Hearing device debugging method, system and device and storage medium

Abstract

The invention discloses a hearing device debugging method, system and device and a storage medium, and the method comprises the steps: obtaining hearing configuration data of a user, the hearing configuration data being acquired based on a hearing device; the hearing configuration data are sent to a target server, the hearing configuration data are analyzed based on the target server, a debugging strategy is obtained, the debugging strategy is generated by a preset analysis model, and the preset analysis model is used for analyzing the hearing configuration data. The preset analysis model is obtained by performing iterative training on hearing configuration data of a plurality of users, an adjustment scheme corresponding to hearing equipment and a hearing debugging result; and debugging the hearing device according to the debugging strategy so as to improve the hearing of the user. According to the invention, the hearing treatment efficiency of the user is improved.

Description

Technical Field

[0001] The present application relates to the field of hearing diagnosis and treatment technology, and in particular to a hearing device debugging method, system, device and storage medium. Background Art

[0002] In the field of hearing health, when patients have hearing problems, professional technicians are often needed to perform personalized hearing tests and tinnitus diagnosis on the patients, and then perform fitting programming and debugging before the debugged hearing devices can be worn by the users. When the patients have other hearing problems, they are also required to go to the hospital for a follow-up visit, and after manual diagnosis by the doctor, the hearing devices need to be debugged again to improve the user's hearing condition. This undoubtedly increases the steps of hearing diagnosis and leads to lower efficiency of hearing treatment. Summary of the invention

[0003] The main purpose of this application is to provide a hearing device debugging method, system, device and storage medium, aiming to solve the technical problem in the related technology that professional technicians debug the hearing device after manually diagnosing the patient, resulting in low hearing treatment efficiency.

[0004] To achieve the above-mentioned purpose, an embodiment of the present application provides a hearing device debugging method, which is applied to a cloud platform, wherein the cloud platform is communicatively connected with the hearing device and the application terminal, and the hearing device debugging method comprises:

[0005] The cloud platform sends a data extraction instruction to the application terminal based on the received hearing adjustment instruction;

[0006] The application terminal sends a data extraction request to the hearing device based on the data extraction instruction, and the hearing device sends hearing configuration data to the application terminal based on the data extraction request, where the hearing configuration data is obtained based on the hearing device detecting the hearing data of the user;

[0007] The application terminal sends the hearing configuration data to the cloud platform;

[0008] The cloud platform sends the hearing configuration data to a target server, and based on the target server, analyzes the hearing configuration data to obtain a debugging strategy, wherein the debugging strategy is generated by a preset analysis model, and the preset analysis model is obtained by iterative training based on the hearing configuration data of multiple users, adjustment plans of corresponding hearing devices, and hearing debugging results; and the hearing device is debugged using the debugging strategy to improve the user's hearing.

[0009] In a possible implementation manner of the present application, the target server includes a preset analysis model, and the step of analyzing the hearing configuration data based on the target server to obtain a debugging strategy includes:

[0010] Based on the preset analysis model, predicting the hearing configuration data to obtain a prediction result;

[0011] Based on the prediction result, a debugging strategy of the hearing device is determined.

[0012] In a possible implementation manner of the present application, the step of debugging the hearing device using the debugging strategy includes:

[0013] Based on the debugging strategy, determining debugging configuration data;

[0014] configuring the debugging configuration data to the hearing device, and determining a debugging result of the hearing device;

[0015] If the debugging result shows that the hearing configuration data does not meet the preset hearing requirement, the process returns to the step of obtaining the user's hearing configuration data until the hearing configuration data meets the preset hearing requirement.

[0016] In a possible implementation manner of the present application, after the step of sending the hearing configuration data to the target server, the following steps are included:

[0017] Based on the target server, the hearing configuration data is matched with the case data in the preset database for similarity to obtain a data matching degree;

[0018] Selecting the first case data corresponding to the data matching degree being greater than a preset matching degree threshold;

[0019] The hearing device is adjusted based on a treatment plan corresponding to the first case data.

