Digital assessment method and system for selecting suitable hearing apparatus

Abstract

Provided are a digital assessment method and system for selecting a suitable hearing apparatus. The method comprises: completing login, wherein the login is completed to an assessment system by a user by means of a user interface, and the assessment system comprises a processing unit and a memory unit; performing numerical scoring on a hearing history, wherein a hearing history problem is captured by the processing unit and the memory unit in the assessment system, and the questioning and answering of the hearing history problem are performed with the user by means of the processing unit; and recommending an optional hearing apparatus type, wherein after the processing unit and the memory unit capture the hearing apparatus type, the processing unit performs scoring and sorting according to a recorded answer result of the hearing history problem, and recommends at least one hearing apparatus type according to the cumulative score sorting of scores.

Description

Digital assessment method and system for selecting appropriate hearing devices Technical Field

[0001] This invention relates to a digital assessment method, particularly for hearing device purchase scenarios. Through online Q&A sessions and professional hearing screening, users can, with full knowledge and consent, independently assess whether they are suitable for online product selection or require in-person assistance from a hearing aid specialist. The purpose of this digital assessment method is to provide a self-assessment mechanism, enabling users to eliminate unsuitable risk factors through professional hearing screening, more clearly understand their needs, and make appropriate purchasing decisions. Background Art

[0002] When purchasing a hearing device (such as a hearing aid or hearing assistive device), in addition to hardware requirements (such as functionality, price, etc.), it is more important to consult with a professional (such as an audiologist) based on the hearing strength and life needs of the hearing-impaired user. After consultation and testing, the professional will assist the user in selecting, evaluating, and adjusting the device to achieve the effect of subsequent rehabilitation. For example, choosing a hearing device with a suitable appearance for the user can allow the user to wear it for a longer period of time, so that the auditory nerve can be stimulated for a period of time, thereby achieving the effect of rehabilitation or maintenance. Therefore, before purchasing a hearing device, it is very important to consult with a professional and conduct testing. This ensures that the product selection meets the individual needs of the user and provides the best hearing support effect.

[0003] In this method, hearing devices are defined as hearing equipment with a gain-amplifying sound effect. Among them, hearing aids are defined as hearing devices that need to be evaluated and set by experts before they can be purchased, while hearing assistive devices refer to hearing devices that users can purchase without expert evaluation, setting, and adjustment. However, it should be noted that many hearing assistive devices are usually designed only for specific hearing levels, but manufacturers often do not mark detailed applicable hearing ranges, and there is also a lack of third-party service platforms that can predict the applicability of various products. In addition, there is currently a lack of any professional instructional videos or online courses that assist in adjusting volume prescriptions. Therefore, if users rashly purchase hearing assistive devices on their own, there is a great risk of choosing unsuitable products, which may even cause damage to their hearing.

[0004] Based on the above, the digital assessment method of this invention provides users with a self-assessment mechanism. Through online Q&A and professional hearing screening algorithms, users can more clearly understand their needs and applicable scope, and make informed and consent-based decisions about hearing device purchases. This helps avoid rashly purchasing unsuitable products and ensures hearing protection and optimal hearing aid effectiveness.

[0005] Summary of the Invention

[0006] The present invention aims to provide a digital evaluation system and method for selecting appropriate hearing devices. This system provides users with a self-assessment mechanism. Through online Q&A and professional hearing screening algorithms, users can more clearly understand their needs and applicable scope, and make informed and consenting decisions about purchasing hearing devices.

[0007] To achieve the above objectives, the present invention discloses a digital assessment method for selecting a suitable hearing device. The method comprises: completing a login, in which a user logs into an assessment system through a user interface, the assessment system comprising a processing unit and a memory unit; performing a numerical hearing history scoring, in which the processing unit in the assessment system retrieves hearing history questions from the memory unit and then conducts a question-and-answer session with the user; and recommending a suitable hearing device type, in which the processing unit retrieves a classification of hearing device types from the memory unit, scores and ranks the answers to the hearing history questions, and recommends at least one hearing device type based on the cumulative score.

[0008] When the processing unit detects a restricted question from the questions and answers about the hearing history, the processing unit selects whether to continue the assessment based on the user's choice.

[0009] The present invention further discloses a digital assessment method for selecting a suitable hearing device, which is characterized by comprising: completing a login, in which a user logs into an assessment system through a user interface, the assessment system comprising a processing unit and a memory unit; receiving a user's audiogram, in which the user inputs the audiogram into the assessment system through the user interface, and the assessment system obtains hearing measurements for the left and right ears based on the audiogram; performing a fit assessment, in which the processing unit in the assessment system obtains a hearing aid / hearing-aid suitability analysis table from the memory unit, and then compares the hearing measurements for the left and right ears with the hearing aid / hearing-aid suitability analysis table to obtain a fit assessment result, including whether the user is suitable for a hearing aid, a hearing aid, or both a hearing aid and a hearing aid; and recommending available hearing device types, in which the processing unit obtains a hearing device type classification from the memory unit and recommends at least one hearing device type based on the fit assessment result.

[0010] To achieve the above-mentioned purpose, a user performance prediction is further performed by having a processing unit retrieve a fit range table from a memory unit, and comparing the left and right hearing scores with the fit range table to obtain a hearing score status code. Subsequently, the hearing score status code is compared with a hearing score code classification table to obtain a classification code that matches the hearing score status code. This code is then compared with a model classification table to eliminate at least one model that does not match the hearing score. Based on the recommended available hearing device types and after eliminating models that do not match the hearing score, the processing unit recommends at least one hearing device type to the user.

[0011] According to the above purpose, further evaluation of the impact on life index is carried out, which is that the processing unit obtains the quantitative impact on life index table from the memory unit, and gives the user corresponding suggestions based on the score range of the quantitative impact on life index evaluation result table.

[0012] According to the above purpose, the neurodegeneration risk assessment is further performed by obtaining an example table of neurodegeneration risk assessment indexes from the processing unit to the memory unit, and providing the user with a recommendation for selecting a hearing device based on the assessment results of the example table of neurodegeneration risk assessment indexes.

[0013] According to the above purpose, when comparing the hearing strength of the left ear and the right ear with the fitting range table, the ear with the better hearing strength is selected for comparison.

[0014] According to the above purpose, when performing user performance prediction, a personal technology ability assessment is further performed, whereby the processing unit obtains a personal technology ability question table from the memory unit, and gives the user a recommendation for selecting a hearing device based on the evaluation results of the personal technology ability question table.

[0015] The present invention further discloses a digital assessment method for selecting a suitable hearing device, which includes: completing a login, in which a user logs into an assessment system through a user interface, the assessment system including a processing unit and a memory unit; performing a numerical scoring of the hearing history, in which the processing unit in the assessment system retrieves hearing history questions from the memory unit, and then the processing unit conducts a question-and-answer session with the user about the hearing history; receiving a user's audiogram, in which the user inputs the audiogram into the assessment system through the user interface, and the assessment system obtains the hearing of the left and right ears based on the input audiogram. degree; the fit assessment is performed by the processing unit in the assessment system retrieving the hearing aid / hearing aid applicability analysis table from the memory unit, and then the processing unit compares the hearing strength of the left ear and the right ear with the hearing aid / hearing aid applicability analysis table to obtain the fit assessment results, including: whether the user is suitable for a hearing aid or a hearing aid, or both a hearing aid and a hearing aid; and the recommended optional hearing device type is recommended by the processing unit according to the fit assessment results and the answers to the hearing history questions after the hearing device type classification is retrieved from the memory unit. At least one hearing device type is recommended.

[0016] To further eliminate models that do not match the hearing level, the processing unit retrieves a fit range table from the memory unit, compares the left and right hearing levels with the fit range table, and obtains a hearing level status code. The hearing level status code is then compared with a hearing level code classification table to obtain a classification code that matches the hearing level status code. The code is then compared with a model classification table to eliminate at least one model that does not match the hearing level. Furthermore, based on the recommended available hearing device types and after eliminating models that do not match the hearing level, the processing unit recommends at least one hearing device type and at least one model to the user.

[0017] According to the above purpose, when the processing unit detects a restricted question from the questions and answers about the hearing history, the processing unit selects whether to continue the assessment based on the user's choice.

[0018] According to the above purpose, in the user performance prediction, the impact on life index is further evaluated, that is, the processing unit obtains the quantitative impact on life index table from the memory unit, and gives the user corresponding suggestions based on the score range of the quantitative impact on life index evaluation result table.

[0019] According to the above purpose, when performing user performance prediction, a personal technology ability assessment is further performed, whereby the processing unit obtains a personal technology ability question table from the memory unit, and gives the user a recommendation for selecting a hearing device based on the evaluation results of the personal technology ability question table.

[0020] According to the above purpose, a neurodegeneration risk assessment is further performed in the user performance prediction, whereby the processing unit obtains an example table of neurodegeneration risk assessment indexes from the memory unit, and provides the user with a recommendation for selecting a hearing device based on the assessment results of the example table of neurodegeneration risk assessment indexes.

[0021] According to the above purpose, when comparing the hearing strength of the left ear and the right ear with the fitting range table, the ear with the better hearing strength is selected for comparison.

[0022] The present invention further discloses a digital assessment method for selecting a suitable hearing device, which is characterized by comprising: completing a login, in which a user logs into an assessment system through a user interface, the assessment system including a processing unit and a memory unit; performing a numerical scoring of the hearing history, in which the processing unit in the assessment system retrieves hearing history questions from the memory unit, and then the processing unit conducts a question-and-answer session with the user about the hearing history; receiving a user's audiogram, in which the user inputs the audiogram into the assessment system through the user interface, and the assessment system obtains hearing scores for the left and right ears based on the input audiogram; performing a fit assessment, in which the processing unit in the assessment system retrieves hearing aid / hearing aid fit from the memory unit. After using the analysis table, the processing unit compares the hearing strength of the left and right ears with the hearing aid / hearing assistive device applicability analysis table to obtain the fit assessment results, including: whether the user is suitable for a hearing aid or a hearing assistive device, or both a hearing aid and a hearing assistive device; recommending the types of hearing devices that can be selected, which is done by the processing unit retrieving the hearing device type classification from the memory unit, and recommending at least one hearing device type based on the fit assessment results and the answers to the hearing history questions; and recommending suitable hearing assistive device accessories and product specifications and features, which is done by the processing unit guiding the user to view the pros and cons of the appearance of the hearing device, giving points based on the user's choice, and providing recommendations for the most suitable product type based on the points.

[0023] To achieve the above-mentioned purpose, a user performance prediction is further performed by having a processing unit retrieve a fit range table from a memory unit, compare the left and right hearing scores with the fit range table, and obtain a hearing score status code. Subsequently, the hearing score status code is compared with a hearing score code classification table to obtain a classification code that matches the hearing score status code. The code is then compared with a design classification table to eliminate at least one design that does not match the hearing score. Based on the recommended available hearing device types and after eliminating designs that do not match the hearing score, the processing unit recommends at least one hearing device type to the user.

[0024] According to the above purpose, when the processing unit detects a restricted question from the questions and answers about the hearing history, the processing unit selects whether to continue the assessment based on the user's choice.

[0025] According to the above purpose, when performing user performance prediction, a personal technology ability assessment is further performed, whereby the processing unit obtains a personal technology ability question table from the memory unit, and gives the user a recommendation for selecting a hearing device based on the evaluation results of the personal technology ability question table.

[0026] According to the above purpose, guiding the user to view the advantages and disadvantages of the appearance of the hearing device includes: viewing the physical button descriptions and ratings of the hearing device.

[0027] In accordance with the above objectives, the description of the advantages and disadvantages of the appearance of the hearing device guiding the user includes: a description and scoring of the correlation between wearing time and nerve stimulation.

[0028] According to the above purpose, guiding the user to view the advantages and disadvantages of the appearance of the hearing device includes viewing the hidden advantages and disadvantages description and rating.

