacing algorithm to calculate a real-time lip spacing signal; wherein the preset lip spacing algorithm includes the following formula: Wherein, B0 is the magnetic induction intensity of the permanent magnet set in the orofacial muscle function training system, k is the output voltage-magnetic induction intensity relationship constant of the Hall element used to obtain the Hall voltage signal, and V is the voltage value of the Hall voltage signal; Step S300: If not, continue to obtain the real-time lip distance signal, and determine whether the lip distance signal enters the lip distance interval preset in the training standard data; Step S400: If yes, then continue to acquire the angular displacement signal, and input the angular displacement signal into a preset bite force evaluation algorithm to calculate the bite force data; the specific steps include: step S410: sampling the angular displacement signal at a preset frequency to obtain the sampled angular displacement signal and its corresponding timestamp signal; step S420: calculating the angular acceleration data according to the angular displacement signal and its corresponding timestamp signal; step S430: inputting the angular acceleration data into the bite force evaluation algorithm to calculate the bite force data; wherein the bite force evaluation algorithm includes the following equation: In the above formula, F is the bite force data, I is the moment of inertia of the preset orofacial muscle function training system, R is the curvature radius of the arc motion trajectory of the angular displacement sampling point in the preset orofacial muscle function training system, α1, α2, .., α n They are several groups of calculated acceleration data; Step S500: storing the bite force data into a historical bite force change data table, generating and outputting a next stage training plan based on the historical bite force change data table, and the specific steps include: Step S510: Match the bite force data with the preset bite force level range to obtain the current bite force level corresponding to the bite force data; Step S520: Determine whether the current bite force level is consistent with the bite force level corresponding to the previous bite force data stored in the historical bite force change data table; Step S530: If not, store the bite force data, the current bite force level and the timestamp information of obtaining the bite force data into the historical bite force change data table, and mark the bite force data as stage-increasing bite force data; Step S540: Input the bite force level data corresponding to the bite force data marked as stage-increasing bite force data into the preset bite force level-training content correspondence relationship to obtain the training content corresponding to the bite force level.

2. A system for training oral and facial muscle function for oral patients, the system implementing the method according to claim 1, characterized in that: The system comprises: Mouth muscle in place detection module, used to obtain mouth muscle in place signals; A lip distance detection module, used to continuously obtain a real-time lip distance signal and determine whether the lip distance signal enters a lip distance interval preset in the training standard data; An angular displacement detection module, used for detecting angular displacement and outputting an angular displacement signal; A data processing module, used for determining whether the lip distance signal enters the lip distance interval preset in the training standard data, and inputting the angular displacement signal into a preset bite force evaluation algorithm to calculate the bite force data; The storage module is used to store pre-stored training standard data, bite force data, historical bite force change data table and the next stage training plan.

3. The orofacial muscle function training system for oral patients according to claim 2, characterized in that: The lip distance detection module comprises: The Hall voltage acquisition submodule is used to detect the magnetic induction intensity arranged near the Hall voltage acquisition submodule and convert the magnetic induction intensity into a Hall voltage signal.

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