A method for binaural loudness balance for air conduction hearing aids

Abstract

The application relates to the field of air conduction hearing aids, in particular to a binaural loudness balance method for air conduction hearing aids, comprising a hearing aid system, which is internally provided with a system architecture module, a balance algorithm module, a hardware design module, a software design module and a personalization adjustment module. The method realizes a binaural loudness balance method for air conduction hearing aids through sound signal processing, loudness parameter estimation and personalization adjustment strategies. The method has the characteristics of real-time, accuracy and personalization, and is helpful to improve the hearing quality and comfort of hearing aid users. The method collects hearing data of patients, automatically adjusts the volume of the hearing aid by using an intelligent algorithm, and realizes binaural loudness balance. The method not only improves the balance accuracy, but also greatly improves the use experience of the patients. The user demand and use habit are deeply researched, and more intelligent and personalized loudness balance services are provided.

Description

Technical Field

[0001] This invention relates to the field of air conduction hearing aid technology, specifically a method for binaural loudness balancing in air conduction hearing aids. Background Technology

[0002] Air conduction hearing aids are hearing aids that conduct sound through the air, and they are an important component of modern hearing assistance technology. With technological advancements and improved living standards, more and more people with hearing impairments are paying attention to and accepting hearing aids. Hearing loss is particularly prevalent among the elderly, and air conduction hearing aids provide them with significant assistance.

[0003] In existing air conduction hearing aids, binaural loudness balance is typically achieved by adjusting the volume of each ear. However, this method often requires patients to personally test the sound, the adjustment process is cumbersome, and it is difficult to achieve perfect balance. Therefore, we propose a new binaural loudness balance method. Summary of the Invention

[0004] To address the problems in the prior art, this invention provides a method for binaural loudness balancing in air conduction hearing aids.

[0005] The technical solution adopted by the present invention to solve its technical problem is: a binaural loudness balancing method for air conduction hearing aids, including a hearing aid system, wherein the hearing aid system is provided with a system architecture module, a balance algorithm module, a hardware design module, a software design module and a personalized adjustment module, and the system architecture module, the balance algorithm module, the hardware design module, the software design module and the personalized adjustment module are interconnected.

[0006] The system architecture module includes a microphone module, an audio processing module, a binaural loudness balance module, and a power amplifier module. The microphone module is used to collect sound signals from the environment. The audio processing module processes the sound signals collected by the microphone, including filtering, amplification, and noise reduction. The binaural loudness balance module automatically adjusts the volume of the left and right ears according to the user's hearing condition to achieve binaural loudness balance. The power amplifier module amplifies the processed sound signal and transmits it to the user's ears.

[0007] The balancing algorithm module includes a collection module, a processing module, a comparison module, and an adjustment module. The collection module acquires ambient sound and speech signals through sound signal acquisition, in conjunction with sensors such as microphones. The processing module provides noise reduction for the sound signals, employing digital signal processing techniques such as filtering and suppression to reduce the interference of background noise on the signal. The comparison module separates the sound signals using sound source separation technology to isolate the target sound signal from the mixed sound signals, enhancing the sound signal and comparing the sounds from both ears. The adjustment module uses gain control, compression, and other methods to achieve a suitable loudness level for the target sound signal.

[0008] The hardware design module includes multiple microphones, an audio processor, a battery, and a wireless module. The microphones are used to capture ambient sounds, the audio processor is responsible for processing the sound signals, the battery provides power to the system, and the wireless module is used to enable communication between devices.

[0009] The software design module utilizes an audio processing algorithm, a binaural loudness balance algorithm, and a user interface. The audio processing algorithm is responsible for processing the sound captured by the microphone, such as noise reduction and amplification. The binaural loudness balance algorithm dynamically adjusts the volume of the left and right ears based on the user's hearing data to achieve binaural loudness balance. The user interface allows users to adjust the volume and switch programs according to their own needs.

[0010] When in use, the binaural loudness balancing module calculates the loudness of the sound signal based on its amplitude, duration, and other characteristics. It also performs Fourier transform and other analyses on the sound signal to obtain its frequency components and energy distribution. Based on the sound signal's propagation environment and receiving location, it establishes a sound field model to simulate the sound signal's propagation process, facilitating the addition of personalized adjustment strategies for subsequent sound balancing.

