Wavelet time-frequency analysis enhances noise-resilient quantification of corneal wave velocity and natural frequency in optical coherence elastography

In vivo characterization of corneal biomechanics using dynamic optical coherence elastography (OCE) requires accurate quantification of both the temporal and spectral features for transient, frequency-dependent corneal dynamics. However, conventional time-of-flight (TOF) and fast Fourier transform (FFT) methods are limited in resolving coupled time-frequency behaviors, especially under low signal-to-noise ratio (SNR) conditions. We introduce a wavelet-based method for simultaneous characterization of wave propagation and resonant oscillations in air-pulse OCE. A Morlet wavelet transform was employed, with parameters optimized for wave velocity ( F b = 0.2 and F c =1.0) and natural frequency ( F b =5, F c =7). The method was validated against TOF and FFT using agar phantoms, ex vivo porcine corneas (n = 26, IOP: 5–20 mmHg), and an in vivo rabbit model. The wavelet method showed excellent agreement with TOF and FFT under controlled conditions, with mean differences of 0.18 m/s for group velocity (2.3–5.2 m/s) and 0.5 Hz for natural frequency (176–437 Hz) in 1–2% agar phantoms. Critically, it outperformed TOF under challenging conditions, reducing the coefficient of variation by ∼50% (0.27 vs. 0.52) at low-SNR depths and preserving more valid data (86.3% vs. 50.0%) in stressed corneas at 20 mmHg. Its time-frequency localization further enabled the in vivo detection of transient vibrational changes, suggesting the potential to distinguish physiological modulations (e.g., heartbeat, respiration) that are not readily accessible with FFT. This work establishes a robust, noise-tolerant foundation for dynamic corneal elastography, potentially advancing dynamic OCE toward precise, clinically translatable assessment of corneal biomechanics.