[0020] In a possible implementation manner of the present application, after the step of debugging the hearing device using the debugging strategy, the method further includes:

[0021] Acquiring sound loudness data of the hearing device;

[0022] If it is detected that the sound loudness data exceeds a preset loudness standard within a preset time period, an alarm is issued to the user.

[0023] In a possible implementation manner of the present application, after the step of debugging the hearing device using the debugging strategy, the method further includes:

[0024] The debugging strategy is visually displayed on multiple user terminals and stored in a preset database, so that multiple users corresponding to the user terminals can adjust the hearing devices as required.

[0025] In a possible implementation manner of the present application, the step of sending the hearing configuration data to the application terminal based on the data extraction request by the hearing device includes:

[0026] The hearing device detects hearing data of the user based on the data extraction request;

[0027] The hearing data is format converted to obtain the user's hearing configuration data, and the hearing configuration data is sent to the application terminal.

[0028] To achieve the above-mentioned purpose, the embodiment of the present application further provides a hearing device debugging system, wherein the hearing diagnosis and treatment system includes a cloud platform, an application terminal and a hearing device;

[0029] The hearing device is used to obtain the hearing configuration data of the user and transmit the hearing configuration data to the application terminal;

[0030] The application terminal is used to receive the hearing configuration data sent by the hearing device, analyze the hearing configuration data, and visually display the obtained analysis results;

[0031] Alternatively, the hearing configuration data is sent to a cloud platform, and the analysis configuration data fed back by the cloud platform based on the hearing configuration data is sent to the hearing device, so as to debug the hearing device;

[0032] The cloud platform is used to receive the hearing configuration data sent by the application terminal, and send the hearing configuration data to a target server. Based on the target server, the hearing configuration data is analyzed to obtain a debugging strategy, wherein the debugging strategy is generated by a preset analysis model, and the preset analysis model is obtained by iterative training based on the hearing configuration data of multiple users, adjustment plans of corresponding hearing devices, and hearing debugging results; and the hearing device is debugged using the debugging strategy to improve the user's hearing.

[0033] The present application also provides a hearing device debugging device, which is a physical node device, and includes: a memory, a processor, and a program of the hearing device debugging method stored in the memory and executable on the processor. When the program of the hearing device debugging method is executed by the processor, the steps of the hearing device debugging method described above can be implemented.

[0034] To achieve the above objective, a storage medium is further provided, wherein a hearing device debugging program is stored on the storage medium, and when the hearing device debugging program is executed by a processor, the steps of any of the above-mentioned hearing device debugging methods are implemented.

[0035] The present application provides a method, system, device and storage medium for debugging a hearing device. Compared with the related art, in which professional technicians perform manual diagnosis on patients and then debug the hearing device, resulting in low hearing treatment efficiency, in the present application, by establishing the interaction between the hearing device, the application terminal and the cloud platform, by obtaining the hearing configuration data of the user's hearing device, the hearing configuration data is sent from the application terminal to the cloud platform, the hearing configuration data is analyzed by the target server to obtain the debugging strategy, and the hearing device is debugged with the obtained debugging strategy, thereby achieving the debugging work of the hearing device without the participation of technicians, reducing the debugging steps of the hearing device, and because the debugging strategy is generated by a preset analysis model, and the model is obtained by iterative training based on the hearing configuration data of multiple users, the adjustment plan of the corresponding hearing device and the hearing debugging results, the debugging strategy has high accuracy, and thus, the hearing treatment efficiency is improved without the need for manual participation. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 This is a schematic diagram of the functional module architecture of the HAAS platform involved in the first embodiment of the hearing device debugging method of this application;

[0037] Figure 2 This is a flowchart of a second embodiment of the hearing device debugging method of the present application;

[0038] Figure 3 A schematic diagram of the device structure of the hardware operating environment involved in the embodiment of the present application;

[0039] Figure 4 This is a schematic diagram of the HAAS platform component architecture involved in the hearing device debugging method of this application;

[0040] Figure 5 This is a schematic diagram of the device structure involved in the hearing device debugging method of this application. DETAILED DESCRIPTION

[0041] 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.

