Hearing Device Acclimatization via Biased User Preference Learning
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Solution Overview
Problem
Conventional hearing devices with automatic acclimatization management fail to account for user preferences, leading to an excessively long acclimatization phase and requiring multiple visits to adjust intensity settings.
Innovation Solution
A hearing device with a biased user preference learning algorithm that adjusts audio processing parameters based on user input, storing target values in non-volatile memory and calculating intermediate values to approximate the target power-on value, prioritizing adjustments towards the target intensity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If automatic acclimatization management is implemented without user preference consideration, then the acclimatization process can be automated, but the acclimatization phase becomes excessively long and does not adapt to individual user needs
Solution Approach 1:
The system implements feedback by continuously monitoring user adjustments to audio processing parameters and using this information to adapt the acclimatization process. The controller detects when users manually adjust parameters and uses these adjustments as feedback signals to accelerate or decelerate the automatic intensity increase, creating a closed-loop system that responds to user behavior.
Solution Approach 2:
The hearing device performs self-adjustment by automatically modifying audio processing parameters based on detected user behavior patterns. The system serves itself by autonomously determining the optimal rate of intensity increase without requiring external intervention from audiologists, while still adapting to individual user preferences through observed adjustment patterns.
2Ease of operation
If the intensity of the hearing device is increased gradually during acclimatization, then user comfort is improved, but the number of specialist visits required increases
Solution Approach 1:
The hearing device autonomously manages the gradual intensity increase that would otherwise require multiple specialist visits. By implementing self-adjustment capabilities, the device maintains user comfort through controlled gradual increases while eliminating the need for repeated professional interventions, allowing the acclimatization process to occur continuously between wear periods.
Solution Approach 2:
The system prepares for future adjustments by pre-planning the acclimatization trajectory based on initial fitting parameters and detected user behavior. The controller anticipates needed adjustments and implements them proactively during periods when the device is not being worn, so that by the time the user returns to the specialist, the device has already been optimized closer to target settings.
3Adaptability or versatility
If user preference learning is implemented without bias towards target values, then the system adapts to user behavior, but the acclimatization process lacks direction and may not reach the desired target intensity
Solution Approach 1:
The system applies asymmetric weighting to user adjustments based on their direction relative to target values. Adjustments that move parameters toward target values are weighted more heavily than those moving away from targets, creating an asymmetric learning process. This asymmetry ensures the system adapts to user behavior while maintaining directional bias toward achieving prescribed target intensities.
Solution Approach 2:
The system dynamically changes the learning parameters and weighting factors based on the current state of acclimatization and detected user behavior patterns. By adjusting the influence of user preferences versus target values at different stages of the process, the system maintains adaptability early on while ensuring convergence to target parameters as acclimatization progresses.
Data Source
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AI summary
Acclimatization of a hearing device user to a hearing device is made more acceptable by automatic acclimatization management. The intensity of the hearing device is increased in the long term, e.g. during several months. The speed of the intensity increase depends on user inputs. A user controls an audio processing parameter (APP), such as volume, with a user control. Each time the user switches the hearing device off and on again, the power-on value (POV) of the audio processing parameter (APP) is changed. The amount of the change depends on which settings for the audio processing parameter (APP) have been selected by the hearing device user and how long the settings have been active. An initial power-on value (iPOV) and a target power-on value (tPOV), which is to be reached at the end (H) of the acclimatization phase, may be programmed by an audiologist.