Hearing Device Personalization via GPS-Tagged Noise Profiles
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Solution Overview
Problem
Hearing devices are not personalized to user preferences in specific sound environments, leading to inadequate noise level adjustment in environments like restaurants or bars, and require clinical optimization that is inefficient and impractical, often 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 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
1Adaptability or versatility
If hearing devices use average noise environment settings optimized for the average listener, then the device can be manufactured and deployed efficiently, but the sound quality and noise filtering are not personalized to user preferences or specific sound environments
Solution Approach 1:
The system performs preliminary actions by having users complete a hearing assessment and environment questionnaire before needing the device. Noise profiles for different environments are pre-calculated and stored in the database, so when a user arrives at a restaurant or bar, the device can quickly retrieve and apply the appropriate settings without requiring complex real-time analysis or clinical intervention.
Solution Approach 2:
The hearing device automatically personalizes settings by retrieving pre-calculated noise profiles from the database based on the user's location or selected environment. The system self-adjusts frequency response, noise filtering, and amplification parameters without requiring the user to manually configure complex settings or visit a clinician, thus achieving personalization while maintaining simplicity.
2Manufacturing precision
If hearing devices require clinical optimization appointments for setting changes, then professional tuning can be achieved, but user convenience and efficiency are significantly reduced
Solution Approach 1:
A database of pre-calculated noise profiles serves as an intermediary between clinical settings and real-world environments. The database stores professionally-tuned noise profiles for various environments (restaurants, bars, concerts) that can be automatically retrieved and applied, eliminating the need for users to schedule clinical appointments while maintaining the precision of professional tuning through the use of pre-calculated settings.
Solution Approach 2:
Noise profiles are pre-calculated and stored in the database before users need them. This preliminary preparation allows the system to instantly retrieve and apply appropriate settings when users enter specific environments, eliminating the time loss associated with scheduling and attending clinical appointments while preserving the precision of professional tuning.
3Ease of operation
If hearing devices use fixed settings for average environments, then device operation is simple, but the devices perform poorly in specific noisy environments like restaurants or bars with divergent frequency and amplitude profiles
Solution Approach 1:
The hearing device transitions from fixed settings to dynamic, environment-specific settings by automatically retrieving and applying pre-calculated noise profiles from the database. The device adapts its frequency response, noise filtering, and amplification parameters based on the user's location or selected environment, maintaining operational simplicity while significantly improving performance reliability in specific noisy environments like restaurants and bars.
Solution Approach 2:
The system changes key parameters including frequency response characteristics, noise filtering thresholds, and amplification levels based on the specific environment. Pre-calculated noise profiles contain optimized parameter sets for different environments (e.g., restaurants with ambient chatter, bars with music and clinking glasses), allowing the device to maintain simple operation while achieving reliable performance through automatic parameter adjustment.
4Loss of information
If users cannot predict sound levels in establishments beforehand, then no advance preparation is needed, but users cannot make informed decisions or adjust hearing devices in advance
Solution Approach 1:
The system performs preliminary measurements of sound levels and noise profiles in various establishments before users need this information. A database is pre-populated with sound level data, frequency spectra, and optimized hearing device settings for different environments. Users can query this database in advance to learn about sound levels at specific establishments and pre-configure their hearing devices, eliminating information loss while avoiding the need for complex real-time measurement infrastructure.
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 the need for frequent clinical visits, while aggregating data for collective noise level awareness and proactive hearing health monitoring.
Implementation Method 1
microphones to detect sound levels
Implementation Method 2
deliver sound to the ears of the user through speakers
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.