[0042] The present application embodiment provides a hearing device debugging system. In the first embodiment of the hearing device debugging method of the present application, referring to Figure 1 and Figure 4 , the hearing diagnosis and treatment system includes a cloud platform, an application terminal and a hearing device;

[0043] The hearing device is used to obtain the hearing configuration data of the user and transmit the hearing configuration data to the application terminal;

[0044] The application terminal is used to receive the hearing configuration data sent by the hearing device, analyze the hearing configuration data, and visually display the obtained analysis results;

[0045] Alternatively, the hearing configuration data is sent to a cloud platform, and the analysis configuration data fed back by the cloud platform based on the hearing configuration data is sent to the hearing device, so as to debug the hearing device;

[0046] The cloud platform is used to receive the hearing configuration data sent by the application terminal, and send the hearing configuration data to a target server. Based on the target server, the hearing configuration data is analyzed to obtain a debugging strategy, wherein the debugging strategy is generated by a preset analysis model, and the preset analysis model is obtained by iterative training based on the hearing configuration data of multiple users, adjustment plans of corresponding hearing devices, and hearing debugging results; and the hearing device is debugged using the debugging strategy to improve the user's hearing.

[0047] It should be noted that hearing devices can be wearable hearing devices (WHD) and direct-attached hearing accessories (DAH). Edge hearing aids (EHD) are like digital hearing aids, usually with a digital signal processor (DSP) for processing acoustic algorithms. Such devices can connect to an APP on a smartphone via Bluetooth, use the APP to receive configuration data from a remote fitter (cloud), and then send the data to the hearing aid, so that the hearing aid can be personalized to fit the individual's audiogram. At the same time, hearing health data and user usage data can be captured on the hearing aid side, uploaded to the APP, and then uploaded to the cloud for algorithm model optimization. An example of a direct-attached hearing aid accessory (DAH) is an otoscope accessory that connects directly to a smartphone. This type of device does not have a high-end chip with a DSP processor in the WHD to process complex hearing aid algorithms, but it has its own simple ARM chip to perform pronunciation functions such as tinnitus generators. By working with an app on a smartphone, EHD acts as an edge computing device, collecting information about the body and its device usage directly from sensors in contact with the body, and uploading the data to the app and the cloud for further data analysis.

[0048] It should be understood that the application and Internet gateway (AIG) gateway device can be a smartphone, tablet computer, etc. The main role of the application and Internet gateway (AIG) gateway device is data communication, which is used to connect the hearing device and the cloud platform. The gateway device communicates with the hearing device using the Bluetooth protocol and uses wifi or 4G / 5G to connect to the Internet. The second role of the gateway device is to provide hearing service applications. Taking smartphones as an example, many hearing applications can be built on smartphones to work alone or closely with hearing devices. For example, there are many APPs such as noise detection, hearing test, hearing protection, tinnitus treatment, etc. The hearing protection APP is based on the WHO / ITC-H standard H.870. According to the standard, a person should not avoid hearing >89dB in 5 hours in 1 week. The application will collect sound loudness data from the earplugs, store and analyze it on the smartphone APP, and send an alert to the user. Another important task of the gateway device is to support the configuration of hearing aid headset devices through this data channel, allowing remote configuration of hearing devices. Such functions are the core part of remote hearing aid programming.

[0049] It should be understood that the cloud platform is a cloud-based hearing service platform, namely the HaaS platform (Hearing as a Service), which includes a server side for computing, such as Figure 4 As shown, the tasks that can be completed by the HaaS platform include:

[0050] (1) Based on its powerful computing power, data mining and AI engine, it provides medical logic analysis and guidance for many hearing services. For example, it can assess the patient's hearing condition and provide patients with personalized hearing treatment plans.