[0011] The personalized adjustment module assesses the user's hearing threshold and degree of hearing loss through methods such as hearing tests. Based on the user's hearing threshold and degree of hearing loss, it adjusts the loudness of the binaural hearing aids to achieve a suitable matching effect. According to the user's auditory feedback and environmental changes, it adjusts the loudness of the binaural hearing aids in real time to adapt to different auditory needs. Moreover, during use, it establishes a model of the user's auditory habits and preferences through methods such as machine learning to achieve personalized loudness balance adjustment.

[0012] The following usage steps are included: Step 1: When using an air conduction hearing aid, the system architecture module first uses a microphone module, audio processing module, binaural loudness balance module, and power amplification module to quickly collect sounds from the external environment. Then, the audio processing module filters, amplifies, and reduces noise in the sound signals collected by the microphone to increase the overall clarity of the collected sound. In addition, the binaural loudness balance module automatically adjusts the volume of the left and right ears according to the user's pre-recorded binaural hearing status to achieve binaural loudness balance and increase overall adaptability. The power amplification module amplifies the processed sound signal and transmits it to the user's ears. The second step: The balance algorithm module can process the internal situation to adjust the air conduction hearing aid. It also assesses the user's hearing threshold and degree of hearing loss based on the user's usage habits. According to the degree of hearing loss, it automatically adjusts the loudness of the sound when the hearing aid is used to achieve the best effect. At the same time, when the user's auditory feedback and environment change during use, it adjusts the sound of the binaural hearing aid in a timely manner to adapt to different auditory needs. During use, machine learning and other methods are used to establish a model of the user's auditory habits and preferences to achieve personalized loudness balance adjustment. The third step is to adjust the hardware parameters of the hearing aid through the hardware design module to achieve loudness balance. This can be done by changing the microphone sensitivity, the power amplifier size, etc., to adjust the loudness of both ears. However, this method requires personalized customization based on the user's ear structure and hearing condition. The software design module algorithm calculates the loudness difference between the two ears, and then the software processes the sound signal to make the loudness received by both ears equal. The adjustment process is simple and low-cost.

[0013] The beneficial effects of this invention are: (1) The present invention provides a binaural loudness balancing method for air conduction hearing aids. This method achieves binaural loudness balancing through sound signal processing, loudness parameter estimation, and personalized adjustment strategies. This method features real-time performance, accuracy, and personalization, helping to improve the hearing quality and comfort of hearing aid users. By setting this method, the system collects the patient's hearing data and uses intelligent algorithms to automatically adjust the volume of the hearing aid to achieve binaural loudness balancing. This method not only improves the accuracy of balancing but also greatly enhances the user experience. It delves into user needs and usage habits, providing a more intelligent and personalized loudness balancing service. Attached Figure Description

[0014] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0015] Figure 1 A schematic diagram of the overall framework structure of a binaural loudness balancing method for an air conduction hearing aid provided by the present invention; Figure 2 This is a schematic diagram of the system architecture module in the clamping mechanism of the air conduction hearing aid binaural loudness balancing method provided by the present invention; Figure 3 This is a schematic diagram of the flow structure of the balance algorithm module in the driving mechanism of an air conduction hearing aid binaural loudness balancing method provided by the present invention. Detailed Implementation

[0016] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0017] like Figures 1-3 As shown, the present invention provides a binaural loudness balancing method for an air conduction hearing aid, comprising a hearing aid system. The hearing aid system internally includes a system architecture module, a balance algorithm module, a hardware design module, a software design module, and a personalized adjustment module, and the system architecture module, the balance algorithm module, the hardware design module, the software design module, and the personalized adjustment module are interconnected. The system architecture module includes a microphone module, an audio processing module, a binaural loudness balance module, and a power amplifier module. The microphone module is used to collect sound signals from the environment; the audio processing module processes the sound signals collected by the microphone, including filtering, amplification, and noise reduction; the binaural loudness balance module automatically adjusts the volume of the left and right ears according to the user's hearing condition to achieve binaural loudness balance; and the power amplifier module amplifies the processed sound signal and transmits it to the user's ears. The balance algorithm module includes a collection module, a processing module, a comparison module, and an adjustment module. The collection module acquires ambient sound and speech signals through sound signal acquisition, in conjunction with sensors such as microphones. The processing module provides noise reduction for the sound signals, employing digital signal processing techniques such as filtering and suppression to reduce the interference of background noise on the signal. The comparison module separates the sound signals using sound source separation technology to isolate the target sound signal from the mixed sound signals, enhancing the sound signal and comparing the sounds from both ears. The adjustment module uses gain control, compression, and other methods to achieve an appropriate loudness level for the target sound signal.

