Adaptive Hearing Evaluation Using Population Models
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current hearing ability evaluation methods are time-consuming and uncomfortable for individuals, requiring a large number of hearing evaluation events to accurately determine hearing thresholds, which can be burdensome for both the person being tested and the audiologist.
Innovation Solution
A method and system that utilize a representation of the distribution of hearing ability for a population to establish a hearing ability model by optimizing the stimulus sequence and response observation, allowing for a faster and more accurate estimation of hearing thresholds with fewer evaluation events, using a probabilistic model to update and refine the hearing ability model based on responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional manual or automatic audiometry methods are used to accurately determine hearing thresholds, then measurement precision is improved, but the duration of the testing procedure increases significantly
Solution Approach 1:
The system performs preliminary actions by establishing a population-based hearing ability model before individual testing. This pre-computed model contains statistical information about hearing ability distributions across populations, which is then used to guide and optimize the individual testing process, reducing the number of evaluation events needed
Solution Approach 2:
The system implements feedback by continuously updating the hearing ability model based on observed responses during testing. Each response provides information that refines the model, allowing the system to adaptively determine when sufficient accuracy has been achieved and when to terminate testing, thereby reducing overall testing duration
2Measurement precision
If a large number of hearing evaluation events are conducted to ensure accurate hearing ability modeling, then measurement precision is improved, but the discomfort and burden on the tested individual increases
Solution Approach 1:
The system applies partial action by determining when sufficient hearing ability information has been obtained without requiring complete exhaustive testing. By using population-based models and adaptive updating, the system achieves adequate precision with fewer than the traditional maximum number of evaluation events, reducing discomfort while maintaining acceptable accuracy
3Productivity
If population-based statistical models are used to guide individual hearing evaluation, then productivity is improved by reducing the number of required evaluation events, but device complexity increases due to the probabilistic modeling system
Solution Approach 1:
The population-based hearing ability model serves as an intermediary between the large population dataset and the individual testing process. This intermediary model pre-processes population information into usable statistical forms, simplifying the individual evaluation task while maintaining productivity benefits without requiring direct complex population analysis during testing
Data Source
AI summary
A system for establishing a hearing ability model of a hearing ability of a person, includes a data storage configured to store a representation of a distribution of a hearing ability of a population of individuals, and a processor configured to establish a hearing ability model representing a hearing ability of the person based at least in part on (i) information regarding a person's response to a stimulus of a hearing evaluation event, and (ii) the representation of the distribution of the hearing ability of the population.