[0051] (2) The user-centric database can securely store patients’ personalized data for longitudinal analysis, which can be used to monitor and analyze patients’ hearing status over the long term so that treatment plans can be adjusted in a timely manner.

[0052] (3) Use artificial intelligence technology to continuously optimize the sound processing model and upgrade the calculation algorithm on the terminal hearing device, which can improve the sound quality and performance of the hearing aid and provide better hearing services.

[0053] (4) Data visualization can guide data to doctors, patients, and hearing aid manufacturers to provide support for improvement and decision-making. For example, doctors can view patients’ hearing conditions and treatment effects in real time, patients can understand their hearing conditions and treatment methods, and hearing aid manufacturers can improve their products based on user needs and feedback.

[0054] The present application provides a method, system, device and storage medium for debugging a hearing device. Compared with the related art, in which professional technicians perform manual diagnosis on patients and then debug the hearing device, resulting in low hearing treatment efficiency, in the present application, by establishing the interaction between the hearing device, the application terminal and the cloud platform, by obtaining the hearing configuration data of the user's hearing device, the hearing configuration data is sent from the application terminal to the cloud platform, the hearing configuration data is analyzed by the target server to obtain the debugging strategy, and the hearing device is debugged with the obtained debugging strategy, thereby achieving the debugging work of the hearing device without the participation of technicians, reducing the debugging steps of the hearing device, and because the debugging strategy is generated by a preset analysis model, and the model is obtained by iterative training based on the hearing configuration data of multiple users, the adjustment plan of the corresponding hearing device and the hearing debugging results, the debugging strategy has high accuracy, and thus, the hearing treatment efficiency is improved without the need for manual participation.

[0055] Further, based on the first embodiment of the present application, another embodiment of the present application is provided. In the embodiment of the present application, a method for debugging a hearing device is provided. In the first embodiment of the method for debugging a hearing device of the present application, referring to Figure 2 , the method comprises the following steps:

[0056] Step S10, the cloud platform sends a data extraction instruction to the application terminal based on the received hearing adjustment instruction;

[0057] It should be noted that the hearing device debugging method can be applied to a hearing device debugging apparatus, the hearing device debugging apparatus belongs to a hearing device debugging system, and the hearing device debugging system belongs to a hearing device debugging device.

[0058] It should be noted that the execution subject of this method is the cloud platform in the hearing device debugging system, and the hearing device debugging system includes hearing devices, applications and Internet Gateway (AIG) gateway devices, and cloud platforms, such as Figure 4 As shown, during the data interaction process, when the hearing device detects a problem with the user's hearing data, it will feed back the data to the terminal in real time, and then the terminal will send the data to the server, so that the server processes the data to obtain the debugging strategy of the hearing device, and then adjust the configuration data of the hearing device with the debugging strategy. The data transmission direction is represented as follows: uplink data (left->right): user biological sign data, application data, device usage data, downlink data (right->left): analysis data, configuration data, software update.

[0059] It should be noted that the hearing configuration data is the user's hearing condition data collected by the hearing device, for example, the user's neurological hearing loss and conductive hearing loss data. Collecting this data can reflect the user's hearing condition.

[0060] The step S10 of obtaining the user's hearing configuration data includes:

[0061] Step S11, receiving hearing device data;

[0062] It should be noted that the hearing device data is the user's hearing data stored in the hearing device.

[0063] Step S12: performing format conversion processing on the hearing device data to obtain the user's hearing configuration data.

[0064] It should be noted that the data collected by the hearing device needs to be converted into a predetermined format before it can be used. After the hearing device data is converted into a format, the user's hearing configuration data is obtained.

[0065] Step S20: the application terminal sends a data extraction request to the hearing device based on the data extraction instruction, and the hearing device sends hearing configuration data to the application terminal based on the data extraction request, where the hearing configuration data is obtained based on the hearing device detecting the hearing data of the user;

[0066] It should be noted that after receiving the data extraction instruction, the application terminal sends a data extraction request to the hearing device, and then extracts the hearing configuration data of the hearing device.