[0018] The hardware design module includes multiple microphones, an audio processor, a battery, and a wireless module. The microphones are used to capture ambient sounds, the audio processor is responsible for processing the sound signals, the battery provides power to the system, and the wireless module is used to enable communication between devices.

[0019] The software design module utilizes audio processing algorithms, binaural loudness balancing algorithms, and a user interface. The audio processing algorithm is responsible for processing the sound captured by the microphone, such as noise reduction and amplification. The binaural loudness balancing algorithm dynamically adjusts the volume of the left and right ears based on the user's hearing data to achieve binaural loudness balance. The user interface allows users to adjust the volume and switch programs according to their own needs.

[0020] When in use, the binaural loudness balance module calculates the loudness of the sound signal based on its amplitude, duration, and other characteristics. It also performs Fourier transform and other analyses on the sound signal to obtain its frequency components and energy distribution. Based on the sound signal's propagation environment and receiving location, it establishes a sound field model to simulate the sound signal's propagation process, facilitating the addition of personalized adjustment strategies for later sound balancing.

[0021] The personalized adjustment module assesses the user's hearing threshold and degree of hearing loss through methods such as hearing tests. Based on the user's hearing threshold and degree of hearing loss, it adjusts the loudness of the binaural hearing aids to achieve a suitable matching effect. It also adjusts the loudness of the binaural hearing aids in real time according to the user's auditory feedback and environmental changes to adapt to different auditory needs. Furthermore, during use, it establishes a model of the user's auditory habits and preferences through methods such as machine learning to achieve personalized loudness balance adjustment.

[0022] In practical use: When using an air conduction hearing aid, the system architecture modules—microphone, audio processing, binaural loudness balance, and power amplification—first rapidly collect sounds from the external environment. The audio processing module then filters, amplifies, and reduces noise in the collected sound signal, increasing overall clarity. The binaural loudness balance module automatically adjusts the volume of each ear based on the user's pre-recorded hearing information, achieving binaural loudness balance and enhancing overall adaptability. The power amplification module amplifies the processed sound signal and transmits it to the user's ears. The balance algorithm module processes the internal data to adjust the air conduction hearing aid, assessing the user's hearing threshold and degree of hearing loss based on usage habits. The system automatically adjusts the loudness of the hearing aids based on the degree of hearing loss to achieve optimal performance. It also adjusts the sound levels in both ears promptly to adapt to changes in the user's auditory feedback and environment, catering to different hearing needs. During use, machine learning and other methods are used to build a model of the user's auditory habits and preferences, enabling personalized loudness balance adjustments. Loudness balance can also be achieved by adjusting the hardware parameters of the hearing aids through a hardware design module, such as changing microphone sensitivity and amplifier power. However, this method requires customization based on the user's ear structure and hearing condition. Alternatively, a software design module algorithm calculates the loudness difference between the two ears and processes the sound signals to ensure equal loudness in both ears. This adjustment process is simple and low-cost. The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of protection claimed by the present invention. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for binaural loudness balancing in an air conduction hearing aid, characterized in that, The system includes a hearing aid system, which internally comprises a system architecture module, a balance algorithm module, a hardware design module, a software design module, and a personalized adjustment module, and the system architecture module, the balance algorithm module, the hardware design module, the software design module, and the personalized adjustment module are interconnected.

2. The binaural loudness balancing method for an air conduction hearing aid according to claim 1, characterized in that: The system architecture module includes a microphone module, an audio processing module, a binaural loudness balance module, and a power amplifier module. The microphone module is used to collect sound signals from the environment. The audio processing module processes the sound signals collected by the microphone, including filtering, amplification, and noise reduction. The binaural loudness balance module automatically adjusts the volume of the left and right ears according to the user's hearing condition to achieve binaural loudness balance. The power amplifier module amplifies the processed sound signal and transmits it to the user's ears.