[0029] According to the above purpose, in the user performance prediction, the impact on life index is further evaluated, that is, the processing unit obtains the quantitative impact on life index table from the memory unit, and gives the user corresponding suggestions based on the score range of the quantitative impact on life index evaluation result table.

[0030] According to the above purpose, a neurodegeneration risk assessment is further performed in the user performance prediction, whereby the processing unit obtains an example table of neurodegeneration risk assessment indexes from the memory unit, and provides the user with a recommendation for selecting a hearing device based on the assessment results of the example table of neurodegeneration risk assessment indexes.

[0031] According to the above purpose, when comparing the hearing strength of the left ear and the right ear with the fitting range table, the ear with the better hearing strength is selected for comparison.

[0032] The present invention further discloses a digital assessment system for selecting a suitable hearing device. The assessment system includes a processing unit and a memory unit. The assessment system assists a user in selecting a hearing device through the following procedures: completing login, in which the user logs into the assessment system through a user interface; performing a numerical hearing history scoring, in which the processing unit in the assessment system retrieves hearing history questions from the memory unit and then asks the user questions about the hearing history; and recommending available hearing device types, in which the processing unit retrieves hearing device type classifications from the memory unit, scores and ranks the answers to the hearing history questions, and recommends at least one hearing device type based on the cumulative scores.

[0033] The present invention further discloses a digital hearing device selection system. The system comprises a processing unit and a memory unit. The system assists a user in selecting a hearing device through the following procedures: completing a login, in which the user logs into the system through a user interface; receiving a user's audiogram, in which the user inputs the audiogram into the system through the user interface, and the system obtains hearing measurements for the left and right ears based on the input audiogram; performing a fit assessment, in which the processing unit in the system obtains a hearing aid / hearing-aid suitability analysis table from the memory unit. The processing unit compares the hearing measurements for the left and right ears with the hearing aid / hearing-aid suitability analysis table to obtain a fit assessment result, including whether the user is suitable for a hearing aid, a hearing aid, or both a hearing aid and a hearing aid; and recommending available hearing device types, in which the processing unit retrieves a hearing device type classification from the memory unit and recommends at least one hearing device type based on the fit assessment result.

[0034] The present invention further discloses a digital assessment system for selecting a suitable hearing device. The assessment system includes a processing unit and a memory unit. The assessment system assists a user in selecting a hearing device through the following procedures: completing a login, in which the user logs into the assessment system through a user interface. The assessment system includes a processing unit and a memory unit; performing a numerical hearing history scoring, in which the processing unit in the assessment system retrieves hearing history questions from the memory unit and then conducts a question-and-answer session with the user about the hearing history; and receiving a user's audiogram, in which the user inputs the audiogram into the assessment system through the user interface. The evaluation system obtains the hearing strength of the left and right ears based on the input audiogram; the fit evaluation is performed by the processing unit in the evaluation system retrieving the hearing aid / hearing instrument applicability analysis table from the memory unit, and then the processing unit compares the hearing strength of the left and right ears with the hearing aid / hearing instrument applicability analysis table to obtain the fit evaluation results, including: whether the user is suitable for a hearing aid or a hearing instrument, or both a hearing aid and a hearing instrument; and the recommended optional hearing device type is performed by the processing unit retrieving the hearing device type classification from the memory unit, and then recommending at least one hearing device type based on the fit evaluation results and the answers to the hearing history questions.

[0035] The present invention further discloses a digital assessment system for selecting a suitable hearing device, characterized in that the assessment system includes a processing unit and a memory unit, wherein the assessment system assists the user in selecting a hearing device through the following procedures, the procedures including: completing login, that is, the user completes the login to the assessment system through the user interface; performing numerical scoring of hearing history, that is, the processing unit in the assessment system retrieves hearing history questions from the memory unit, and then the processing unit conducts questions and answers on the hearing history with the user; receiving the user's audiogram, that is, the user inputs the audiogram into the assessment system through the user interface, and the assessment system obtains the hearing power scores of the left ear and the right ear based on the input audiogram; performing fit assessment, that is, the processing unit in the assessment system retrieves the hearing aid / hearing aid applicability analysis table from the memory unit, and the processing unit compares the hearing power scores of the left ear and the right ear with the hearing aid / hearing aid applicability analysis table to obtain the fit assessment results, including: whether the user is suitable for a hearing aid or a hearing aid, or both a hearing aid and a hearing aid; recommending suitable hearing aids. The processing unit retrieves the hearing device type classification from the memory unit and recommends at least one hearing device type based on the fit assessment results and the answers to the hearing history questions. The processing unit recommends suitable hearing assistive device accessories and product specifications and features by guiding the user to view the advantages and disadvantages of the hearing device appearance, assigning points based on the user's selection, and providing the most suitable product type recommendation based on the points. User effectiveness prediction is performed by the processing unit retrieving the fit range table from the memory unit and comparing the hearing scores of the left and right ears with the fit range table to obtain a hearing score status code. Subsequently, the hearing score status code is compared with the hearing score code classification table to obtain a classification code that matches the hearing score status code. The code is then compared with the appearance style classification table to exclude at least one appearance that does not match the hearing score. In particular, based on the recommended optional hearing device types and after excluding the appearance that does not match the hearing score, the processing unit recommends at least one hearing device type to the user. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] FIG1 is a schematic diagram of the evaluation system architecture of the present invention.

[0037] FIG2 is a schematic diagram of an evaluation system of the present invention.

[0038] FIG3 is a schematic diagram of nine types of product shapes according to the present invention.

[0039] FIG. 4 illustrates a digital evaluation method for selecting a suitable hearing device according to an embodiment of the present invention.

[0040] FIG. 5 shows a digital evaluation method for selecting a suitable hearing device according to another embodiment of the present invention. DETAILED DESCRIPTION

[0041] First of all, it should be noted that the hearing device referred to in the following embodiments of the present invention is an audio device that can help people with hearing difficulties hear more clearly, including the following types: hearing aids, personal sound amplifiers or other wearable sound devices (hearables). Hearing devices are further defined as two categories: 1. (traditional) hearing aids and 2. personal sound amplifiers (hereinafter referred to as hearing aids). The main difference between the two is that hearing aids can be set up by the user himself, and usually there is no evaluation or support from a trained hearing expert (such as an audiologist or hearing aid dispenser). Hearing aids that meet the above definition may also include self-prescribed hearing aids, over-the-counter (OTC) hearing aids or other terms that are suitable for the above definitions in each country.

[0042] Next, please refer to Figure 1, which is a schematic diagram of the assessment system architecture of the present invention. The assessment system 200 includes a processing unit 101 connected to a memory unit 102. The assessment system 200 can be implemented in the cloud. The memory unit 102 already stores a database 210 for the digital assessment method executed by the assessment system 200. According to an embodiment of the present invention, the user interface 110 can be a portable intelligent communication device, such as a smartphone, a laptop, or a tablet (iPad). It can also be a terminal processing device, such as a desktop computer, a workstation with computing capabilities, or an edge computing system. The workstation or edge computing system can be located at the user's residence, a store, or a business, without limitation. Furthermore, the user interface 110 can download an operator-provided application (App) from the cloud or open a website via a network system. The user interface 110 can then communicate with the hearing device 120 and the cloud via the App or website's user interface. The user interface 110 can exchange information with the hearing device 120 via communication protocols such as Bluetooth or Wi-Fi.

[0043] The purpose of the digital evaluation method provided by the present invention is to convert professional problems into problems that are easy for users to understand, for example: according to the user's personal hearing information, lifestyle, level of technological operation and other issues, the relevant parameters are obtained in a question-and-answer manner through the evaluation system. Then, the processing unit 101 uses an algorithm to perform calculations (for example: using a weight distribution method) to obtain a comprehensive score. Finally, the user's degree of adaptation to the hearing aid and hearing aid is predicted based on the comprehensive score, usually expressed in stars or scores. In addition, the digital evaluation method of the present invention further provides some explanations of health education concepts to allow users to understand that the benefit predictions and explanations of the hearing aid or hearing aid obtained based on their personal hearing scores allow users to evaluate whether they can purchase hearing aids through the cloud, online or any digital system, or whether they need the physical assistance of hearing aid experts to purchase hearing aids, with full knowledge and consent. In addition, the memory unit 102 also stores actual evaluation results of various hearing devices, including analytical data such as appearance, function, and price (e.g., Table 1, Table 3, Table 4, Table 5, Table 6, Table 7, Table 9, Table 10, Table 11, Table 12, Table 13, Table 14, Table 15, Table 16, Table 17, Table 18, Table 19, and Table 20 described below) for reference in evaluating the fitting results.

[0044] Next, please refer to Figure 2, a schematic diagram of the evaluation system of the present invention. In the figure, a question database 210 for the digital evaluation method has been established in the evaluation system 200, and concise and easy-to-understand professional questions have been designed, as shown in 2500. Through the database 210 and the professional question design, the evaluation system 200 allows users to fully understand and agree to the recommended hearing device and then self-evaluate whether they can purchase it online or require the physical assistance of a hearing aid expert. The first question database of the digital evaluation method includes: questions presented in a theoretical or information-organized manner (as shown in 2100), which are divided into an explanation of the level of naked ear hearing condition (as shown in 2110), an explanation of the difference between expert assistance and self-adjustment (as shown in 2130), and an explanation of health education concept 1 (as shown in 2150).

[0045] First, in the naked ear hearing condition level description (shown as 2110), the naked ear hearing condition description is provided by the assessment system 200 through an online audiogram explanation, allowing users to understand how to interpret the audiogram and the distribution range of daily speech. For example, the assessment system 200 presents each user's naked ear hearing condition as a relative score value that is more easily understood by the general public, as shown in the naked ear hearing condition level table in Table 1 below.

[0046] Table 1

[0047] Next, the assessment system 200 interactively interprets the audiogram based on the user's current hearing condition. After explaining the level of naked-ear hearing, the user can understand the reasons for their inability to hear sounds and speech. For example, a hearing score of 100 indicates normal hearing, meaning the hearing in either the left or right ear is within the normal range. A hearing score of 75-99 in one ear indicates mild hearing loss, requiring increased concentration to understand conversations in noisy environments. A hearing score of 40-59 or above indicates moderate to severe hearing loss, making it difficult to have regular conversations and requiring the other person to raise their voice or get closer to understand. A hearing score of 20-39 or above indicates severe hearing loss, meaning the user can barely hear the other person's speech and requires them to shout or get very close to understand. Finally, a coordinate graph representing volume and frequency, as well as image and speech ranges, can be used to display the ranges of hearing loss in the user's left or right ear.

[0048] To further illustrate, the assessment system 200, based on an audiogram report from a user (referred to as Xiao Ming), shows that the hearing scores for the right ear from 250 Hz to 8 kHz are 40 dB, 40 dB, 50 dB, 50 dB, 60 dB, and 60 dB, respectively. The hearing scores for the left ear from 250 Hz to 8 kHz are 75 dB, 75 dB, 90 dB, 90 dB, 105 dB, and 105 dB, respectively, as shown in the example hearing scores in Table 2 below.

[0049] Table 2

[0050] As shown in Table 2, Xiao Ming's right ear's hearing in the low and mid-frequency range is "mild hearing loss," while its high-frequency hearing is "moderate to severe hearing loss." Xiao Ming's left ear's hearing in the low and mid-frequency range is "severe hearing loss," while its high-frequency hearing is "moderate to severe hearing loss." Therefore, based on the unaided ear hearing analysis, Xiao Ming's right ear is classified as "mild to moderately severe hearing loss," while his left ear is "severe to profound hearing loss." Clearly, Xiao Ming requires hearing devices to improve both right and left ears. Secondly, regarding the differences between expert assistance and self-adjustment (as shown in 2130), the present invention provides users with essential professional information, allowing them to understand the differences between hearing aids and new hearing aids, as well as professional aspects such as suitability in terms of hearing strength. Therefore, the present invention uses a different service approach from traditional methods to help users assess which hearing device is best for them. For example: Traditional services refer to services that require the assistance of real experts to evaluate the suitability of hearing devices for users, while the present invention is a new type of service that does not require real experts. It can also provide more extensive product comparison information than real experts, especially new types of hearing aids. In order to achieve the above purpose, the evaluation system 200 of the present invention will be inserted with videos, texts, and diagrams to allow users to understand the advantages and disadvantages of hearing aids and hearing aids, as well as the problems and limitations that may be faced in care such as subsequent adjustments without the assistance of experts. Allow users to obtain complete and comprehensive information to determine whether they can purchase hearing aids online.