[0067] It should be noted that the hearing configuration data may be the user's hearing data within a future period of time extracted after receiving the data extraction instruction, or may be the hearing data within a historical period of time stored in the hearing device.

[0068] Step S30, the application terminal sends the hearing configuration data to the cloud platform;

[0069] It should be noted that after the application terminal receives the hearing configuration data, it sends the hearing configuration data to the cloud platform for analysis.

[0070] In step S40, the cloud platform sends the hearing configuration data to a target server, and based on the target server, analyzes the hearing configuration data to obtain a debugging strategy, wherein the debugging strategy is generated by a preset analysis model, and the preset analysis model is obtained by iteratively training the hearing configuration data of multiple users, the adjustment schemes of the corresponding hearing devices, and the hearing debugging results; and the hearing device is debugged according to the debugging strategy to improve the user's hearing.

[0071] It should be noted that the data transmission direction of the hearing device data is: hearing device-gateway device (application terminal)-cloud platform.

[0072] It should be noted that the target server is stored in the cloud platform and is mainly used to perform data calculation and model processing functions. After the target server receives the hearing configuration data, it predicts and processes the hearing configuration data through a preset analysis model to obtain the required debugging strategy. Then, the debugging strategy can be sent to the hearing device or gateway device to adjust the configuration of the hearing device.

[0073] It should be noted that the preset analysis model is a neural network model based on deep reinforcement learning. Since the preset analysis model is obtained through iterative training of the hearing configuration data of multiple users, the adjustment plans of the corresponding hearing devices and the hearing effects, after training the model with multiple sample data, the preset analysis model can obtain more accurate prediction results.

[0074] The target server includes a preset analysis model, and the step S40 of analyzing the hearing configuration data based on the target server to obtain a debugging strategy includes:

[0075] Step S41, performing prediction processing on the hearing configuration data based on the preset analysis model to obtain a prediction result;

[0076] It should be noted that in the processing of the preset analysis model, the hearing configuration data is subjected to feature conversion, and the feature data obtained by the hearing configuration data conversion is processed and classified by a convolutional network, a fully connected layer network, etc., and a prediction result is output.

[0077] Step S42: determining a debugging strategy for the hearing device based on the prediction result.

[0078] It should be noted that, through the prediction results, an adjustment plan for the classification corresponding to the hearing configuration data, that is, a debugging strategy, can be obtained, and then the hearing device can be adjusted through the debugging strategy.

[0079] The step S40 of debugging the hearing device according to the debugging strategy further includes:

[0080] Based on the debugging strategy, determining debugging configuration data;

[0081] It should be noted that the debugging configuration data is the device data that needs to be changed in the debugging strategy.

[0082] It should be noted that the method of debugging the hearing device may be: changing the configuration data of the hearing device, after changing the configuration data, receiving the hearing test form fed back by the hearing device, and observing from the hearing test form whether the user's hearing has improved.

[0083] configuring the debugging configuration data to the hearing device, and determining a debugging result of the hearing device;

[0084] It should be noted that after the debugging configuration data is configured in the hearing device, the user's audiogram within a preset time period is collected, and the user's audiogram is used to reflect the debugging result of the hearing device.

[0085] If the debugging result shows that the hearing configuration data does not meet the preset hearing requirement, the process returns to the step of obtaining the user's hearing configuration data until the hearing configuration data meets the preset hearing requirement.

[0086] It should be noted that the preset hearing requirement can be less than 30 decibels, less than 25 decibels, etc., and can be changed according to the user's actual hearing condition and the therapeutic degree of the hearing device, without specific limitation.

[0087] It should be noted that when the debugging result does not meet the requirements, the user's hearing device needs to be debugged again until the user's hearing configuration data is normal.

[0088] Wherein, after the step S40 of debugging the hearing device according to the debugging strategy, the method further includes:

[0089] Acquiring sound loudness data of the hearing device;

[0090] It should be noted that the sound loudness data is the external noise data collected by the hearing device.

