Cochlear Implant Neural Network Audio Environment Adaptation
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Solution Overview
Problem
Current cochlear implant systems lack user control and customization, often requiring visits to audiologists for adjustments and relying on external components, which can be inconvenient and ineffective in managing ambient noise.
Innovation Solution
A cochlear implant system utilizing a neural network and mobile application to recognize audio environments and automatically adjust settings, providing users with fine-grained control over their hearing experience through advanced filtering and scene recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If cochlear implant systems rely on external components and require audiologist visits for adjustments, then device functionality is maintained, but user convenience and ease of operation deteriorate
Solution Approach 1:
The system enables users to independently control and customize their hearing experience through a mobile application. Users can select from pre-configured filter settings optimized for different environments (quiet, noisy, speech, music) without requiring audiologist visits. The mobile app provides self-service functionality that was previously only available through professional adjustments.
Solution Approach 2:
The mobile application serves multiple functions: it acts as a remote control for the cochlear implant, provides environmental scene recognition, selects appropriate filter configurations, and transmits settings wirelessly. This consolidates what would otherwise require separate external components and professional visits into a single universal interface.
2Adaptability or versatility
If cochlear implant systems use fixed settings, then device complexity is reduced, but adaptability to different environments deteriorates
Solution Approach 1:
Multiple filter configurations are pre-configured and stored in the system, each optimized for specific environmental conditions (quiet, noisy, speech, music). The scene recognition algorithm compares real-time environmental characteristics against these pre-defined templates to rapidly select the most appropriate filter setting, avoiding the need for complex real-time optimization algorithms.
Solution Approach 2:
The system dynamically adapts to changing environmental conditions by continuously monitoring audio characteristics and automatically switching between different pre-configured filter settings. This provides environmental adaptability while maintaining manageable complexity through the use of discrete, pre-optimized configurations rather than continuous parameter adjustment.
3Measurement precision
If audiologist visits are required for setting adjustments, then measurement precision is maintained, but loss of time increases
Solution Approach 1:
The system incorporates user feedback mechanisms where users can rate their hearing experience and provide input about environmental conditions. This feedback loop allows the system to learn and refine filter selections over time, maintaining measurement precision through iterative improvement rather than requiring repeated professional visits for adjustments.
Data Source
AI summary
Systems and methods for improved control and performance of cochlear implants are disclosed. In an embodiment, the audio environment is sampled, and a neural network determines suggested filter setting for the cochlear implant. The process is repeated such that, as the user moves through various audio environments having differing noise levels, satisfactory performance of the cochlear implant is maintained for the user.