[0051] Next, the evaluation system 200 explains health education concept 1 (shown as 2150). This is presented by the evaluation system 200 during the evaluation process using videos, text, and diagrams to facilitate user understanding. For example, these concepts include the importance of wearing duration and continuous wear, the benefits of sound stimulation of the brain, and other propositions and correct knowledge. This helps establish the user's correct understanding and internalize the necessary knowledge and skills for hearing device use. Furthermore, the evaluation system 200 can also use videos during the evaluation process to illustrate some of the challenges of hearing device use, such as the concept of progressive prescription gain and the auditory journey experienced after purchase. This helps establish the user's correct understanding and promote the user's success rate, compliance, and motivation for continued hearing device use.

[0052] Next, the second question database established by the digital evaluation method includes: the evaluation system 200 divides the hearing aid and hearing aid benefit prediction and description into hearing aids (as shown in 2210), neurodegeneration risk assessment (as shown in 2230), and exclusion of inappropriate appearance styles (as shown in 2250) based on the hearing strength score and the weight calculation of professional questions (as shown in 2200).

[0053] First, the hearing aid and hearing aid effectiveness prediction and description (as shown in 2210) are classified by the evaluation system 200 according to the user's hearing strength, and further compared with the average commercially available hearing aid and the measured fitting range of commercially available hearing aids to predict the user's personal effectiveness and explain the reasons why the hearing strength is not suitable, as shown in Table 3 below, an example of a hearing aid / hearing aid applicability analysis table.

[0054] Table 3

[0055] It's important to note that when determining the final compatibility result in Table 3, a comprehensive assessment of both ears is required. For example, if the "Compatibility Type" results for the left and right ears differ, the "Hearing Aid Only" result will prevail. For example, if the left ear is classified as H (Hearing Aid Compatible) and the right ear is classified as P (Both Compatible), the final result will be "Hearing Aid Compatible."

[0056] Taking the hearing test scores in Table 2 as an example for further explanation, when the assessment system 200 reports the hearing test scores of a user (referred to as Xiao Ming) from 250 Hz to 8 kHz based on an audiogram report, the hearing test scores of the right ear are 40 dB, 40 dB, 50 dB, 50 dB, 60 dB, and 60 dB, respectively, and the hearing test scores of the left ear are 75 dB, 75 dB, 90 dB, 90 dB, 105 dB, and 105 dB, respectively, from 250 Hz to 8 kHz.

[0057] According to the results of the hearing strength example in Table 2, it is obvious that Xiao Mingzhi does not know whether his current hearing condition is suitable for a hearing aid or a hearing aid. Then, the evaluation system 200 of the present invention can refer to the hearing strength in Table 2 and Table 3 according to the classification logic of the hearing aid and hearing aid benefit prediction and description in 2210, and it can be obtained that the right ear meets category C and category H, and the left ear meets category H. According to the results of the cross-reference between Table 2 and Table 3, it can be obtained that category C and category H of the right ear are both "suitable for hearing aids", and category A of the left ear is also "suitable for hearing aids". As mentioned above, if the "suitable category" results of the two ears are different, the final applicable result of the evaluation system 200 of the present invention must be comprehensively judged by the two ears, and the result of "suitable for hearing aids" is mainly based on the result. Therefore, the evaluation system 200 will recommend Xiao Ming to use "hearing aids" as the main method. Obviously, the evaluation system 200 of the present invention obtains an objective judgment basis for the hearing scores of hearing aids and hearing aids based on Xiao Ming's actual hearing scores, so as to help Xiao Ming understand his suitable hearing device and further assist him in making a purchasing decision.

[0058] Secondly, a neurodegeneration risk assessment (as shown in 2230) is performed. This refers to the fact that when a user's hearing loss leads to reduced sound input, it may cause neurons and related brain regions to become inactive or degenerate, negatively impacting the individual's nervous system. For example, in the neurodegeneration risk assessment (as shown in 2230), the assessment system 200 uses the standards shown in Table 1, such as mild hearing loss at 40dBHL, which indicates a sharp decrease in most daily ambient sounds, and severe hearing loss at 60dBHL, which indicates significant disturbance at the volume of typical conversations. The system then accumulates scores based on the user's hearing strength. Please refer to Table 4 for an example neurodegeneration risk assessment index to determine the neurodegeneration risk assessment index.

[0059] Table 4

[0060] Based on Xiao Ming's hearing condition in Table 2 and the assessment index in Table 4, we obtain an assessment index of 8 for his right ear and 12 for his left ear. Clearly, Xiao Ming's left ear is at extremely high risk for neurodegeneration, and he must use a hearing aid.

[0061] Finally, an evaluation is performed to exclude inappropriate models (as shown in 2250). The evaluation system 200 further eliminates models that do not meet the user's hearing requirements based on the user's hearing strength and the measured fitting range of average commercially available hearing devices, thereby selecting hearing device models that are suitable for the user's hearing strength. The measured fitting range of average commercially available hearing devices, as shown in Table 5, is a table of the present invention that comprehensively defines the hearing strength applicability of different frequencies after actual acoustic and electrical analysis testing of commercially available hearing aids. The data includes low frequency, mid-frequency, mid-high frequency, and high frequency. TVOX is the hearing strength status code: T represents a sense of stuffiness, V represents the optimal fitting range, O represents a tight range, and X represents exceeding the fitting range.

[0062] Table 5

[0063] Next, based on the user's hearing ability, we eliminate hearing device models that don't match the hearing scale. First, we need to redefine the user's hearing scale code. See Table 6 for a detailed classification of hearing scale codes. We first need to compare the user's hearing scale (for example, obtaining the hearing scores for the user's left and right ears at different frequencies) with the fit of average commercially available hearing devices across the high, medium, and low frequency ranges listed in Table 5. This is used to obtain the hearing scale status code (OXVT) in Table 5. The comparison of the hearing scale status codes in Table 6 is performed item by item, and once a matching condition is found, no further comparison is performed.

[0064] Table 6

[0065] After finding the classification conditions that match the user's hearing level status code in Table 6, the classification conditions that match the hearing level status code are then compared with those in Table 7 to eliminate hearing device models that are inappropriate for the user's hearing level. Table 7 represents a classification table for eliminating models that do not match the user's hearing level. An example of the nine model categories in Table 7 is shown in FIG3 .

[0066] Table 7

[0067] It should be noted that if the hearing test scores for the two ears differ, the hearing device designs that need to be excluded may also differ. Therefore, to maximize the potential for use, a preferred embodiment of the present invention uses the hearing test scores of the superior ear as the primary mechanism for eliminating unsuitable hearing device designs. For example, the average of 500 (low frequency), 1K (mid-frequency), 2K (mid-high frequency), and 4K (high frequency) is used as the basis for comparison of the hearing test scores of the superior ear.

[0068] It should be further explained that the above Table 3 (Analysis of Hearing Assistance / Hearing Aid Suitability), Table 4 (Example of Neurodegeneration Risk Assessment Index), Table 5 (Average Fit Range of Commercially Available Hearing Devices), Table 6 (Classification of Hearing Scale Codes), and Table 7 (Classification of Models and Styles Excluding Those Not Matching Hearing Scales) are all examples related to the fit of hearing devices of the present invention and are therefore stored in the fit database of the memory unit 102.

[0069] For another example, if the processing unit 101 of the assessment system 200 shows, based on Xiao Ming's audiogram report, that Xiao Ming's right ear hearing scores from 250 Hz to 8 kHz are 30 dB, 30 dB, 40 dB, 40 dB, 50 dB, and 50 dB, and Xiao Ming's left ear hearing scores from 250 Hz to 8 kHz are 45 dB, 45 dB, 60 dB, 60 dB, 70 dB, and 70 dB, respectively, as shown in the example hearing scores in Table 8 below, in this embodiment, the average of the hearing scores at 250 Hz and 500 Hz in Table 8 is used as the low-frequency hearing score, the average of the hearing scores at 1 kHz and 2 kHz is used as the mid-frequency hearing score, the average of the hearing scores at 4 kHz is used as the mid-high-frequency hearing score, and the average of the hearing scores at 8 kHz is used as the high-frequency hearing score.

[0070] Table 8

[0071] Furthermore, in another preferred embodiment of the present invention, the average hearing score of the "better ear" can be selected as the primary mechanism for eliminating unsuitable hearing device designs. Therefore, according to Table 8, this embodiment selects the right ear (i.e., the better ear) as the primary basis for exclusion. Next, the processing unit 101 of the evaluation system 200 of the present invention can, based on the evaluation logic for eliminating unsuitable designs (2250), compare the hearing scores in Table 8 with those in Table 5 in real time. For example, the hearing score status code for the right ear can be determined to be TVOX. Using the classification table for eliminating unsuitable hearing scores in Table 6, it is determined that the right ear meets the classification condition of π (the hearing aid is acceptable, but the high frequencies are poor). Then, π is compared with Table 7, resulting in the elimination of the "true wireless" hearing device design. This means that all eight designs in Figure 3 are suitable for Xiao Ming. It is particularly important to note that a key benefit of the present invention is that it assists users in professionally eliminating unsuitable designs, rather than blindly choosing based solely on appearance preferences. This effectively reduces the risk of users purchasing unsuitable hearing devices.

[0072] Finally, the user will be provided with further introductions to the appearance. For example, after clicking on a specific appearance style, the user will be linked to a video or description of the appearance introduction for further selection.

[0073] Next, the third question database established by the digital assessment method includes professional information (shown as 2300) obtained by the processing unit 101 of the assessment system 200 based on the user's customized answers. For example, the user's personal hearing score can be mapped on the audiogram, and the shaded area can be used to provide the user with an understanding of their current hearing condition. This database is divided into indicators that affect life (shown as 2310), an assessment of personal technological capabilities (shown as 2330), suitable hearing aid accessories and product specifications (shown as 2350), filtering out users with a history of hearing limitations (shown as 2370), and recommending three most suitable hearing device models (shown as 2390).

[0074] First, the evaluation system 200 of the present invention categorizes various commercially available hearing devices based on whether they have an app, battery capacity, or appearance. For example, different hearing aid models on the market are categorized into five different types based on whether they have an app or battery capacity, as shown in Table 9 below. For example, different hearing aid models on the market are categorized into six different types based on whether they have an app or battery capacity, as shown in Table 10 below. It should be noted that the appearance of each product type listed in Tables 9 and 10 of the present invention is merely an example. Therefore, the present invention does not limit the actual appearance classifications available on the market.

[0075] Table 9

[0076] Table 10

[0077] In a preferred embodiment of the present invention, the evaluation system 200 calculates the data and provides a default recommended order for the 11 hearing device categories listed in Tables 9 and 10. Please refer to Table 11 below. In the event of a tie in the total scores of each item answered by a user, the default recommended order in Table 11 can be used to reorder the categories.

[0078] Table 11

[0079] Next, the quantified impact on life index (shown as 2310) is generated by the assessment system 200 by summarizing interpersonal, social, psychological, communication, and speech issues caused by hearing loss, as shown in Table 12. The processing unit 101 of the assessment system 200 then evaluates the user's lifestyle based on the questions in Table 18 and assigns a score based on the user's responses. For example, by having the user answer the questions shown in Table 12, the assessment system 200 can help the user reflect on the various limitations and negative impacts of hearing loss, thereby raising awareness and promoting motivation to wear hearing devices.