[0091] If it is detected that the sound loudness data exceeds a preset loudness standard within a preset time period, an alarm is issued to the user.

[0092] It should be noted that when noise greater than 89 decibels (or 100 decibels) is heard for a long time, it will damage the human eardrum. At this time, an alarm needs to be issued to warn the user.

[0093] It should be noted that the preset loudness standard may be less than 89 decibels, less than 100 decibels, etc., without specific limitation.

[0094] It should be noted that the preset time period can be 1 hour, 2 hours, etc., and there is no specific limitation.

[0095] In this embodiment, by acquiring the hearing configuration data of the user, the hearing configuration data is analyzed based on the target server to obtain a debugging strategy, and the hearing device is debugged with the obtained debugging strategy, thereby achieving the debugging of the hearing device without the participation of technical personnel, and reducing the debugging steps of the hearing device. Since the debugging strategy is generated by a preset analysis model, and the model is iteratively trained based on the hearing configuration data of multiple users, the adjustment plan of the corresponding hearing device and the hearing effect, the debugging strategy has higher accuracy, thereby improving the efficiency of hearing treatment without the need for human participation.

[0096] Further, based on the first embodiment and the second embodiment of the present application, another embodiment of the present application is provided. In this embodiment, after the step S40 of sending the hearing configuration data to the target server, the following steps are included:

[0097] Step A1, based on the target server, performing similarity matching between the hearing configuration data and case data in a preset database to obtain a data matching degree;

[0098] It should be noted that after the target server receives the hearing configuration data of the user, it will perform similarity matching between the hearing configuration data and the case data in the preset database, and observe whether there is similar case data in the preset database to reduce data processing time.

[0099] It should be noted that the data matching degree can be 80%, 90%, etc., and there is no specific limitation.

[0100] Step A2, selecting the first case data corresponding to the data matching degree being greater than a preset matching degree threshold;

[0101] It should be noted that the preset matching degree threshold may be 80%, 90%, 100%, etc., and is not specifically limited.

[0102] Step A3: adjusting the hearing device based on the treatment plan corresponding to the first case data.

[0103] It should be noted that when the data matching degree of the first case data exceeds the preset matching degree threshold, it means that the two cases are highly similar, and you can try to debug the hearing device with the solution of this case.

[0104] In this embodiment, by comparing the hearing configuration data with the data in the preset database, the required treatment plan is selected according to the data matching degree, thereby reducing the data processing time.

[0105] Further, based on the first embodiment, the second embodiment and the third embodiment of the present application, another embodiment of the present application is provided. In this embodiment, after the step S40 of debugging the hearing device according to the debugging strategy, the method further includes:

[0106] Step B1, visually displaying the debugging strategy on multiple user terminals and storing it in a preset database, so that multiple users corresponding to the user terminals can adjust the hearing devices as required.

[0107] It should be noted that the multiple user ends include doctors, patients and hearing aid manufacturers, and the debugging strategies can be displayed to the three parties. For example, doctors can view the patient's hearing condition and treatment effect in real time, patients can understand their own hearing condition and treatment methods, and hearing aid manufacturers can improve their products based on user needs and feedback.

[0108] In this embodiment, by displaying the debugging strategy to multiple users, multiple users can be encouraged to adjust the hearing device, which can improve the treatment efficiency compared to the previous method of relying solely on doctors to treat patients.

[0109] Reference Figure 3 , Figure 3 It is a schematic diagram of the device structure of the hardware operating environment involved in the embodiment of the present application.

[0110] like Figure 3 As shown, the hearing device debugging device may include: a processor 1001 , a memory 1005 , and a communication bus 1002 . The communication bus 1002 is used to implement connection and communication between the processor 1001 and the memory 1005 .

[0111] Optionally, the hearing device debugging device may further include a user interface, a network interface, a camera, an RF (Radio Frequency) circuit, a sensor, a WiFi module, etc. The user interface may include a display screen (Display), an input submodule such as a keyboard (Keyboard), and the optional user interface may also include a standard wired interface and a wireless interface. The network interface may include a standard wired interface and a wireless interface (such as a WI-FI interface).