3. The binaural loudness balancing method for an air conduction hearing aid according to claim 1, characterized in that: The balancing algorithm module includes a collection module, a processing module, a comparison module, and an adjustment module. The collection module acquires ambient sound and speech signals through sound signal acquisition, in conjunction with sensors such as microphones. The processing module provides noise reduction for the sound signals, employing digital signal processing techniques such as filtering and suppression to reduce the interference of background noise on the signal. The comparison module separates the sound signals using sound source separation technology to isolate the target sound signal from the mixed sound signals, enhancing the sound signal and comparing the sounds from both ears. The adjustment module uses gain control, compression, and other methods to achieve a suitable loudness level for the target sound signal.

4. The binaural loudness balancing method for an air conduction hearing aid according to claim 1, characterized in that: The hardware design module includes multiple microphones, an audio processor, a battery, and a wireless module. The microphones are used to capture ambient sounds, the audio processor is responsible for processing the sound signals, the battery provides power to the system, and the wireless module is used to enable communication between devices.

5. The binaural loudness balancing method for an air conduction hearing aid according to claim 1, characterized in that: The software design module utilizes an audio processing algorithm, a binaural loudness balance algorithm, and a user interface. The audio processing algorithm is responsible for processing the sound captured by the microphone, such as noise reduction and amplification. The binaural loudness balance algorithm dynamically adjusts the volume of the left and right ears based on the user's hearing data to achieve binaural loudness balance. The user interface allows users to adjust the volume and switch programs according to their own needs.

6. The method for binaural loudness balancing in an air conduction hearing aid according to claim 2, characterized in that: When in use, the binaural loudness balancing module calculates the loudness of the sound signal based on its amplitude, duration, and other characteristics. It also performs Fourier transform and other analyses on the sound signal to obtain its frequency components and energy distribution. Based on the sound signal's propagation environment and receiving location, it establishes a sound field model to simulate the sound signal's propagation process, facilitating the addition of personalized adjustment strategies for subsequent sound balancing.

7. The binaural loudness balancing method for an air conduction hearing aid according to claim 1, characterized in that: The personalized adjustment module assesses the user's hearing threshold and degree of hearing loss through methods such as hearing tests. Based on the user's hearing threshold and degree of hearing loss, it adjusts the loudness of the binaural hearing aids to achieve a suitable matching effect. According to the user's auditory feedback and environmental changes, it adjusts the loudness of the binaural hearing aids in real time to adapt to different auditory needs. Moreover, during use, it establishes a model of the user's auditory habits and preferences through methods such as machine learning to achieve personalized loudness balance adjustment.

8. The method for binaural loudness balancing in an air conduction hearing aid according to claim 1, characterized in that: The following usage steps are included: Step 1: When using an air conduction hearing aid, the system architecture module first uses a microphone module, audio processing module, binaural loudness balance module, and power amplification module to quickly collect sounds from the external environment. Then, the audio processing module filters, amplifies, and reduces noise in the sound signals collected by the microphone to increase the overall clarity of the collected sound. In addition, the binaural loudness balance module automatically adjusts the volume of the left and right ears according to the user's pre-recorded binaural hearing status to achieve binaural loudness balance and increase overall adaptability. The power amplification module amplifies the processed sound signal and transmits it to the user's ears. The second step: The balance algorithm module can process the internal situation to adjust the air conduction hearing aid. It also assesses the user's hearing threshold and degree of hearing loss based on the user's usage habits. According to the degree of hearing loss, it automatically adjusts the loudness of the sound when the hearing aid is used to achieve the best effect. At the same time, when the user's auditory feedback and environment change during use, it adjusts the sound of the binaural hearing aid in a timely manner to adapt to different auditory needs. During use, machine learning and other methods are used to establish a model of the user's auditory habits and preferences to achieve personalized loudness balance adjustment. The third step is to adjust the hardware parameters of the hearing aid through the hardware design module to achieve loudness balance. This can be done by changing the microphone sensitivity, the power amplifier size, etc., to adjust the loudness of both ears. However, this method requires personalized customization based on the user's ear structure and hearing condition. The software design module algorithm calculates the loudness difference between the two ears, and then the software processes the sound signal to make the loudness received by both ears equal. The adjustment process is simple and low-cost.

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