Auditory Prosthesis Microphone Degradation Detection
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Solution Overview
Problem
Auditory prosthesis systems face microphone degradation due to environmental contaminants, which can lead to decreased sensitivity and altered frequency response, making it difficult to detect and may affect speech intelligibility, especially in children, and is often imperceptible over time.
Innovation Solution
A sound processor in the auditory prosthesis system continuously monitors the microphone's output signals for specific characteristics, comparing them to a reference signal to detect degradation, and adjusts control parameters or provides notifications when quality falls below an acceptable level.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the microphone is exposed to the environment to detect sound, then the sound detection capability is improved, but the microphone is exposed to environmental contaminants causing degradation
Solution Approach 1:
The system performs preliminary characterization of the microphone's frequency response during manufacturing or initial operation, storing this baseline data for later comparison. This preliminary action enables the system to detect degradation by comparing current performance against the known good state, resolving the contradiction by establishing a reference point before contamination occurs.
Solution Approach 2:
The system continuously monitors the microphone's output signal characteristics and compares them against stored reference values. When degradation is detected through this feedback mechanism, the system can trigger alerts or adjustments. This closed-loop feedback resolves the contradiction by enabling continuous detection of contamination effects while the microphone remains exposed to the environment.
2Ease of operation
If the microphone degradation is not detected, then the system operates without intervention, but speech intelligibility and language development are affected
Solution Approach 1:
The system replaces manual inspection or subjective assessment of microphone performance with automated electronic analysis. The sound processor automatically analyzes frequency response characteristics and compares them against reference data, substituting mechanical/manual verification with electronic measurement and computation. This resolves the contradiction by maintaining ease of operation while ensuring speech intelligibility through automated monitoring.
Solution Approach 2:
The system performs self-diagnosis by automatically monitoring its own microphone's performance and detecting degradation without external intervention. The sound processor analyzes the microphone output and determines when cleaning or replacement is needed, enabling the system to serve itself in monitoring its own health. This resolves the contradiction by maintaining simple operation while ensuring reliability through automated self-monitoring.
3Duration of action of stationary object
If the microphone degradation occurs slowly over time, then the system operates for extended periods, but the degradation becomes imperceptible to users
Solution Approach 1:
The system establishes a baseline frequency response profile during manufacturing or initial operation, storing this reference data for continuous comparison. This preliminary characterization enables the system to detect subtle, gradual changes that would be imperceptible to users. By having the reference data ready in advance, the system can immediately detect degradation trends without requiring user perception or manual testing.
Solution Approach 2:
The system implements continuous feedback monitoring of the microphone's frequency response, automatically comparing current performance against the stored baseline. This continuous feedback loop detects gradual degradation trends that accumulate over extended operational periods, enabling the system to identify problems before they become perceptible to users. The automated comparison resolves the detection difficulty by providing objective, continuous measurement rather than relying on user perception.
Data Source
AI summary
An exemplary system includes a sound processor associated with a patient and a microphone (102). The microphone is configured to detect an audio signal presented to the patient and output an output signal (302) representative of the audio signal. The sound processor is configured to 1) receive the output signal, 2) identify at least one temporal portion of the output signal that has a classification attribute associated with a reference signal, 3) determine (304) a signal characteristic value (306) associated with the at least one temporal portion, 4) determine (308) that a difference (312) between the signal characteristic value associated with the at least one temporal portion and a reference signal characteristic value (310) associated with the reference signal meets a threshold condition, the meeting of the threshold condition indicating that a quality level of the microphone is below an acceptable level and 5) perform a predetermined action associated with the quality level of the microphone.