[0080] Table 12

[0081] As shown in Table 12, the present invention provides five questions with a total of 16 answer options, including 5 or more "no" answers. Processing unit 101 allows the online user to answer each question, then, after selecting a checkbox and deducting the "no" answer, accumulates scores based on the answers to create a quantified life impact index, as shown in Table 13. Processing unit 101 then provides appropriate recommendations based on the score ranges and corresponding impact levels in Table 13, and further promotes relevant courses or film information based on the question. The calculation table for the quantified life impact index is shown in Table 13.

[0082] Table 13

[0083] Based on the results in Table 13, the evaluation system 200 will give different suggestions. For example, when the evaluation system 200 evaluates the user's answer to question 5, if it is judged that the hearing problem is mild or above according to Table 13, the evaluation system 200 will recommend that the user actively deal with it.

[0084] Next, the personal technological ability is assessed (as shown in step 2330). The processing unit 101 of the evaluation system 200 evaluates the user's technological ability by having them answer questions about their personal technological ability and assigns a score based on the user's answers. The personal technological ability assessment method includes: The evaluation system 200 scores the user's ability to use or operate 3C products based on their answers. The personal technological ability questions of the present invention are shown in Table 14 below.

[0085] Table 14

[0086] For example, if a user answers "I don't know how to download apps," the evaluation system 200 will assign a score based on their answer, such as 0.5. For another example, if the user further answers "I don't know how to connect to a phone using Bluetooth," the evaluation system 200 will assign a score based on their answer, such as 0.5. For another example, if the question is "Do you think you can wear it?" and the user answers "No," the evaluation system 200 will assign a score based on their answer, such as 0.5. Alternatively, if the question is "Can you learn to use it on your own through online videos or text tutorials?" and the user answers "No," the evaluation system 200 will assign a score based on their answer, such as 0.5. Finally, based on the interactive questions and scores in Table 14, the evaluation system 200 will generate an assessment result for "Personal Technological Ability," such as a score between 0.5 and 2. Furthermore, in this embodiment, the evaluation system 200 also asks the user whether they have a specific product appearance preference, inviting the user to select at least one product with a preferred appearance. For example, if a user has purchased a hearing device in the evaluation system 200, they can directly select their preferred product appearance based on their usage experience. In an embodiment of the present invention, the user can select three preferred product types.

[0087] Next, the evaluation system 200 recommends suitable assistive listening device accessories and product specifications and features (as shown in 2350). This is based on the accessories of the assistive listening device, including physical buttons, phone transfer accessories, or remote microphone accessories, and other product specifications and features that can cooperate with hearing aid technology products. Therefore, the purpose of establishing and introducing suitable assistive listening device accessories and product specifications and features in the present invention is to establish the concept of an auditory ecosystem, so that users understand that hearing health and ability do not rely solely on personal hearing devices, and other assistive listening devices are also part of the solution. Among them, the evaluation method for recommending suitable assistive listening device accessories and product specifications and features includes:

[0088] 1. Instruct the user to watch a video explaining the pros and cons of physical buttons (e.g., the presence or absence of buttons, buttons on the back, etc.) or the presence or absence of app operation in a hearing device. The evaluation system 200 then conducts a Q&A session with the user and, based on the user's confirmation of the ease of use of the physical buttons, app operation, or button size, assigns a score. An example of a scoring table for describing the pros and cons of physical buttons or the presence or absence of app operation is shown in Table 15 below. For example, if the question is "Would you prefer physical buttons?" and the user answers "physical buttons," the evaluation system 200 will assign a score based on the answer, e.g., 1 point. Alternatively, if the question is "Would you prefer a hidden hearing aid design, or one that's invisible?" and the user answers "like earphones," "invisible," or "both," the evaluation system 200 will assign a score based on the answer, e.g., 1 point.

[0089] Table 15

[0090] 2. Guide the user to watch a video explaining the correlation between wearing time and nerve stimulation, demonstrating the pros and cons. For example, the video explains which hearing device design should be chosen to allow the user to wear the device longer, thereby stimulating the auditory nerve for longer periods of time and achieving rehabilitation or maintenance benefits. The evaluation system 200 then conducts a Q&A session with the user and assigns a score based on the user's estimated daily usage hours. For example, 4 hours of daily use will be assigned a 0.5 point, while over 8 hours will be assigned a 1 point. A sample daily usage scoring table is shown in Table 16 below.

[0091] Table 16

[0092] 3. Guide the user to watch a video explaining the advantages and disadvantages of concealed hearing devices. Afterwards, the evaluation system 200 will conduct a Q&A session with the user and assign a score based on the user's answer to the appearance preference. For example, when the question is "Would you prefer a concealed style, or one that is not visible as a hearing aid?", and the user answers "like earphones" or "invisible" or "both", the evaluation system 200 will assign a score based on the answer, for example, 1 point. Finally, based on the interactive questions and scores in Table 17, the evaluation system 200 will obtain an evaluation result, for example, 2 points. In particular, Table 17 includes an evaluation of hearing aids, and the evaluation results of hearing aids can range from 0 to 2 points.

[0093] Table 17

[0094] Based on the evaluation results in Tables 15-17, evaluation system 200 can recommend whether a user is suitable for using a hearing aid, a hearing aid, or both, based on their individual technological capabilities. When evaluating Tables 15-17, evaluation system 200 can be used in conjunction with the product classification tables in Tables 9 and 10. A detailed evaluation method will be provided later.

[0095] Next, users whose hearing history has limitations are filtered out (as shown in 2370). This is because the assessment system 200 initially analyzes whether users have risk factors for using self-adjusting hearing devices through professional questions about their hearing history. The hearing-related medical history questions are shown in Table 18 below.

[0096] The processing unit 101 of the assessment system 200 calculates the cumulative score based on Table 18 by inquiring about the user's hearing history. The processing unit 101 then determines which hearing device type is suitable for the user based on the scores obtained from the user's answers to the medical history questions. Clearly, by further incorporating risk factors into the assessment system 200 of the present invention as limiting factors, the user can independently determine whether they have limitations that make them unsuitable for self-adjusting hearing devices. Consequently, the assessment system 200 of the present invention can provide timely reminders, allowing the user to make a comprehensive assessment and make an informed decision.

[0097] Table 18

[0098] As shown in Table 18, in an embodiment of the present invention, when the processing unit 101 of the evaluation system 200 determines whether the user's hearing history has limitations, especially when the user answers the question in Table 18 as "microtia, no ear canal, deformed or abnormal structure after surgery", the evaluation system 200 will ask the user whether to continue the evaluation. This is because users with "microtia" may not be able to support hearing aids because their ear shells are too small. Therefore, the evaluation system 200 will assist in the evaluation, for example, explaining the causes and limitations of "microtia" to the user. Then, when the result of the user evaluation is that the user cannot wear or use the hearing device, the evaluation system 200 will display "End Service". Or when the result of the user evaluation is that the user has microtia but can still use ordinary in-ear headphones, the evaluation system 200 will display "Continue Evaluation".

[0099] In addition, in addition to the forced pop-up of microtia, the evaluation system 200 will further explain this issue with other risk factors, so that the user can understand the possible limitations and problems and decide whether to continue the evaluation according to the user's own wishes, such as: "The ears often have severe water and pus discharge", "Unsure whether the hearing often changes drastically", etc. For example: After the user understands the questions in Table 18 and answers them, the evaluation system 200 will give a score based on the answer. For example, when the user answers that the earwax is wet earwax, the evaluation system 200 will give a score based on the answer, such as: 0.5 points. For another example, if the user further answers that their earwax is often excessive, the evaluation system 200 will give a score based on the answer, such as: 0.25 points. The following Table 19 is an example of Xiao Ming's answers to medical history questions, in which the questions in Table 19 include some of the questions in Tables 14, 15, 16, 17 and 18.

[0100] Table 19

[0101] According to the total scores in Table 19 above, the top three ranking scores are: hearing aid type 2, hearing aid type 6 with the same score (9.25), hearing aid type 1, hearing aid type 3, hearing aid type 4, and hearing aid type 5 with the same score (7.25). In a preferred embodiment of the present invention, when multiple types have the same score, the present invention can further refer to the default recommendation order in Table 11, and the ones with the same score will be ranked higher. Therefore, according to the default recommendation order in Table 11, the types with the same score are given the highest priority for hearing aid type 4, so hearing aid type 4 is the third recommended appearance. Therefore, in this embodiment, Xiao Ming's most recommended three appearances are:

[0102] 1. Hearing aid type 6

[0103] 2. Hearing aid type 2

[0104] 3. Hearing aid type 4

[0105] Next, the fourth question database established by the digital assessment method includes: the assessment system 200 performs system question stimulation (as shown in 2400), and currently evaluates by reviewing the psychological problems in life caused by hearing loss (as shown in 2410), including: the assessment system 200 uses interpersonal, social, psychological, communication, and speech problems caused by hearing loss to allow consumers to review the various limitations and adverse effects caused by their hearing loss, thereby awakening consumers' awareness of the disease and promoting their motivation to wear hearing aid technology.

[0106] The assessment system 200 shown in FIG2 converts the professional questions asked by audiologists during consultations or tests into simple questions that are easy for users to understand through online operations or online interactive Q&A. The system helps users understand their hearing condition, required rehabilitation information and courses, and the effectiveness of hearing aids or hearing aids. The system 200 of the present invention then assigns weighted scores based on the user's answers to the questions. Based on each user's individual weighted scores, the system recommends various types of hearing devices (hearing aids / hearing aids) to the user. Finally, after providing a health education concept (as shown in 2150), the user can, with full knowledge and consent, independently assess whether they are suitable to purchase hearing aids online or require in-person assistance from an audiologist, as shown in 2600. It should be noted that the database contents established in FIG2 are not in any particular order, and the database 210 can be accessed based on the purpose of the assessment system 200. Furthermore, the questions in the database 210 are illustrative and are not intended to limit the scope of the present invention. Furthermore, the content of the question database 210 disclosed in the specification can be supplemented with new questions and content based on the frequency of use to form a large amount of data, which can be used as basic data for artificial intelligence (AI) operations.

[0107] Next, please refer to Figure 4 , which illustrates a digital assessment method for selecting appropriate hearing devices according to the present invention. As shown in Figure 4 , first, as shown in step 3100, each user must create an application (App) for this case on the user interface 110. For example, the user interface 110 can be a smart communication device, a laptop, or a desktop personal computer. The user then completes membership registration in the cloud (or backend) through the App, enabling management of each user's personal information.

[0108] Next, the first embodiment shown in FIG. 4 will be described.

[0109] After a user logs into the system, processing unit 101 accesses the fit database in memory unit 102 and retrieves Table 3 (Hearing Assist / Hearing Aid Suitability Analysis Table), Table 4 (Example Table of Neurodegeneration Risk Assessment Index), Table 5 (Average Fit Range of Commercially Available Hearing Devices), Table 6 (Hearing Scale Code Classification Table), and Table 7 (Appearance Model Classification Table for Excluding Incompatible Hearing Scales). The fit database has been established in FIG. 2 and stored in database 210 in memory unit 102.

