Auditory Device Optimization System for Real-Time Parameter Adaptation
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Solution Overview
Problem
Existing audiological devices, such as cochlear implants and hearing aids, face challenges in optimizing a large number of parameters to accommodate individual hearing needs and varying auditory environments, due to the complexity of audio signals and unique factors like signal-to-noise issues and threshold hearing variances.
Innovation Solution
An optimization system comprising three modules: the first module collects and analyzes patient feedback to determine parameter ranges, the second module allows patients to select preferred parameter settings through user interfaces, and the third module uses a database of sound profiles and classifier algorithms to automatically adjust device settings based on environmental sounds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the number of parameters for audio signal processing is increased to accommodate individual hearing needs and varying environments, then the adaptability and performance of the auditory device is improved, but the device complexity and difficulty of optimization increases
Solution Approach 1:
The system employs automated algorithms that independently analyze patient feedback and environmental sounds to determine optimal parameter settings, eliminating the need for manual optimization by operators and enabling the device to self-adjust to individual hearing needs
Solution Approach 2:
The system dynamically adjusts multiple audio processing parameters including gain, compression, noise reduction, and directional microphone settings based on real-time analysis of patient responses and environmental acoustic conditions, allowing adaptability without manual intervention
2Measurement precision
If manual optimization of multiple parameters is performed to tailor device settings to individual patients, then the customization and performance are improved, but the time and expertise required increases
Solution Approach 1:
The system performs preliminary automated analysis of patient feedback during initial fitting sessions to establish baseline parameter ranges, and continuously refines settings based on ongoing patient responses, significantly reducing the time and expertise needed compared to traditional manual optimization processes
Solution Approach 2:
The system incorporates real-time feedback from patient responses to automatically adjust parameters, using iterative optimization based on measured hearing thresholds and patient preferences to achieve precise customization without requiring extensive manual intervention
3Productivity
If automated algorithms are used to transform acoustic waves into electrical signals for cochlear implant stimulation, then the processing speed and consistency are improved, but the ability to capture subtle auditory nuances decreases
Solution Approach 1:
The system dynamically adjusts processing parameters including window lengths, filter banks, and pulse timing based on the temporal and spectral characteristics of the input signal, allowing fast processing while preserving important auditory information through adaptive signal analysis
Data Source
AI summary
A system comprises an auditory device processor, an auditory device output mechanism, an auditory input sensor, a database including a reference bank of environmental sounds and corresponding sound profiles, and a memory. The auditory device processor is configured to: while the auditory input sensor is detecting a first environmental sound, receive a sound selection from the user, wherein the sound selection is associated with the first environmental sound; store a first sound profile in the reference bank corresponding to the first environmental sound; receive a second environmental sound detected by the auditory input sensor; analyze a frequency content of the second environmental sound; compare the frequency content of the second environmental sound with the reference bank of environmental sounds and corresponding sound profiles stored in the database; in response to the comparison, select one of the sound profiles corresponding to the second environmental sound; and automatically adjust the parameter settings.