Hearing Aid Dynamic Learning Time Adaptation
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Solution Overview
Problem
Existing hearing devices struggle to adjust parameters effectively to individual user preferences across multiple hearing programs, leading to inconsistent learning times that may result in either too rapid or too slow adaptation, as they are typically configured based on assumed usage patterns rather than actual usage data.
Innovation Solution
A method and device that record data on hearing device settings along with temporal information to determine active usage periods, allowing for automatic adaptation of parameters based on individual usage times, enabling faster learning for rarely used programs and slower learning for frequently used ones, with continuous adaptation of parameters such as time constants and filter algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a fixed learning time is used for all hearing programs, then the device complexity is reduced and ease of operation is improved, but the adaptability to individual usage patterns deteriorates
Solution Approach 1:
The patent implements dynamic learning times that automatically adjust based on actual usage data. Instead of fixed predetermined time constants, the system continuously adapts the learning duration for each hearing program according to how long the user actually uses each program, enabling the device to optimize itself without user intervention
Solution Approach 2:
The hearing device performs self-adjustment by automatically recording its own usage data and using this information to adapt learning times for different programs. The system monitors which programs are used most frequently and longest, then automatically configures appropriate learning times without requiring external configuration or user input
2Productivity
If learning progresses rapidly for all programs, then productivity is improved, but the reliability of identifying user wishes deteriorates due to insufficient learning data
Solution Approach 1:
The system dynamically adjusts learning speed based on program usage frequency. Frequently used programs receive longer learning periods to ensure reliable data collection, while rarely used programs have shorter learning times. This dynamic adaptation allows rapid learning where needed while maintaining data reliability
Solution Approach 2:
Different learning time constants are applied to different hearing programs based on their individual usage characteristics. Instead of a uniform learning rate, each program receives a customized learning duration proportional to its importance and usage frequency, optimizing both speed and reliability for each specific program
3Reliability
If learning progresses slowly for all programs, then the reliability of identifying user wishes is improved, but the productivity and user satisfaction deteriorate due to extended learning periods
Solution Approach 1:
The system implements dynamic learning time adjustment where the learning duration for each program is automatically optimized based on actual usage patterns. Programs that are used frequently and for long durations receive extended learning periods to ensure reliability, while programs used rarely or briefly have shorter learning times, maximizing overall productivity
Data Source
AI summary
A method for adjusting a hearing device, in particular a hearing aid, to an individual user, includes firstly recording data relating to at least one setting of the hearing device together with direct or indirect temporal information. Thereupon, a period of time during which the at least one setting was/is active is automatically determined. Finally, at least one parameter of the hearing device is automatically adapted as a function of the determined period of time and the at least one setting. This affords the possibility of adapting, for example, time constants according to individual usage. A corresponding hearing device is also provided.