Arturas Janusauskas

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A new approach to the design of time windows is presented for detection of transient-evoked otoacoustic emissions (TEOAE). The windows are designed with reference to a minimum mean square error criterion involving the correlation properties of the ensemble of responses. Latency information is introduced in the detection process by windowing at different(More)
A new method is presented for the purpose of improving pass/fail separation during transient evoked otoacoustic emission (TEOAE) hearing screening. The method combines signal decomposition in scales using the discrete wavelet transform, non-linear denoising and scale-dependent time windowing. The cross-correlation coefficient between two subaveraged,(More)
This paper presents a new approach for human cataract automatical detection based on ultrasound signal processing. Two signal decomposition techniques, empirical mode decomposition and discrete wavelet transform are used in the presented method. Performance comparison of these two decomposition methods when applied to this specific ultrasound signal is(More)
This paper presents an application of the Hilbert–Huang transform (HHT) and ensemble correlation for detection of the transient evoked otoacoustic emissions (TEOAEs), and high resolution time–frequency mapping. The HHT provides a powerful tool for nonlinear analysis of nonstationary signals such as TEOAEs. Since the HHT itself does not distinguish between(More)
Transient evoked otoacoustic emissions (TEOAEs) have been analyzed for objective assessment of hearing function and monitoring of the influence of noise exposure and ototoxic drugs. This paper presents a novel application of the Hilbert–Huang transform (HHT) for detection and time-frequency mapping of TEOAEs. Since the HHT does not distinguish between(More)
This paper presents a unified approach to multiscale detection of transient evoked otoacoustic emissions (TEOAEs). Using statistical detection theory, it is shown that the optimal detector involves a time windowing operation where the window can be estimated from ensemble correlation information. The detector performs adaptive splitting of the signal into(More)
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