Hearing Device Acoustic Path Anomaly Detection
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Solution Overview
Problem
Existing ear-level electronic devices, such as hearing aids, struggle to effectively detect and diagnose acoustic-related anomalies, including blockages and pathologies, which can affect device performance and user health.
Innovation Solution
The implementation of a self-check mechanism in hearing devices using an audio processor circuit to measure the transfer function of the feedback path between the receiver and microphones, comparing it to characterization data to detect anomalies and predict potential faults or otoscopic conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional acoustic anomaly detection methods are used in hearing devices, then device complexity is reduced, but measurement precision and anomaly detection accuracy deteriorate
Solution Approach 1:
The hearing device performs self-diagnosis by automatically measuring its own acoustic transfer functions and comparing them against stored baseline data. The processor circuitry initiates self-check routines that measure feedback paths from receivers to microphones, detecting anomalies without requiring external clinical equipment or professional intervention, thereby achieving high measurement precision while maintaining relatively simple device architecture
Solution Approach 2:
The system detects anomalies by monitoring changes in acoustic transfer function parameters (frequency response, gain, phase) over time. By establishing baseline parameter values during normal operation and detecting deviations from these baselines, the system achieves sensitive anomaly detection through parameter comparison rather than requiring complex absolute measurement systems
2Reliability
If comprehensive acoustic path monitoring is implemented, then reliability of device performance assessment is improved, but loss of time for measurement and processing increases
Solution Approach 1:
The hearing device implements periodic self-check routines that measure acoustic transfer functions at scheduled intervals or triggered by specific events (e.g., user requests, configuration changes). This periodic monitoring approach ensures reliable detection of acoustic path anomalies while minimizing measurement time by conducting checks only when necessary rather than continuously
Solution Approach 2:
Baseline transfer function data is pre-measured and stored during device initialization or manufacturing. This preliminary action creates reference data that enables rapid anomaly detection through simple comparison operations, reducing the time required for ongoing monitoring while maintaining high reliability in assessing acoustic path integrity
3Measurement precision
If detailed feedback path characterization is performed, then measurement precision of acoustic anomalies is improved, but device complexity increases
Solution Approach 1:
The system extracts and measures only the specific acoustic transfer functions that are critical for detecting common anomalies (e.g., feedback path from receiver to microphone). By focusing measurements on these key parameters rather than attempting to characterize the entire acoustic field, the system achieves high measurement precision for relevant anomalies while keeping the measurement and processing complexity manageable
Solution Approach 2:
The system uses the microphone as an intermediary sensor to indirectly measure receiver output characteristics through the acoustic feedback path. Instead of requiring direct measurement of receiver performance, the microphone captures the acoustic signal, allowing the processor to derive transfer function information through signal analysis, thereby achieving detailed characterization with relatively simple sensor requirements
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This solution enables the hearing device to accurately detect anomalies, predict potential faults, and provide user-friendly indications, thereby ensuring optimal device performance and user health.
Implementation Method 1
measuring a transfer function of a feedback path between a receiver of the hearing device to at least one microphone of the hearing device
Data Source
AI summary
A self-check is initiated via an audio processor circuit of the hearing device. In response to the self-check, a transfer function of a feedback path is measured between a receiver of the hearing device to at least one microphone of the hearing device. An anomaly is determined in the transfer function via comparison with example feedback path characterization data. An abnormality associated with the hearing device is predicted based on the anomaly. An indication of the abnormality is presented via a user interface of the hearing device.