[0110] Next, as shown in step 3310, the system requires the user to enter an audiogram. This audiogram can be obtained by the user undergoing a hearing test (e.g., pure-tone audiometry) at a hospital or professional hearing clinic, resulting in left and right ear audiograms, such as those shown in Table 2 or Table 8. In an embodiment of the present invention, the hearing test uses audio clips to measure the user's sensitivity to different frequencies. The frequency range provided includes, for example, 250Hz, 500Hz, 1000Hz, 2000Hz, 4000Hz, and 8000Hz. Tables 2 and 8 show the user's left and right ear hearing at specific frequencies, and the resulting left and right ear hearing scores are based on the unaided hearing scale in Table 1. If the user does not have an audiogram when logging in, they can establish communication with the assessment system via a wireless communication device, and a remote professional will assist the user in performing an online audiogram test, thereby obtaining a personalized left and right ear audiogram, such as those shown in Table 2 or Table 8. Alternatively, users can use other online hearing tests on their own. However, users are warned that without professional assistance and due to differences in user equipment, the results may be less accurate. For example, in an embodiment of the present invention, online hearing tests can also use audio clips to test the user's sensitivity to different frequencies. The frequencies provided include, for example, 250Hz, 500Hz, 1000Hz, 2000Hz, 4000Hz, and 8000Hz.

[0111] Next, the fit assessment process proceeds, as shown in step 3350. In step 3350, the processing unit 101 of the assessment system 200 retrieves the audiogram report from Table 2, which shows that the hearing scores for the right ear from 250Hz-8kHz are 40, 40, 50, 50, 60, and 60, respectively, and the hearing scores for the left ear from 250Hz-8kHz are 75, 75, 90, 90, 105, and 105, respectively. Next, the processing unit 101 of the assessment system 200 retrieves the hearing aid / hearing aid suitability analysis table from the fit database, as shown in Table 3. By cross-referencing the hearing scores in Table 2 with Table 3, it is determined that the right ear meets Category C and Category H, while the left ear also meets Category H. Based on the cross-referencing results of Table 2 and Table 3, it is determined that Category C and Category H for the right ear are both "suitable for a hearing aid," while Category A for the left ear is also "suitable for a hearing aid." As previously mentioned, if the "suitability type" results for the two ears differ, the evaluation system 200 of the present invention makes a comprehensive assessment of both ears, prioritizing the "suitability of hearing aids." Therefore, the evaluation system 200 will primarily recommend Xiao Ming using "hearing aids." Clearly, the evaluation system 200 of the present invention uses Xiao Ming's actual audiogram scores to objectively determine the difference between hearing aids and hearing aids, helping Xiao Ming understand his suitable hearing device and ultimately aiding his purchasing decision.

[0112] After the evaluation system 200 recommends Xiao Ming to primarily use a hearing aid in step 3350, it then proceeds to recommend the types of hearing devices available, as shown in step 3500. First, the processing unit 101 in the evaluation system 200 retrieves a classification of hearing device types from the database 210, as shown in step 3510. For example, Tables 9, 10, and 11 are retrieved. Table 9 lists the features of hearing aids of different shapes, Table 10 lists the features of hearing aids of different shapes, and Table 11 lists the default recommendation order. Clearly, in step 3500, the processing unit 101 in the evaluation system 200 recommends Xiao Ming to primarily use a hearing aid based on the results of cross-referencing Tables 2 and 3. Furthermore, in a preferred embodiment, the present invention can also determine the recommended order of hearing aids based on the default recommendation order in Table 11, for example, recommending hearing aid type 5 first, followed by hearing aid type 4, and finally hearing aid type 3. Obviously, the default recommendation order shown in Table 1 can be a new order generated based on the accumulation of big data and through AI algorithms, and the present invention is not limited to this.

[0113] Next, the assessment system 200 performs a user performance prediction process, as shown in step 3600. The user performance prediction can be achieved through processes such as quantifying the impact on life index in step 3610, assessing the neurodegeneration risk index in step 3620, or eliminating appearance styles that do not match the hearing test score in step 3630.

[0114] In a preferred embodiment of the present invention, the processing unit 101 in the evaluation system 200 retrieves the average measured fitting range of commercially available hearing devices from the database 210, as shown in Table 5. It also retrieves the hearing test score code classification table in Table 6 and the model classification table for excluding models that do not meet the hearing test scores in Table 7, to perform an evaluation to exclude unsuitable models, as shown in step 3630. The implementation is described below:

[0115] If the processing unit 101 of the evaluation system 200 can extract the audiogram report content of Table 2, the hearing strength of the right ear from 250Hz-8kHz is 40dB, 40dB, 50dB, 50dB, 60dB, and 60dB in sequence, and the hearing strength of the left ear from 250Hz-8kHz is 75dB, 75dB, 90dB, 90dB, 105dB, and 105dB in sequence. Next, the evaluation system 200 of the present invention can compare the hearing scores in Table 2 with those in Table 5 in real time, using the evaluation logic for eliminating unsuitable models. The system can then determine that the hearing score status code for the right ear is VVOX and the hearing score status code for the left ear is XXXX. After eliminating the incompatible hearing score categories using Table 6, the processing unit 101 of the evaluation system 200 determines that the right ear meets the category π (i.e., the hearing aid is acceptable, but the high frequencies are poor) and the left ear meets the category β (i.e., a hearing aid is needed, but the power is too strong). The system then compares π and β with Table 7. During the comparison process in Table 7, the present invention can select the hearing score of the better ear as the primary mechanism for eliminating unsuitable hearing device models. Therefore, Xiao Ming uses π to eliminate the "true wireless hearing aid model number 1," indicating that all eight hearing aid models numbered 2 through 9 in FIG. 3 are suitable for Xiao Ming.

[0116] In another example, if Xiao Ming provides an audiogram as shown in Table 8, where Xiao Ming's right ear hearing scores from 250Hz-8kHz are 30, 30, 40, 40, 50, 50, and Xiao Ming's left ear hearing scores from 250Hz-8kHz are 45, 45, 60, 60, 70, 70, respectively, then, based on the evaluation logic for excluding unsuitable models, the assessment system 200 of the present invention can compare the hearing scores in Table 8 with Table 5 in real time, and determine that the hearing score status code for the right ear is TVOX. Then, using the classification table for excluding unsuitable hearing scores in Table 7, it is determined that the right ear meets the classification condition π (the hearing aid is acceptable, but the high frequencies are poor). Then, by comparing π with Table 7, the result is that the "true wireless" hearing device model can be excluded, indicating that all eight models in Figure 3 are suitable for Xiao Ming.

[0117] Secondly, in other embodiments of the present invention, the assessment system 200 can optionally perform a "Quantitative Impact on Life Index Assessment." Processing unit 101 can retrieve the quantitative impact on life index questions from Table 12 from database 210 of memory unit 102, as shown in step 3610. Processing unit 101 then asks the online user to answer each question in Table 12. Based on the results in Table 13, the assessment system 200 will provide different recommendations. For example, if the assessment system 200 assesses the user's answers to five questions and determines, according to Table 13, that the hearing problem is mild or above, the assessment system 200 will recommend that the user proactively address the issue.

[0118] In other embodiments of the present invention, the assessment system 200 can also optionally perform a "neurodegeneration risk assessment" to inform the user of the neurodegeneration risk assessment for both ears, as shown in step 3620. The processing unit 101 in the assessment system 200 retrieves the example neurodegeneration risk assessment index table shown in Table 4 from the database 210. The processing unit 101 then substitutes the hearing strength index table in Table 2 into the calculation logic in Table 4 to obtain assessment scores for both ears. This is used to assess the risk index for the left and right ears, further clarifying the importance of using hearing aid technology. For example, based on Xiao Ming's hearing condition in Table 2 and the calculation of the assessment index in Table 4, the right ear's assessment index is 8, while the left ear's assessment index is 12. Therefore, Xiao Ming's neurodegeneration risk assessment for both ears is above high risk. Therefore, the assessment system 200 recommends that Xiao Ming use hearing aids because his hearing strength is too severe and hearing aids are inadequate. For example, based on Xiao Ming's hearing condition in Table 8 and the evaluation index in Table 4, the right ear's evaluation index is 4, while the left ear's evaluation index is 10. Clearly, Xiao Ming's right ear's neurodegeneration assessment result indicates a low risk, while the left ear's neurodegeneration assessment result indicates a high risk or higher. Based on this, the evaluation system 200 of the present invention, after performing a neurodegeneration risk assessment, can inform the user of the neurodegeneration risk index for both ears, allowing the user to fully understand the importance of using hearing aids.

[0119] Obviously, after completing step 3600 of the first embodiment, the evaluation system 200 gives Xiao Ming the following recommendations (Table 2):

[0120] 1. The order of applicable hearing aid types is: hearing aid type 5, hearing aid type 4 and hearing aid type 3.

[0121] 2. Applicable hearing aid shapes include the eight shapes numbered 2 to 9 in Figure 3.

[0122] Next, based on the "predicted effectiveness of the recommended hearing device design," the user is presented with a video explaining the advantages and disadvantages of the recommended design and viewing it, allowing the user to understand the estimated effectiveness, as shown in step 3700. In step 3700, the processing unit 101 in the evaluation system 200 presents the user with various recommended hearing device designs through a video presentation and explanations of the advantages and disadvantages of each design. For example, the user can activate the video presentation and explanations by pressing the play button on the various hearing device designs shown in FIG3 . The relevant video presentation and explanations are stored in the database 210 in the memory unit 102. Clearly, after step 3700, the user understands the advantages and disadvantages of each design, helping them to determine the product that suits them best.

[0123] Finally, as shown in step 3800, the user self-evaluates whether to purchase a hearing aid online. In step 3800, the evaluation system 200 allows the user to self-evaluate which hearing aid / hearing device to purchase online, or after selecting multiple hearing aid / hearing devices online, select or schedule a date and which physical store to visit. After actually wearing the selected hearing aid / hearing device, the user can decide to purchase the most suitable appearance. Obviously, regardless of whether the user purchases directly online or in a physical store, the present invention can enable the user to self-select a hearing aid / hearing device with full knowledge and consent to the hearing device recommended by the evaluation system 200.

[0124] Next, the second embodiment of FIG. 4 will be described.

[0125] As shown in FIG4 , first, as shown in step 3100, each user needs to create an application (App) for this case on the user interface 110. For example, the user interface 110 can be a smart communication device, a laptop, or a desktop personal computer. The user then completes the membership registration in the cloud (or backend) through the App, which allows for the management of each user's personal information.

[0126] After confirming the user's identity, the system then filters the user's hearing history to determine if there are any restrictions, as shown in step 3330. In step 3330, the processing unit 101 in the assessment system 200 retrieves the hearing-related medical history question table in Table 18 from the database 210 in the memory unit 102. Next, as shown in step 3400, the assessment system 200 allows the user to answer the questions in Table 18 through online interaction. If the processing unit 101 of the assessment system 200 determines that the user's answer in Table 18 is "microtia," as shown in step 3410, the processing unit 101 proceeds based on the user's selection. For example, if the user chooses to continue the assessment, the assessment system 200 proceeds to step 3500; if the user chooses to stop the assessment, the assessment system 200 proceeds to step 3420 and terminates the service. The restrictions imposed by "microtia" on the user's ability to wear hearing devices have been detailed in the database creation step 2370 in Figure 2 and will not be further elaborated on here.

[0127] Furthermore, in a preferred embodiment of the present invention, Table 18 only evaluates hearing aid products, specifically notifying users of "unsuitability factors." If processing unit 101 determines that the user's answer in Table 18 is "Hearing problems are unclear," as shown in step 3430, for example, "Do you often have severe ear discharge or pus?" Processing unit 101 then further explains the question, explaining to the user which conditions are consistent with the problem, such as "Ear inflammation causes fluid or pus to be secreted," "When touching the ear canal with a finger, a moist liquid or a pus with a yellow odor is felt," etc., as shown in step 3440. After understanding the medical history, if the user selects "Do not continue the evaluation," processing unit 101 displays a "Stop evaluation" screen and terminates the service. If the user understands the medical history and selects "Continue the evaluation," processing unit 101 executes step 3500, as shown in step 3450.

