Analyzing transient-evoked otoacoustic emissions by concentration of frequency and time

Abstract

The linear part of transient evoked otoacoustic emission (TEOAE) is thought to be generated via coherent reflection near the characteristic place of constituent wave components. Because of the tonotopic organization of the cochlea, high frequency emissions return earlier than low frequencies; however, due to the random nature of coherent reflection, the instantaneous frequency (IF) and amplitude envelope of TEOAEs both fluctuate. Multiple reflection components and synchronized spontaneous emissions can further make it difficult to extract the IF by linear transforms. This paper proposes to model TEOAEs as a sum of intrinsic mode-type functions and analyze it by a nonlinear-type time-frequency (T-F) analysis technique called concentration of frequency and time (ConceFT). When tested with synthetic otoacoustic emission signals with possibly multiple oscillatory components, the present method is able to produce clearly visualized traces of individual components on the T-F plane. Further, when the signal is noisy, the proposed method is compared with existing linear and bilinear methods in its accuracy for estimating the fluctuating IF. Results suggest that ConceFT outperforms the best of these methods in terms of optimal transport distance, reducing the error by 10% to 21% when the signal to noise ratio is 10 dB or below.

Theta Oscillations at Subthalamic Region Predicts Hypomania State After Deep Brain Stimulation in Parkinson's Disease

“…We demonstrated the advantage of conceFT in Figure 1B. Accordingly, we used conceFT to measure the spectral power as this technique can sharpen the spectrum at each moment, capture the non-stationary dynamics, and stabilize the impact of noise (Daubechies et al, 2016;Lin and Wu, 2017;Wu and Liu, 2018). LFP power was determined in four candidate frequency bands, namely, θ (4-7 Hz), α (7-10 Hz), β (13-35 Hz), and γ (40-60 Hz), for every 1 mm point.…”

Denoising Click-evoked Otoacoustic Emission Signals by Optimal Shrinkage

“…Generation of simulated CEOAEs. Following Wu and Liu [52], an electromechanical model of cochlea [26] was adopted to generate CEOAE by simulation. The model was based on a transmission-line model of cochlear mechanics [33,34], and the outer hair cell (OHC) was characterized by a piezo-electrical equivalent circuit [25,31].…”

“…The model was based on a transmission-line model of cochlear mechanics [33,34], and the outer hair cell (OHC) was characterized by a piezo-electrical equivalent circuit [25,31]. As in [52], a term called "roughness" was added to the model by applying perturbation to the mass density along the basilar membrane, and the level of roughness was adjusted so as to cause coherent reflection of the traveling waves at an empirically reasonable level. The roughness influenced both the shape and the level of CEOAE.…”

“…The first challenge can be tackled by modern time-frequency (T-F) analysis techniques [3]. For instance, the continuous wavelet transform (CWT) was applied for visualizing the composition and frequency variation of CEOAEs [35,46], and a modern T-F analysis tool called concentration of frequency and time (ConceFT) can enhance the clarity of CEOAE traces on the T-F plane [52].…”

Improve concentration of frequency and time (ConceFT) by novel complex spherical designs

“…In other words, for each x, we have a new window h [x] := we average all TFR's by SST with those windows. While the ConceFT has been applied to a variety of medical signal processing problems [9,15,16], for the clinical application purpose, there is still a gap. In fact, due the step of random samples from S J−1 , the analysis result varies from one experiment to another and leads to an un-reproducibility issue unless a large number of sampling points are considered.…”