Hearing Device Voice Biomarker Analysis for Earlier Diagnosis
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Solution Overview
Problem
Conventional diagnosis methods for neurodegenerative disorders are limited to perceptual tests or controlled laboratory setups, leading to late diagnosis and increased treatment costs.
Innovation Solution
A hearing device equipped with a processor, microphone, and biomarker feature analysis capabilities to analyze biomarker features extracted from a user's own voice, enabling early detection of neurodegenerative disorders during general usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If conventional diagnosis methods are used, then diagnosis can be performed with simple equipment, but diagnosis occurs late leading to serious conditions and high treatment costs
Solution Approach 1:
The hearing device performs self-service by continuously monitoring the user's voice characteristics during normal hearing device usage. The processor automatically extracts biomarker features from the user's speech signals and compares them against reference data to detect neurodegenerative disorders, eliminating the need for separate dedicated diagnostic devices or laboratory visits.
Solution Approach 2:
The system performs preliminary action by continuously analyzing voice biomarkers during daily hearing device use, enabling early detection of disease symptoms before they progress to serious stages. The processor monitors changes in speech characteristics over time and triggers alerts when biomarker thresholds indicate potential neurodegenerative conditions, allowing for early intervention.
2Measurement precision
If biomarker feature analysis is applied to own voice content, then early detection of neurodegenerative disorders is enabled, but device complexity increases
Solution Approach 1:
The hearing device achieves universality by integrating multiple functions into a single device: it provides hearing assistance while simultaneously performing biomarker analysis for neurodegenerative disorder detection. The processor leverages the existing audio signal processing capabilities of the hearing device to extract voice biomarkers, eliminating the need for separate diagnostic equipment.
Solution Approach 2:
The hearing device performs self-service by using its own audio processing resources to analyze the user's voice characteristics. The processor extracts biomarker features from the audio signals it already captures for hearing enhancement, and compares these features against stored reference data to detect disease symptoms, all within the existing device architecture.
3Measurement precision
If environmental noise level is determined, then biomarker analysis accuracy is improved, but additional processing steps are required
Solution Approach 1:
The system applies local quality by adapting the biomarker analysis process based on local environmental conditions. When environmental noise levels are determined to be below a threshold, the processor proceeds with full biomarker feature extraction and analysis. This localized adaptation ensures high analysis accuracy in suitable acoustic environments while avoiding unnecessary processing in noisy conditions.
Data Source
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AI summary
An exemplary hearing device configured to be worn by a user includes a microphone and a processor. The microphone detects an audio signal. The processor is configured to determine that the audio signal includes own voice content representative of a voice of the user and determine that an environmental noise level within the audio signal is below a threshold The processor is further configured to apply, based on the environmental noise level being below the threshold, a biomarker feature analysis heuristic to the own voice content.