Hierarchical Sound Classification in Hearing Prostheses
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Solution Overview
Problem
Individuals with sensorineural hearing loss, who have residual hearing, often do not benefit sufficiently from auditory prostheses that generate mechanical motion of the cochlea fluid, and there is a need for a more effective method to classify and adapt to varying sound environments to improve hearing outcomes.
Innovation Solution
A hearing prosthesis system that receives sound signals, determines a primary classification, and generates a hierarchical classification of the sound environment, including nested classifications, to deliver targeted stimulation, using input elements, processors, and memory to convert and process sound signals effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If auditory prostheses generate mechanical motion of the cochlea fluid, then conductive hearing loss is addressed, but sensorineural hearing loss does not benefit sufficiently
Solution Approach 1:
The prosthesis dynamically adapts its operation mode based on the detected hearing loss type. The system transitions between mechanical motion generation for conductive hearing loss and electrical/optical nerve stimulation for sensorineural hearing loss, making the device versatile across different hearing impairment conditions while maintaining effective treatment for each type
Solution Approach 2:
The prosthesis changes its operational parameters based on the type of hearing loss detected. For conductive hearing loss, it uses mechanical parameters (cochlea fluid motion), while for sensorineural hearing loss, it switches to electrical or optical parameters (nerve cell stimulation), thereby adapting to different physiological conditions
2Adaptability or versatility
If simple sound processing is used, then device complexity is reduced, but adaptability to varying sound environments deteriorates
Solution Approach 1:
The sound environment classification is segmented into hierarchical levels: primary classifications (e.g., quiet, noisy, reverberant) and secondary classifications (more specific sub-categories). This segmentation allows the system to adapt to varying sound environments effectively while managing complexity through a structured, multi-level approach rather than a single complex classification system
Solution Approach 2:
The system adds a hierarchical dimension to sound environment classification by introducing secondary classifications that are derivative of primary classifications. This dimensional expansion enables more nuanced adaptation to sound environments without requiring a completely complex re design, as the hierarchy builds upon itself in an organized manner
Data Source
AI summary
Presented herein are techniques for generating a hierarchical classification of a set of sound signals received at hearing prosthesis. The hierarchical classification includes a plurality of nested classifications of a sound environment associated with the set of sound signals received at hearing prosthesis, including a primary classification and one or more secondary classifications that each represent different characteristics of the sound environment. The primary classification represents a basic categorization of the sound environment, while the secondary classifications define sub-categories/refinements of the associated primary classification and/or other secondary classifications.