Biomedical subjects

Roger P Hamernik

Publications and source records attributed to Roger P Hamernik.

8 recordsLinked to original sources

PubMed2006

Real-time data-reusing adaptive learning of a radial basis function network for tracking evoked potentials.

Tracking variations in both the latency and amplitude of evoked potential (EP) is important in quantifying properties of the nervous system. Adaptive filtering is a powerful tool for tracking such variations. In this paper, a data-reusing non-linear adaptive filtering method, based on a radial basis function network (RBFN), is implemented to estimate EP. The RBFN consists of an input layer of source nodes, a single hidden layer of non-linear processing units and an output layer of linear weights. It has built-in nonlinear activation functions that allow learning of function mappings. Moreover, it produces satisfactory estimates of signals against a background noise without a priori knowledge of the signal, provided that the signal and noise are independent. In clinical situations where EP responses change rapidly, the convergence rate of the algorithm becomes a critical factor. A carefully designed data-reusing RBFN can accelerate the convergence rate markedly and, thus, enhance its performance. Both theoretical analysis and simulation results support the improved performance of our new algorithm.

Adolescent↗

PubMed2006

The kurtosis metric as an adjunct to energy in the prediction of trauma from continuous, nonGaussian noise exposures.

Data from an earlier study [Hamernik et al. (2003). J. Acoust. Soc. Am. 114, 386-395] were consistent in showing that, for equivalent energy [Leq= 100 dB(A)] and spectra, exposure to a continuous, nonGaussian (nonG) noise could produce substantially greater hearing and sensory cell loss in the chinchilla model than a Gaussian (G) noise exposure and that the statistical metric, kurtosis, computed on the amplitude distribution of the noise could order the extent of the trauma. This paper extends these results to Leq= 90 and 110 dB(A), and to nonG noises that are generated using broadband noise bursts, and band limited impacts within a continuous G background noise. Data from nine new experimental groups with 11 or 12 chinchillas/group is presented. Evoked response audiometry established hearing thresholds and surface preparation histology quantified sensory cell loss. At the lowest level [Leq=90 dB(A)] there were no differences in the trauma produced by G and nonG exposures. For Leq >90 dB(A) nonG exposures produced increased trauma relative to equivalent G exposures. Removing energy from the impacts by limiting their bandwidth reduced trauma. The use of noise bursts to produce the nonG noise instead of impacts also reduced the amount of trauma.

Animals↗

PubMed2005

Sensitivity of distortion product otoacoustic emissions in noise-exposed chinchillas.

The present study investigates the effect of small amounts of outer hair cell (OHC) loss on distortion product otoacoustic emission (DPOAE) levels and evoked potential permanent threshold shifts (PTS) in a population of 12 noise-exposed chinchillas. The group mean DPOAE level, which decreased by up to approximately 15 dB in the presence of less than 8 dB PTS and 15% OHC loss, indicates that DPOAEs can detect an underlying cochlear pathology (i,e., OHC damage/loss) despite the presence of normal to near normal thresholds. The sensitivity of DPOAEs in detecting OHC loss makes this test measure suited for diagnosing sensorineural hearing impairment, particularly when abnormal auditory symptoms (i.e., speech discrimination problems) are associated with a normal audiogram in the clinical setting and as part of a hearing conservation program.

Animals↗

PubMed2004

The use of distortion product otoacoustic emissions in the estimation of hearing and sensory cell loss in noise-damaged cochleas.

Distortion product otoacoustic emissions (DPOAE), permanent threshold shifts (PTS) and outer hair cell (OHC) losses were analyzed in a population of 187 noise-exposed chinchillas to determine the predictive accuracy (sensitivity and specificity) of the DPOAE for PTS and OHC loss. Auditory evoked potentials (AEP) recorded from the inferior colliculus of the brainstem were used to estimate hearing thresholds and surface preparation histology was used to determine sensory cell loss. The overlapping cumulative distributions and high variability in emission responses for both PTS and OHC loss made it difficult to predict AEP threshold and OHC loss from DPOAE level measurements alone. Using a strict criterion (i.e. emissions better than the 5th percentile of the preexposure DPOAE level, and PTS< or = 5 dB or OHC loss< or = 5%), it was found that the postexposure DPOAE level could be used with reasonable confidence to determine if the status of peripheral auditory system was either normal (i.e. PTS< or = 5 dB) or abnormal (PTS>30 dB or OHC loss>40%). However, the high variability of individual DPOAE responses resulted in a broad region of 'uncertainty' (i.e. 5 or = 50%) or PTS (> or = 35 dB) in noise-exposed chinchillas. Based on an exponential regression analysis of individual subjects, correlations were higher for PTS/DPOAE than for OHC loss/DPOAE.

Animals↗

PubMed2003

Cochlear toughening, protection, and potentiation of noise-induced trauma by non-Gaussian noise.