[0112] Those skilled in the art will understand that Figure 3 The hearing device debugging device structure shown in the figure does not constitute a limitation on the hearing device debugging device, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0113] like Figure 3As shown, the memory 1005 as a storage medium may include an operating system, a network communication module and a hearing device debugging program. The operating system is a program that manages and controls the hardware and software resources of the hearing device debugging device, and supports the operation of the hearing device debugging program and other software and / or programs. The network communication module is used to realize the communication between the components inside the memory 1005, and the communication with other hardware and software in the hearing device debugging system.

[0114] exist Figure 3 In the hearing device debugging device shown, the processor 1001 is used to execute the hearing device debugging program stored in the memory 1005 to implement the steps of any one of the above-mentioned hearing device debugging methods.

[0115] The specific implementation of the hearing device debugging device of the present application is basically the same as the above-mentioned embodiments of the hearing device debugging method, and will not be repeated here.

[0116] The present application also provides a hearing device debugging device, referring to Figure 5 , the hearing device debugging device also includes:

[0117] The receiving module 101 is used to send a data extraction instruction to the application terminal based on the received hearing adjustment instruction;

[0118] The analysis module 102 is used to send the hearing configuration data to a target server, analyze the hearing configuration data based on the target server, and obtain a debugging strategy, wherein the debugging strategy is generated by a preset analysis model, and the preset analysis model is obtained by iteratively training the hearing configuration data of multiple users, the adjustment scheme of the corresponding hearing device, and the hearing debugging results; and debug the hearing device according to the debugging strategy to improve the user's hearing.

[0119] In a possible implementation manner of the present application, the analysis module includes:

[0120] A processing unit, configured to perform prediction processing on the hearing configuration data based on the preset analysis model to obtain a prediction result;

[0121] The first determining unit is configured to determine a debugging strategy for the hearing device based on the prediction result.

[0122] In a possible implementation manner of the present application, the analysis module further includes:

[0123] A second determining unit, configured to determine debugging configuration data based on the debugging strategy;

[0124] a configuration unit, configured to configure the debugging configuration data to the hearing device and determine a debugging result of the hearing device;

[0125] A returning unit is used to return to the step of obtaining the user's hearing configuration data if the debugging result shows that the hearing configuration data does not meet the preset hearing requirement, until the hearing configuration data meets the preset hearing requirement.

[0126] In a possible implementation manner of the present application, the device further includes:

[0127] A matching module, used for performing similarity matching between the hearing configuration data and case data in a preset database based on the target server to obtain a data matching degree;

[0128] A selection module, used for selecting the first case data corresponding to the data matching degree being greater than a preset matching degree threshold;

[0129] An adjustment module is used to adjust the hearing device based on a treatment plan corresponding to the first case data.

[0130] In a possible implementation manner of the present application, the device further includes:

[0131] An acquisition module, used to acquire sound loudness data of the hearing device;

[0132] The alarm module is used to issue an alarm to the user if it is detected that the sound loudness data exceeds a preset loudness standard within a preset time period.

[0133] In a possible implementation manner of the present application, the device further includes:

[0134] The visualization display module is used to visualize the debugging strategy on multiple user terminals and store it in a preset database so that multiple users corresponding to the user terminals can adjust the hearing devices as required.

[0135] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0136] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0137] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0138] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A method for debugging a hearing device, characterized in that: Applied to a cloud platform, the cloud platform is in communication with a hearing device and an application terminal, and the hearing device debugging method includes: The cloud platform sends a data extraction instruction to the application terminal based on the received hearing adjustment instruction; The application terminal sends a data extraction request to the hearing device based on the data extraction instruction, and the hearing device sends hearing configuration data to the application terminal based on the data extraction request, where the hearing configuration data is obtained based on the hearing device detecting the hearing data of the user; The application terminal sends the hearing configuration data to the cloud platform; The cloud platform sends the hearing configuration data to a target server, and based on the target server, analyzes the hearing configuration data to obtain a debugging strategy, wherein the debugging strategy is generated by a preset analysis model, and the preset analysis model is obtained by iterative training based on the hearing configuration data of multiple users, adjustment plans of corresponding hearing devices, and hearing debugging results; and the hearing device is debugged using the debugging strategy to improve the user's hearing.

