Obtaining reliable phase-gradient delays from otoacoustic emission data.

Area of Science:

• Auditory Neuroscience
• Biomedical Engineering
• Signal Processing

Background:

• Reflection-source otoacoustic emissions (OAEs) provide noninvasive estimates of cochlear function.
• Phase-gradient delays from OAEs are crucial for assessing cochlear tuning.
• Existing data-processing strategies yield variable delay estimates, necessitating reliability assessment.

Purpose of the Study:

• To evaluate the reliability of six different methods for extracting delay trends from OAEs.
• To compare established and novel signal-processing strategies for OAE delay analysis.
• To develop methods for separating direct OAEs from reflections to improve interpretation.

Main Methods:

• In silico experiments were conducted to assess six OAE delay extraction methods.
• Methods evaluated include phase smoothing, energy-weighting, SNR-based exclusion, peak-picking, and all-pass factorization.
• Novel strategies using continuous wavelet transform and cepstral analysis were developed to address standing waves.

Main Results:

• The peak-picking method demonstrated good performance in extracting OAE delay trends.
• Phase smoothing was found to introduce significant bias and is not recommended.
• Continuous wavelet transform and cepstral analysis effectively separated direct OAEs from reflections.

Conclusions:

• The findings help resolve discrepancies regarding the frequency dependence of human OAE delays.
• The study provides reliable analysis methods for future research on cochlear tuning and function.
• Specific methods are recommended for accurate OAE delay analysis, improving noninvasive audiological assessments.