Hearing Aid Personalization via Mobile Noise Profiling
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Solution Overview
Problem
Hearing devices are not personalized to user preferences in specific sound environments, leading to inadequate noise management in varying noise levels, and clinicians cannot efficiently adjust settings remotely, resulting in situational hearing problems and potential hearing loss.
Innovation Solution
A system that uses a hearing device and a mobile device wirelessly linked via Bluetooth, with integrated microphones to detect sound levels, create a database of noise profiles, and allow users to adjust settings manually or automatically based on GPS-tagged data, enabling real-time optimization and remote clinician adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If hearing devices use average listener settings optimized for typical noise environments, then device complexity is reduced and ease of manufacture is improved, but adaptability to specific sound environments and user preferences deteriorates
Solution Approach 1:
The hearing device dynamically adjusts audio settings based on real-time environment detection and user feedback. The system transitions from static average settings to adaptive personalized settings by continuously monitoring sound levels and user responses, allowing the device to optimize performance for specific environments rather than relying on fixed manufacturer defaults
Solution Approach 2:
The system enables users to self-adjust hearing device settings through mobile device integration and feedback mechanisms. Users can provide real-time feedback about their hearing experience in specific environments, and the system automatically adjusts settings or allows manual customization, eliminating the need for frequent clinic visits while maintaining high adaptability
2Adaptability or versatility
If hearing devices are personalized to specific sound environments and user preferences, then adaptability and sound quality are improved, but device complexity and data processing requirements increase
Solution Approach 1:
A mobile device acts as an intermediary between the hearing device and the user, handling complex data processing, environment analysis, and settings optimization. The hearing device itself remains relatively simple, while the mobile device performs the computationally intensive tasks of analyzing sound environments, processing user feedback, and generating personalized audio profiles, thereby distributing complexity across the system rather than concentrating it in the hearing device
Solution Approach 2:
The system adds the dimension of remote computing and cloud-based processing to the hearing device ecosystem. By moving complex algorithms and data processing to the mobile device and potentially cloud services, the system achieves high adaptability without significantly increasing the complexity of the implanted or wearable hearing device itself
3Measurement precision
If clinicians adjust hearing device settings in-office only, then measurement precision and personalized fitting are improved, but loss of time and user convenience deteriorate
Solution Approach 1:
The system implements continuous feedback loops where users report their hearing experience in real-world environments, and the system uses this feedback to automatically adjust settings or alert clinicians for optimization. This allows precision measurement and personalization to occur continuously in the user's natural environment rather than only during periodic clinic visits, significantly reducing time loss while maintaining or improving measurement accuracy through real-world data
4Device complexity
If hearing devices lack environment-specific optimization, then device complexity is reduced, but hearing performance in noisy environments and user satisfaction deteriorate
Solution Approach 1:
The system performs preliminary analysis of sound environments using mobile device microphones and sensors before the user enters noisy environments. By pre-characterizing the acoustic environment and pre-adjusting hearing device settings accordingly, the system ensures optimal hearing performance in challenging acoustic conditions without requiring complex real-time adjustment mechanisms during the actual noisy event
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables personalized sound delivery tailored to specific environments, reducing noise-related hearing issues and allowing for efficient remote tuning, thereby preventing hearing loss and improving user experience.
Implementation Method 1
A personalized hearing profile is generated for an ear-level device comprising a memory, microphone, speaker and processor
Implementation Method 2
A position on the frame of reference is determined in response to user interaction with the user interface, and certain sound profile data associated with the position. Certain data is transmitted to the ear level device. Sound can be generated through the speaker based upon the audio stream data
Data Source
AI summary
Various systems and methods are disclosed herein to increase the quality of the sound delivered to a user and allow personalization to optimize listening performance and comfort under atypical listening conditions, environment specific adjustment, and data capture to assist in the personalization of the system to the user's needs and preferences. Features disclosed include sound level rating systems that aggregate noise data detected by user's mobile phones or hearing devices to provide a database of real-time noise levels. Additionally, a user's sound settings may be saved in the system by location so that they may be recalled when re-entering a specific location. A remote clinician may tune a hearing device, or a user can tune the device using a pre-recorded audio sample. Also, a user may replay the last X seconds of audio recorded by their hearing device.