[0128] Next, if the user confirms in step 3400 that their ear shape is not "microtia," or selects "Continue Evaluation" in steps 3410 or 3430, the process proceeds to step 3500. First, the processing unit 101 in the evaluation system 200 retrieves the classification of hearing device shapes from the database 210, as shown in step 3510. For example, it retrieves Table 9 (Hearing Aid Type Table), Table 10 (Hearing Aid Type Table), and Table 11 (Default Recommendation Order Table). Table 9 displays the characteristics of different hearing aid types, Table 10 displays the characteristics of different hearing aid types, and Table 11 is the default recommendation order table. Obviously, in step 3500, the processing unit 101 in the evaluation system 200 expands the 11 different hearing device characteristics tables retrieved from Tables 9 and 10, along with the hearing-related medical history questions in Table 18, into Table 20. Afterwards, the processing unit 101 of the present invention may perform a comprehensive weighted calculation and scoring based on the user's answers to the hearing-related medical history questions in Table 20, and then accumulate the scores of the 11 hearing devices of different appearances, as shown in Table 20.

[0129] Finally, based on the total scores in Table 20, the processing unit 101 recommends the available hearing device models. The method for recommending the available hearing device models may be as shown in FIG3. It should be noted that Table 20 excludes microtia and other unclear hearing problems.

[0130] Table 20

[0131] In an embodiment of the present invention, when a user answers their personal preference, for example, based on their experience using a hearing device, the processing unit 101 can then recommend the most suitable hearing device model based on the accumulated scores in Table 20. For example, when recommending three most suitable hearing device models based on Table 20, the top three scores before sorting are: hearing aid type 2, hearing aid type 6 (tied at 3.25), and hearing aid type 4 (2 points). Furthermore, in another embodiment of the present invention, if the evaluation system 200 determines that the user can only choose a hearing aid, hearing aid type 4 (2 points) is excluded. If the evaluation system 200 determines that the user is suitable for both types, hearing aid type 4 is included in the recommended model based on the score sorting. In this case, the processing unit 101 excludes hearing aid type 4 (2 points) and instead sorts based on hearing aids. For example, the processing unit 101 can recommend the most suitable hearing device model based on the accumulated scores in Table 20. For example, when recommending the three most suitable hearing device types according to Table 20, the top three scores before sorting are: hearing aid type 2 and hearing aid type 6, which are tied at 3.25. Hearing aid type 1, hearing aid type 3, hearing aid type 4, and hearing aid type 5 are tied at 1.25. Therefore, after sorting according to the default recommendation order in Table 15, hearing aid type 4 is included in the recommended type. Therefore, the three most suitable hearing device types recommended by processing unit 101 are:

[0132] 1. Hearing aid type 6

[0133] 2. Hearing aid type 2

[0134] 3. Hearing aid type 4

[0135] Afterwards, as shown in step 3800, the user self-evaluates whether to purchase a hearing aid online. In step 3800, the evaluation system 200 allows the user to self-evaluate which type of hearing aid to purchase online, or after selecting multiple types of hearing aids online, select or make an appointment for a date and which physical store to visit. After actually wearing the selected hearing aid, the user can decide to purchase the type of hearing aid that best suits the user. Obviously, regardless of whether the user purchases directly online or in a physical store, the present invention allows the user to self-select a hearing aid after fully understanding and agreeing to the hearing device recommended by the evaluation system 200.

[0136] Furthermore, if the user is unable to select or does not answer a personal preference in step 3500, a user performance prediction process will be established, as shown in step 3600. The user performance prediction assessment in step 3600 can be achieved through a process such as the quantified life impact index question in step 3610, the neurodegeneration risk assessment index in step 3620, or the exclusion of appearance styles that do not match the hearing test score in step 3630. The execution of steps 3610, 3620, and 3630 has been described in detail in the first embodiment and will not be repeated here. However, in a preferred embodiment of the present invention, step 3600 is first executed to exclude appearance styles that do not match the hearing test score in step 3630, and then either step 3620 or step 3610 can be selectively executed.

[0137] Obviously, after completing step 3600 of the second embodiment, the evaluation system 200 gives Xiao Ming the following recommendations (Table 2):

[0138] 1. The order of suitable hearing aid types is: hearing aid type 6, hearing aid type 2, and hearing aid type 4. (Based on the scores in Table 20)

[0139] 2. Applicable hearing aid shapes include the eight shapes numbered 2 to 9 in Figure 3.

[0140] Next, in step 3700, the evaluation system 200 can promote courses or videos corresponding to the recommended hearing device types based on the predicted effectiveness from step 3600. By viewing and explaining the advantages and disadvantages of various appearances, the user can understand the potential effectiveness of hearing aids / hearing assistive devices for their individual hearing strengths, thereby assisting the user in making a selection. For example, the user can use the play button on the various hearing aid designs shown in FIG3 to initiate the viewing and explanation. The relevant viewing and explanation content is stored in the database 210 in the memory unit 102. Clearly, after step 3700, the user can understand the potential effectiveness of hearing aids / hearing assistive devices for their individual hearing strengths, thereby assisting the user in making a selection.

[0141] Finally, as shown in step 3800, the user self-evaluates whether to purchase a hearing aid online. In step 3800, the evaluation system 200 allows the user to self-evaluate which hearing aid / hearing device to purchase online, or after selecting multiple hearing aid / hearing devices online, select or schedule a date and which physical store to visit. After actually wearing the selected hearing aid / hearing device, the user can decide to purchase the most suitable appearance. Obviously, regardless of whether the user purchases directly online or in a physical store, the present invention can enable the user to self-select a hearing aid / hearing device with full knowledge and consent to the hearing device recommended by the evaluation system 200.

[0142] Next, the third embodiment of FIG. 4 will be described.

[0143] First, as shown in step 3100, each user needs to create an application (App) on the user interface 110. For example, the user interface 110 can be a smart communication device, a laptop, or a desktop personal computer. The user then completes the membership registration in the cloud (or backend) through the App, which allows for the management of each user's personal information.

[0144] Next, the evaluation system 200 can select the first path. This first path follows the same process as the first embodiment, including the fit evaluation in step 3350. Therefore, this process will not be further described; only the results will be used for illustration. Clearly, the result of the first path in step 3500 is that the processing unit 101, based on the cross-reference of Table 2 and Table 3, recommends that Xiao Ming primarily use a "hearing aid." Furthermore, based on Table 13, the top three priorities are hearing aid type 5, hearing aid type 4, and hearing aid type 3.

[0145] Next, evaluation system 200 can select a second path. This second path is identical to the second embodiment and will not be further described. Only the results will be used for illustration. If processing unit 101 of evaluation system 200 determines that the user does not have microtia, the result of the second path, at step 3500, is that processing unit 101 of evaluation system 200 can determine, based on Table 20, that the top three priorities are hearing aid type 6, hearing aid type 2, and hearing aid type 4.

[0146] Based on the above, in step 3500 of the third embodiment of the present invention, after the first three values ​​of the first and second paths are included in the recommendations, the hearing devices suitable for Xiao Ming can be recommended as follows: hearing aid type 2, hearing aid type 3, hearing aid type 4, hearing aid type 5, and hearing aid type 6. Clearly, a wide range of hearing technology products can be recommended to the user in step 3500 of this embodiment.

[0147] Next, the assessment system 200 performs a user outcome prediction process, as shown in step 3600. The user outcome prediction assessment in step 3600 can be achieved through processes such as quantifying the impact on life index in step 3610, assessing the neurodegeneration risk index in step 3620, or eliminating models that do not match the hearing level in step 3630. The execution of steps 3610, 3620, and 3630 has been described in detail in the first embodiment and will not be repeated here. In a preferred embodiment of step 3600, step 3630 is first executed to eliminate models that do not match the hearing level, and then either step 3620 or step 3610 can be selectively executed. Based on the results of step 3630, the processing unit 101 excludes the hearing aid model numbered "True Wireless" in Figure 3. In other words, the eight hearing aid models numbered 2 through 9 in Figure 3 are all suitable for Xiao Ming's hearing level in Table 2.

[0148] Obviously, after completing step 3600 of the third embodiment, the evaluation system 200 gives Xiao Ming the following recommendation (Table 2):

[0149] 1. Applicable hearing aid types are: hearing aid type 2, hearing aid type 3, hearing aid type 4, hearing aid type 5 and hearing aid type 6.

[0150] 2. Applicable hearing aid shapes include the eight shapes numbered 2 to 9 in Figure 3.

[0151] Furthermore, in this embodiment of the present invention, assessment system 200 can optionally perform a neurodegeneration risk assessment to inform the user of the neurodegeneration risk assessment for both ears, as shown in step 3620. Based on the results of step 3600, processing unit 101 in assessment system 200, according to the hearing test scores in Table 2, confirms that Xiao Ming's neurodegeneration risk assessment for both ears is above "high risk." Clearly, the neurodegeneration risk assessment allows the user to determine the neurodegeneration risk index for both ears, enabling them to more proactively address hearing impairment.

[0152] Next, based on the "predicted effectiveness of the recommended hearing device appearance," the user is presented with a description of the advantages and disadvantages of the recommended appearance, allowing them to view and understand the estimated effectiveness, as shown in step 3700. In step 3700, the processing unit 101 in the evaluation system 200 presents the user with various recommended hearing aid appearances, allowing them to view and understand the advantages and disadvantages of each appearance. For example, the user can activate the viewing and explanation by pressing the play button on the various hearing aid appearances shown in FIG3 . The relevant viewing and explanation content is stored in the database 210 in the memory unit 102. Clearly, after step 3700, the user understands the advantages and disadvantages of each appearance, helping them to determine the product that suits them best.

[0153] Finally, as shown in step 3800, the user self-evaluates whether to purchase a hearing aid online. In step 3800, the evaluation system 200 allows the user to self-evaluate which hearing aid / hearing device to purchase online, or after selecting multiple hearing aid / hearing devices online, select or schedule a date and which physical store to visit. After actually wearing the selected hearing aid / hearing device, the user can decide to purchase the most suitable appearance. Obviously, regardless of whether the user purchases directly online or in a physical store, the present invention can enable the user to self-select a hearing aid / hearing device with full knowledge and consent to the hearing device recommended by the evaluation system 200.

[0154] Next, please refer to Figure 5, which illustrates another digital assessment method for selecting suitable hearing devices according to the present invention. The difference between Figures 4 and 5 is that the present invention adds a "recommendation of suitable hearing aid accessories and product specifications and features" step, as shown in step 4600, to the embodiment of Figure 5. Clearly, many processes in Figures 4 and 5 are identical. The procedures for these steps are listed in Table 21 below.

[0155] Table 21

[0156] According to the results shown in Table 21, when describing the process of Figure 5, the present invention will not explain in detail the process that is the same as Figure 4, but will present the results obtained by the same steps. For detailed descriptions of each identical step, please refer to the identical step in Table 21 corresponding to Figure 4, which will be explained first.

[0157] First, after confirming the user's identity, during the startup process of the assessment system 200, the processing unit 101 accesses the fit database and obtains the following information: Table 3 (Hearing Assisted Device / Hearing Aid Suitability Analysis Table), Table 4 (Example Table of Neurodegeneration Risk Assessment Index), Table 5 (Average Fit Range of Commercially Available Hearing Devices), Table 6 (Hearing Scale Code Classification Table), and Table 7 (Appearance Model Classification Table for Excluding Incompatible Hearing Scales). The fit database has been established in FIG. 2 and stored in the database 210 in the memory unit 102.

[0158] Next, after the evaluation system 200 performs the fit evaluation in step 4350, the processing unit 101 can, in step 4500, recommend that Xiao Ming use "hearing aids" as the primary choice based on the results of cross-referencing Table 2 and Table 3. Furthermore, according to Table 11, the top three priorities are hearing aid type 5, hearing aid type 4, and hearing aid type 3.

[0159] Next, after the evaluation system 200 obtains the personal hearing history questions in Table 18 through step 4330, in step 4400, when the processing unit 101 of the evaluation system 200 confirms that the user does not have "microtia", the result that the evaluation system 200 can obtain in step 4500 is that the processing unit 101 in the evaluation system 200 can obtain the top three priorities according to Table 20: hearing aid type 6, hearing aid type 2, and hearing aid type 4.