2. The hearing device debugging method according to claim 1, characterized in that: The target server includes a preset analysis model, and the step of analyzing the hearing configuration data based on the target server to obtain a debugging strategy includes: Based on the preset analysis model, predicting the hearing configuration data to obtain a prediction result; Based on the prediction result, a debugging strategy of the hearing device is determined.

3. The hearing device debugging method according to claim 1, characterized in that: The step of debugging the hearing device using the debugging strategy comprises: Based on the debugging strategy, determining debugging configuration data; configuring the debugging configuration data to the hearing device, and determining a debugging result of the hearing device; If the debugging result shows that the hearing configuration data does not meet the preset hearing requirement, the process returns to the step of obtaining the user's hearing configuration data until the hearing configuration data meets the preset hearing requirement.

4. The hearing device debugging method according to claim 1, characterized in that: After the step of sending the hearing configuration data to the target server, the method further comprises: Based on the target server, the hearing configuration data is matched with the case data in the preset database for similarity to obtain a data matching degree; Selecting the first case data corresponding to the data matching degree being greater than a preset matching degree threshold; The hearing device is adjusted based on a treatment plan corresponding to the first case data.

5. The hearing device debugging method according to claim 1, characterized in that: After the step of debugging the hearing device using the debugging strategy, the method further includes: Acquiring sound loudness data of the hearing device; If it is detected that the sound loudness data exceeds a preset loudness standard within a preset time period, an alarm is issued to the user.

6. The hearing device debugging method according to claim 1, characterized in that: After the step of debugging the hearing device using the debugging strategy, the method further includes: The debugging strategy is visually displayed on multiple user terminals and stored in a preset database, so that multiple users corresponding to the user terminals can adjust the hearing devices as required.

7. The hearing device debugging method according to claim 1, characterized in that: The step of sending the hearing configuration data to the application terminal based on the data extraction request by the hearing device comprises: The hearing device detects hearing data of the user based on the data extraction request; The hearing data is format converted to obtain the user's hearing configuration data, and the hearing configuration data is sent to the application terminal.

8. A hearing device debugging system, characterized in that: The hearing diagnosis and treatment system includes a cloud platform, an application terminal and a hearing device; The hearing device is used to obtain the hearing configuration data of the user and transmit the hearing configuration data to the application terminal; The application terminal is used to receive the hearing configuration data sent by the hearing device, analyze the hearing configuration data, and visually display the obtained analysis results; Alternatively, the hearing configuration data is sent to a cloud platform, and the analysis configuration data fed back by the cloud platform based on the hearing configuration data is sent to the hearing device, so as to debug the hearing device; The cloud platform is used to receive the hearing configuration data sent by the application terminal, and send the hearing configuration data to a target server, and analyze the hearing configuration data based on the target server to obtain a debugging strategy, wherein the debugging strategy is generated by a preset analysis model, and the preset analysis model is obtained by iterative training based on the hearing configuration data of multiple users, the adjustment scheme of the corresponding hearing device, and the hearing debugging results; The hearing device is debugged using the debugging strategy to improve the user's hearing.

9. A hearing device debugging device, characterized in that: The device comprises: a memory, a processor, and a hearing device debugging program stored in the memory and executable on the processor, wherein the hearing device debugging program is configured to implement the steps of the hearing device debugging method according to any one of claims 1 to 7.

10. A computer storage medium, characterized in that: The computer storage medium stores a hearing device debugging program, and when the hearing device debugging program is executed by the processor, the steps of the hearing device debugging method according to any one of claims 1 to 7 are implemented.

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