An interrupted noise exposure of sufficient intensity, presented on a daily repeating cycle, produces a threshold shift (TS) following the first day of exposure. TSs measured on subsequent days of the exposure sequence have been shown to decrease relative to the initial TS. This reduction of TS, despite the continuing daily exposure regime, has been called a cochlear toughening effect and the exposures referred to as toughening exposures. Four groups of chinchillas were exposed to one of four different noises presented on an interrupted (6 h/day for 20 days) or noninterrupted (24 h/day for 5 days) schedule. The exposures had equivalent total energy, an overall level of 100 dB(A) SPL, and approximately the same flat, broadband long-term spectrum. The noises differed primarily in their temporal structures; two were Gaussian and two were non-Gausssian, nonstationary. Brainstem auditory evoked potentials were used to estimate hearing thresholds and surface preparation histology was used to determine sensory cell loss. The experimental results presented here show that: (1) Exposures to interrupted high-level, non-Gaussian signals produce a toughening effect comparable to that produced by an equivalent interrupted Gaussian noise. (2) Toughening, whether produced by Gaussian or non-Gaussian noise, results in reduced trauma compared to the equivalent uninterrupted noise, and (3) that both continuous and interrupted non-Gaussian exposures produce more trauma than do energy and spectrally equivalent Gaussian noises. Over the course of the 20-day exposure, the pattern of TS following each day's exposure could exhibit a variety of configurations. These results do not support the equal energy hypothesis as a unifying principal for estimating the potential of a noise exposure to produce hearing loss.

Animals↗

PubMed2003

The effects of the amplitude distribution of equal energy exposures on noise-induced hearing loss: the kurtosis metric.

Seventeen groups of chinchillas with 11 to 16 animals/group (sigmaN = 207) were exposed for 5 days to either a Gaussian (G) noise or 1 of 16 different non-Gaussian (non-G) noises at 100 dB(A) SPL. All exposures had the same total energy and approximately the same flat spectrum but their statistical properties were varied to yield a series of exposure conditions that varied across a continuum from G through various non-G conditions to pure impact noise exposures. The non-G character of the noise was produced by inserting high level transients (impacts or noise bursts) into the otherwise G noise. The peak SPL of the transients, their bandwidth, and the intertransient intervals were varied, as was the rms level of the G noise. The statistical metric, kurtosis (beta), computed on the unfiltered noise beta(t), was varied 3 < or = beta(t) < or = 105. Brainstem auditory evoked responses were used to estimate hearing thresholds and surface preparation histology was used to determine sensory cell loss. Trauma, as measured by asymptotic and permanent threshold shifts (ATS, PTS) and by sensory cell loss, was greater for all of the non-G exposure conditions. Permanent effects of the exposures increased as beta(t) increased and reached an asymptote at beta(t) approximately 40. For beta(t) > 40 varying the interval or peak histograms did not alter the level of trauma, suggesting that, in the chinchilla model, for beta(t) > 40 an energy metric may be effective in evaluating the potential of non-G noise environments to produce hearing loss. Reducing the probability of a transient occurring could reduce the permanent effects of the non-G exposures. These results lend support to those standards documents that use an energy metric for gauging the hazard of exposure but only after applying a "correction factor" when high level transients are present. Computing beta on the filtered noise signal [beta(f)] provides a frequency specific metric for the non-G noises that is correlated with the additional frequency specific outer hair cell loss produced by the non-G noise. The data from the abundant and varied exposure conditions show that the kurtosis of the amplitude distribution of a noise environment is an important variable in determining the hazards to hearing posed by non-Gaussian noise environments.

Acoustic Stimulation↗

PubMed2002

Adaptive filtering of evoked potentials with radial-basis-function neural network prefilter.

Evoked potentials (EPs) are time-varying signals typically buried in relatively large background noise. To extract the EP more effectively from noise, we had previously developed an approach using an adaptive signal enhancer (ASE) (Chen et al., 1995). ASE requires a proper reference input signal for its optimal performance. Ensemble- and moving window-averages were formerly used with good results. In this paper, we present a new method to provide even more effective reference inputs for the ASE. Specifically, a Gaussian radial basis function neural network (RBFNN) was used to preprocess raw EP signals before serving as the reference input. Since the RBFNN has built-in nonlinear activation functions that enable it to closely fit any function mapping, the output of RBFNN can effectively track the signal variations of EP. Results confirmed the superior performance of ASE with RBFNN over the previous method.

Algorithms↗

PubMed2002

Relations among early postexposure noise-induced threshold shifts and permanent threshold shifts in the chinchilla.

Threshold shifts (TS) were measured at various times following a wide variety of noise exposures on over 900 chinchillas. An analysis of postexposure TS measures and noise-induced permanent threshold shift (PTS) showed that, across audiometric test frequency, there was a consistent relation between these variables of the form PTS (dB) = alpha(e(TS/beta) - 1), where, for a given test frequency, alpha (dB) and beta (dB) are constants. TSs were measured immediately following exposure (TS0), 24 h after exposure (TS24), and at several intermediate times in order to estimate the maximum TS (TSmax). Correlation between TS and PTS at the various test frequencies was highest for TS24. An analysis of the 90th-percentile PTS showed a linear growth of PTS with TS24 of approximately 0.7 dB PTS/dB TS24. These data provide some support, in the chinchilla model, for a variation of the three postulates originally presented by Kryter et al. [J. Acoust. Soc. Am. 39, 451 (1966)]. Specifically: (i) TS24 is a consistent measure of the effects of a traumatic noise exposure. (ii) All exposures that produce a given TS24 will be equally hazardous. (iii) Noise-induced PTS in the most susceptible animals, following many years of exposure, is approximately equal to (0.7)TS24 measured after an 8-h exposure to the same noise.

Animals↗