[0160] According to the above, after step 4350 and step 4400, the hearing devices suitable for Xiao Ming that can be recommended in step 4500 include: hearing aid type 2, hearing aid type 3, hearing aid type 4, hearing aid type 5, and hearing aid type 6.

[0161] Next, the process of "recommending suitable hearing assistive device accessories and product specifications and features" is performed, as shown in step 4600. The purpose of recommending suitable hearing assistive device accessories is to help users understand that hearing health and ability are not solely dependent on personal hearing devices, but other hearing assistive devices are also part of the solution.

[0162] First, as shown in step 4610, the evaluation system 200 guides the user to watch a video describing the pros and cons of each hearing device design recommended for Xiao Ming in step 4500. Then, as shown in step 4620, the processing unit 101 of the evaluation system 200 conducts a question-and-answer session with the user. If the user selects three preferred design products, the processing unit 101 assigns scores to these design products and accumulates the scores. For example, after viewing the pros and cons descriptions in step 4610, the user can select their preferred design and assign a cumulative score of 2 to the selected design product. In a preferred embodiment, once the user has selected their preferred appearance, the evaluation system 200 can directly jump to step 4950. The evaluation system 200 allows the user to self-evaluate which appearance of hearing aid to purchase online, or to select multiple appearances of hearing aids / hearing assistive devices online, then select or schedule a date and a physical store to visit. After actually wearing the selected hearing aid / hearing assistive device, the user can then decide to purchase the appearance that best suits the user. Obviously, regardless of whether the user purchases directly online or in a physical store, the present invention allows the user to fully understand and agree with the hearing device recommendations of the evaluation system 200 and then purchase the hearing aid / hearing assistive device.

[0163] Next, as shown in step 4630, the processing unit 101 of the evaluation system 200 retrieves the scoring table for hearing aids and accessories in Table 15 from the database 210 of the memory unit 102. The processing unit 101 of the evaluation system 200 then guides the user to watch a video explaining the pros and cons of the hearing device's physical buttons (e.g., the presence or absence of buttons, or buttons located on the back) or the presence or absence of app operation. For example, the evaluation system 200 guides the user to watch the hearing device recommended for Xiao Ming in step 4500. Then, as shown in step 4640, the processing unit 101 of the evaluation system 200 conducts the user's Q&A session in Table 15 and assigns a score based on the user's confirmation of the ease of use of the physical buttons, app operation, or button size. For example, an example scoring table for physical buttons or the presence or absence of app operation. For example, if the question is "Would you prefer physical buttons?" and the user answers "physical buttons," the evaluation system 200 assigns a score based on the answer, e.g., 1 point. Alternatively, when the question is "Would you prefer a concealed hearing aid or one that is not visible?", and the user answers "like an earphone," "invisible," or "both," the evaluation system 200 assigns a score based on the answer, for example, 1 point.

[0164] Next, as shown in step 4650, the processing unit 101 of the evaluation system 200 retrieves the example scoring table for the daily usage hours score table shown in Table 16 from the database 210 of the memory unit 102. The evaluation system 200 guides the user to watch a video explaining the correlation between wearing time and nerve stimulation, and the pros and cons. For example, it explains which hearing device shape should be selected to allow the user to wear the device longer, thereby stimulating the auditory nerve longer and achieving rehabilitation or maintenance effects. Then, as shown in step 4660, the processing unit 101 of the evaluation system 200 conducts the user's questionnaire shown in Table 16. The evaluation system 200 assigns a score based on the user's estimated daily usage hours, for example, 0.5 points for 4 hours of daily use and 1 point for more than 8 hours.

[0165] Next, as shown in step 4670, the processing unit 101 of the evaluation system 200 retrieves the scoring example table for the advantages and disadvantages of concealed hearing devices from the database 210 of the memory unit 102 in Table 17. The evaluation system 200 guides the user to watch a video explaining the advantages and disadvantages of concealed hearing devices. Then, as shown in step 4680, the processing unit 101 of the evaluation system 200 conducts the user's questionnaire in Table 17 and assigns a score based on the user's response to their appearance preference. For example, if the question is "Would you prefer a concealed hearing aid or one that is invisible?" and the user answers "like earphones," "invisible," or "both," the evaluation system 200 assigns a score based on the answer, for example, 1 point.

[0166] After the evaluation system 200 completes the "Recommend suitable hearing aid accessories and product specifications and features" question with the user in step 4600, it calculates a score in step 4700 to recommend the most suitable hearing device type for the user based on the score. As shown in step 4700, the processing unit 101 in the evaluation system 200 combines the questions in Tables 14, 15, 16, 17, and 18 with Tables 9 and 10 to form Table 19. Next, based on the user's answers to the "Recommend suitable hearing aid accessories" question, the processing unit 101 enters the score into Table 19. Finally, before the processing unit 101 sorts the scores in Table 19, the top three scores are: hearing aid type 2 and hearing aid type 6, tied at 9.25; hearing aid type 1, hearing aid type 3, hearing aid type 4, and hearing aid type 5, tied at 7.25. In a preferred embodiment of the present invention, when multiple models with the same score are generated, the present invention can further refer to the default recommendation order in Table 11, and the model with the highest score will be ranked first. Therefore, according to the default recommendation order in Table 11, for models with the same score, hearing aid model 4 is the highest priority, so hearing aid model 4 is selected as the third recommended model. Therefore, in this embodiment, the three models recommended to Xiao Ming are:

[0167] 1. Hearing aid type 6

[0168] 2. Hearing aid type 2

[0169] 3. Hearing aid type 4

[0170] Next, the evaluation system 200 performs the process of establishing a user outcome prediction, as shown in step 4800. First, based on the evaluation results of "excluding models that do not match the hearing scores" in step 4830, the processing unit 101 compares the hearing scores in Table 2 with Table 5 (Average Fit Range of Commercially Available Hearing Devices), Table 6 (Hearing Score Code Classification Table), and Table 7 (Classification Table of Models that Do Not Match the Hearing Score). The evaluation result excludes the hearing aid model "True Wireless Model No. 1" in Figure 3. In other words, the eight hearing aid models No. 2 through No. 9 in Figure 3 are all suitable for Xiao Ming's hearing scores in Table 2.

[0171] Obviously, after completing the evaluation result of step 4800, the evaluation system 200 gives Xiao Ming the following recommendation in Table 2:

[0172] 1. The order of applicable hearing aid types is: hearing aid type 6, hearing aid type 2 and hearing aid type 4.

[0173] 2. Applicable hearing aid shapes include the eight shapes numbered 2 to 9 in Figure 3.

[0174] Furthermore, in this embodiment of the present invention, assessment system 200 can optionally perform a neurodegeneration risk assessment to inform the user of the neurodegeneration risk assessment for both ears, as shown in step 4820. Based on the results of step 4800, processing unit 101 in assessment system 200, according to the hearing test scores in Table 2, confirms that Xiao Ming's neurodegeneration risk assessment for both ears is above "high risk." Clearly, the neurodegeneration risk assessment allows the user to determine the neurodegeneration risk index for both ears, enabling them to more proactively address hearing impairment.

[0175] Next, based on the "predicted effectiveness of the recommended hearing device appearance," the user is presented with a description of the advantages and disadvantages of the recommended appearance, allowing them to view and understand the estimated effectiveness, as shown in step 4900. In step 4900, the processing unit 101 in the evaluation system 200 presents the user with various recommended hearing aid appearances, allowing them to view and understand the advantages and disadvantages of each appearance. For example, the user can activate the viewing and explanation by pressing the play button on the various hearing aid appearances shown in FIG3 . The relevant viewing and explanation content is stored in the database 210 in the memory unit 102. Clearly, after step 4900, the user understands the advantages and disadvantages of each appearance, helping them to determine the product that suits them best.

[0176] Finally, as shown in step 4950, the user self-evaluates whether to purchase a hearing aid online. In step 4950, the evaluation system 200 allows the user to self-evaluate which hearing aid / hearing device to purchase online, or after selecting multiple hearing aid / hearing device designs online, select or schedule a date and which physical store to visit. After actually wearing the selected hearing aid / hearing device, the user can decide to purchase the design that best suits the user. Obviously, regardless of whether the user purchases directly online or in a physical store, the present invention allows the user to self-select a hearing aid / hearing device with full knowledge and consent to the hearing device recommended by the evaluation system 200.

[0177] The above description is only a preferred embodiment of the present invention and is not intended to limit the scope of the present invention. At the same time, the above description should be understandable and implementable for professionals in the relevant technical field. Therefore, other equivalent changes or modifications that do not depart from the spirit disclosed by the present invention should be included in the scope of the patent application.

Claims

1. A digital evaluation method for selecting a suitable hearing device, characterized in that: include: Completing the login means that the user completes the login to the evaluation system through the user interface, and the evaluation system includes a processing unit and a memory unit; To perform a numerical scoring of the hearing history, the processing unit in the evaluation system retrieves the hearing history questions from the memory unit, and the processing unit conducts a question-and-answer session with the user on the hearing history questions; The hearing device type that can be selected is recommended after the processing unit retrieves the hearing device type classification from the memory unit, and the processing unit scores and sorts the results of the hearing history question answer record, and recommends at least one hearing device type according to the cumulative score sorting.

2. The digital evaluation method for selecting a suitable hearing device according to claim 1, characterized in that : When the processing unit detects limiting issues in the questions and answers about the hearing history, the processing unit selects whether to continue the assessment based on the user's choice.

3. A digital evaluation method for selecting a suitable hearing device, characterized in that: include: Completing the login means that the user completes the login to the evaluation system through the user interface, and the evaluation system includes a processing unit and a memory unit; Receiving an audiogram from a user, wherein the user inputs the audiogram to the evaluation system through a user interface, and the evaluation system obtains hearing scores of the left ear and the right ear according to the audiogram; The fit evaluation is performed by the processing unit in the evaluation system obtaining the hearing aid / hearing aid applicable analysis table from the memory unit, and the processing unit compares the hearing strength of the left ear and the right ear with the hearing aid / hearing aid applicable analysis table to obtain the fit evaluation result, including: whether the user is suitable for the hearing aid or the hearing aid, or both the hearing aid and the hearing aid; and The hearing device type that can be selected is recommended by the processing unit to the memory unit after the classification of the hearing device type is captured, and then at least one hearing device type is recommended according to the fit evaluation result.

4. The digital evaluation method for selecting a suitable hearing device according to claim 3, characterized in that To further predict the user's performance, the processing unit retrieves the fit range table from the memory unit, and compares the hearing scores of the left ear and the right ear with the fit range table to obtain a hearing score status code. After that, the hearing score status code is compared with the hearing score code classification table to obtain a classification code that matches the hearing score status code. Then, the code is compared with the appearance style classification table to exclude at least one appearance that does not match the hearing score.

5. The digital evaluation method for selecting a suitable hearing device according to claim 3, characterized in that : To further evaluate the impact on life index, the processing unit obtains a quantitative impact on life index table from the memory unit, and gives the user corresponding suggestions based on the score range of the quantitative impact on life index evaluation result table.

6. The digital evaluation method for selecting a suitable hearing device according to claim 3, characterized in that : Further performing the neurodegeneration risk assessment, the processing unit obtains the neurodegeneration risk assessment index example table from the memory unit, and gives the user a recommendation for selecting a hearing device based on the assessment result of the neurodegeneration risk assessment index example table.

7. The digital evaluation method for selecting a suitable hearing device according to claim 3, characterized in that When comparing the hearing strengths of the left ear and the right ear with the matching range table, the ear with the better hearing strength is selected for comparison.

8. The digital evaluation method for selecting a suitable hearing device according to claim 3, characterized in that When predicting user performance, a personal technological capability assessment is further performed, wherein the processing unit obtains a personal technological capability question list from the memory unit, and gives the user recommendations for selecting a hearing device based on the assessment results of the personal technological capability question list.

9. A digital evaluation method for selecting a suitable hearing device, characterized in that: include: Completing the login means that the user completes the login to the evaluation system through the user interface, and the evaluation system includes a processing unit and a memory unit; To conduct a numerical scoring of the hearing history, the processing unit in the evaluation system retrieves the hearing history questions from the memory unit, and then the processing unit conducts a question-and-answer session with the user on the hearing history questions; Receiving an audiogram from a user, wherein the user inputs the audiogram to the evaluation system through a user interface, and the evaluation system obtains hearing scores of the left ear and the right ear according to the input audiogram; The fit evaluation is performed by the processing unit in the evaluation system retrieving the hearing aid / hearing aid applicable analysis table from the memory unit, and then the processing unit compares the hearing strength of the left ear and the right ear with the hearing aid / hearing aid applicable analysis table to obtain the fit evaluation result, including: whether the user is suitable for the hearing aid or the hearing aid, or both the hearing aid and the hearing aid; and The hearing device type to be recommended is that the processing unit retrieves the classification of the hearing device type from the memory unit and recommends at least one hearing device type according to the fit evaluation result and the answer result of the hearing history question.

10. The digital evaluation method for selecting a suitable hearing device according to claim 9, characterized in that: To further eliminate the appearance that does not match the hearing strength, the processing unit retrieves the adaptation range table from the memory unit, and compares the hearing strength of the left ear and the right ear with the adaptation range table to obtain a hearing strength status code. Then, the hearing strength status code is compared with the hearing strength code code classification table to obtain a classification code that matches the hearing strength status code. Then, the code is compared with the appearance style classification table to eliminate at least one appearance that does not match the hearing strength.

11. The digital evaluation method for selecting a suitable hearing device according to claim 9, characterized in that :When the processing unit detects limiting questions from the questions and answers about the hearing history, the processing unit selects whether to continue the assessment based on the user's choice.

12. The digital evaluation method for selecting a suitable hearing device according to claim 9, wherein In the user performance prediction, the life impact index is further evaluated, that is, the processing unit obtains a quantitative life impact index table from the memory unit, and gives the user corresponding suggestions based on the score range of the quantitative life impact index evaluation result table.

13. The digital evaluation method for selecting a suitable hearing device according to claim 9, characterized in that When predicting user performance, a personal technological capability assessment is further performed, wherein the processing unit obtains a personal technological capability question list from the memory unit, and gives the user recommendations for selecting a hearing device based on the assessment results of the personal technological capability question list.

14. The digital evaluation method for selecting a suitable hearing device according to claim 9, wherein In the user performance prediction, a neurodegeneration risk assessment is further performed, wherein the processing unit obtains an example table of neurodegeneration risk assessment indexes from a memory unit, and gives the user recommendations for selecting a hearing device based on the assessment results of the example table of neurodegeneration risk assessment indexes.

15. The digital evaluation method for selecting a suitable hearing device according to claim 9, characterized in that When comparing the hearing strengths of the left ear and the right ear with the matching range table, the ear with the better hearing strength is selected for comparison.

16. A digital evaluation method for selecting a suitable hearing device, characterized in that: include: Completing the login means that the user completes the login to the evaluation system through the user interface, and the evaluation system includes a processing unit and a memory unit; To conduct a numerical scoring of the hearing history, the processing unit in the evaluation system retrieves the hearing history questions from the memory unit, and then the processing unit conducts a question-and-answer session with the user on the hearing history questions; Receiving an audiogram from a user, wherein the user inputs the audiogram to the evaluation system through a user interface, and the evaluation system obtains hearing scores of the left ear and the right ear according to the input audiogram; The fit evaluation is performed by the processing unit in the evaluation system retrieving the hearing aid / hearing aid applicable analysis table from the memory unit, and then the processing unit compares the hearing scores of the left ear and the right ear with the hearing aid / hearing aid applicable analysis table to obtain the fit evaluation result, including: whether the user is suitable for the hearing aid or the hearing aid, or both the hearing aid and the hearing aid; The processing unit and the memory unit extract the classification of the hearing device types and recommend at least one hearing device type according to the fit evaluation result and the answer result of the hearing history question. as well as The processing unit guides the user to view the advantages and disadvantages of the appearance of the hearing device, gives points according to the user's selection, and provides the most suitable product type recommendation based on the points.

17. The digital evaluation method for selecting a suitable hearing device according to claim 16, wherein: To further predict the user's performance, the processing unit retrieves the fit range table from the memory unit, and compares the hearing strength of the left ear and the right ear with the fit range table to obtain a hearing strength status code. After that, the hearing strength status code is compared with the hearing strength code classification table to obtain a classification code that matches the hearing strength status code. Then, the code is compared with the appearance style classification table to exclude at least one appearance that does not match the hearing strength.

18. The digital evaluation method for selecting a suitable hearing device according to claim 16, wherein : When the processing unit detects limiting issues in the questions and answers about the hearing history, the processing unit selects whether to continue the assessment based on the user's choice.

19. The digital evaluation method for selecting a suitable hearing device according to claim 16, wherein When predicting user performance, a personal technological capability assessment is further performed, wherein the processing unit obtains a personal technological capability question list from the memory unit, and gives the user recommendations for selecting a hearing device based on the assessment results of the personal technological capability question list.

20. The digital evaluation method for selecting a suitable hearing device according to claim 16, wherein : In guiding users to view the pros and cons of the appearance of the hearing device, include: viewing the physical button description and rating of the hearing device.

21. The digital evaluation method for selecting a suitable hearing device according to claim 16, wherein : In guiding users to view the pros and cons of the appearance of hearing devices, include: viewing the correlation between wearing time and nerve stimulation and scoring.

22. The digital evaluation method for selecting a suitable hearing device according to claim 16, wherein : In guiding users to view the pros and cons of the appearance of hearing devices, include: viewing the hidden pros and cons description and ratings.

23. The digital evaluation method for selecting a suitable hearing device according to claim 16, wherein In the user performance prediction, the life impact index is further evaluated, that is, the processing unit obtains a quantitative life impact index table from the memory unit, and gives the user corresponding suggestions based on the score range of the quantitative life impact index evaluation result table.

24. The digital evaluation method for selecting a suitable hearing device according to claim 16, wherein In the user performance prediction, a neurodegeneration risk assessment is further performed, wherein the processing unit obtains an example table of neurodegeneration risk assessment indexes from a memory unit, and gives the user recommendations for selecting a hearing device based on the assessment results of the example table of neurodegeneration risk assessment indexes.

25. The digital evaluation method for selecting a suitable hearing device according to claim 16, wherein When comparing the hearing strengths of the left ear and the right ear with the matching range table, the ear with the better hearing strength is selected for comparison.

26. A digital evaluation system for selecting a suitable hearing device, characterized in that: The evaluation system comprises a processing unit and a memory unit, wherein the evaluation system assists the user in selecting a hearing device through the following procedure, wherein the procedure comprises: Completing the login means that the user completes the login to the evaluation system through the user interface; To perform a numerical scoring of the hearing history, the processing unit in the evaluation system retrieves the hearing history questions from the memory unit, and the processing unit conducts a question-and-answer session with the user on the hearing history questions; The hearing device type that can be selected is recommended after the processing unit retrieves the hearing device type classification from the memory unit, and the processing unit scores and sorts the results of the hearing history question answer record, and recommends at least one hearing device type according to the cumulative score sorting.

27. A digital evaluation system for selecting a suitable hearing device, characterized in that: The evaluation system comprises a processing unit and a memory unit, wherein the evaluation system assists the user in selecting a hearing device through the following procedure, wherein the procedure comprises: Completing the login means that the user completes the login to the evaluation system through the user interface; Receiving an audiogram from a user, wherein the user inputs the audiogram to the evaluation system through a user interface, and the evaluation system obtains hearing scores of the left ear and the right ear according to the input audiogram; The fit evaluation is performed by the processing unit in the evaluation system obtaining the hearing aid / hearing aid applicable analysis table from the memory unit, and the processing unit compares the hearing strength of the left ear and the right ear with the hearing aid / hearing aid applicable analysis table to obtain the fit evaluation result, including: whether the user is suitable for the hearing aid or the hearing aid, or both the hearing aid and the hearing aid; and The hearing device type that can be selected is recommended by the processing unit to the memory unit after the classification of the hearing device type is captured, and then at least one hearing device type is recommended according to the fit evaluation result.

28. A digital evaluation system for selecting a suitable hearing device, characterized in that: The evaluation system comprises a processing unit and a memory unit, wherein the evaluation system assists the user in selecting a hearing device through the following procedure, wherein the procedure comprises: Completing the login means that the user completes the login to the evaluation system through the user interface, and the evaluation system includes a processing unit and a memory unit; To conduct a numerical scoring of the hearing history, the processing unit in the evaluation system retrieves the hearing history questions from the memory unit, and then the processing unit conducts a question-and-answer session with the user on the hearing history questions; Receiving an audiogram from a user, wherein the user inputs the audiogram to the evaluation system through a user interface, and the evaluation system obtains hearing scores of the left ear and the right ear according to the input audiogram; The fit evaluation is performed by the processing unit in the evaluation system retrieving the hearing aid / hearing aid applicable analysis table from the memory unit, and then the processing unit compares the hearing strength of the left ear and the right ear with the hearing aid / hearing aid applicable analysis table to obtain the fit evaluation result, including: whether the user is suitable for the hearing aid or the hearing aid, or both the hearing aid and the hearing aid; and The hearing device type to be recommended is that the processing unit retrieves the classification of the hearing device type from the memory unit and recommends at least one hearing device type according to the fit evaluation result and the answer result of the hearing history question.

29. A digital evaluation system for selecting a suitable hearing device, characterized in that: The evaluation system comprises a processing unit and a memory unit, wherein the evaluation system assists the user in selecting a hearing device through the following procedure, wherein the procedure comprises: Completing the login means that the user completes the login to the evaluation system through the user interface; To conduct a numerical scoring of the hearing history, the processing unit in the evaluation system retrieves the hearing history questions from the memory unit, and then the processing unit conducts a question-and-answer session with the user on the hearing history questions; Receiving an audiogram from a user, wherein the user inputs the audiogram to the evaluation system through a user interface, and the evaluation system obtains hearing scores of the left ear and the right ear according to the input audiogram; The fit evaluation is performed by the processing unit in the evaluation system retrieving the hearing aid / hearing aid applicable analysis table from the memory unit, and then the processing unit compares the hearing scores of the left ear and the right ear with the hearing aid / hearing aid applicable analysis table to obtain the fit evaluation result, including: whether the user is suitable for the hearing aid or the hearing aid, or both the hearing aid and the hearing aid; The processing unit and the memory unit extract the classification of the hearing device types and recommend at least one hearing device type according to the fit evaluation result and the answer result of the hearing history question. Recommending suitable hearing aid accessories and product specifications and features, wherein the processing unit guides the user to view the advantages and disadvantages of the appearance of the hearing device, and gives points according to the user's selection, and provides the most suitable product type recommendation based on the points; To predict the user's performance, the processing unit retrieves the fit range table from the memory unit, and compares the hearing strength of the left ear and the right ear with the fit range table to obtain a hearing strength status code. After that, the hearing strength status code is compared with the hearing strength code classification table to obtain a classification code that matches the hearing strength status code. Then, the code is compared with the appearance style classification table to exclude at least one appearance that does not match the hearing strength. According to the recommended available hearing device types and after eliminating the appearance that does not match the hearing score, the processing unit recommends at least one type of hearing device to the user.

30. The digital evaluation system for selecting a suitable hearing device as claimed in claims 26-29, characterized in that :The evaluation system is configured in a cloud.

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