Several adaptive filters were investigated to enhance speech auditory brainstem responses (speech ABR). The objective was to shorten the long recording time currently needed by the standard coherent averaging method to obtain acceptable performance, which has limited the clinical adoption of speech ABR. Five algorithms were implemented: Wiener Filter (WF), Steepest Descent (SD), Adaptive Noise Cancellation (ANC) based on Least-Mean-Square error (LMS) and normalized LMS error (nLMS), and a multi-adaptive cascade combination of SD and LMS. The performance of the adaptive filters was assessed on speech ABR data gathered from several subjects and compared with coherent averaging using the overall Signal-to-Noise Ratio (SNR), the local SNR around the fundamental frequency and the first formant, and Mean-Square-Error (MSE) in the time and frequency domains. The adaptive filters could reduce the time needed, by at least one order of magnitude, for obtaining comparable signal quality as that obtained with coherent averaging.

Several adaptive filters were investigated to enhance speech auditory brainstem responses (speech ABR). The objective was to shorten the long recording time currently needed by the standard coherent averaging method to obtain acceptable performance, which has limited the clinical adoption of speech ABR. Five algorithms were implemented: Wiener Filter (WF), Steepest Descent (SD), Adaptive Noise Cancellation (ANC) based on Least-Mean-Square error (LMS) and normalized LMS error (nLMS), and a multi-adaptive cascade combination of SD and LMS. The performance of the adaptive filters was assessed on speech ABR data gathered from several subjects and compared with coherent averaging using the overall Signal-to-Noise Ratio (SNR), the local SNR around the fundamental frequency and the first formant, and Mean-Square-Error (MSE) in the time and frequency domains. The adaptive filters could reduce the time needed, by at least one order of magnitude, for obtaining comparable signal quality as that obtained with coherent averaging.

Several adaptive filters were investigated to enhance speech auditory brainstem responses (speech ABR). The objective was to shorten the long recording time currently needed by the standard coherent averaging method to obtain acceptable performance, which has limited the clinical adoption of speech ABR. Five algorithms were implemented: Wiener Filter (WF), Steepest Descent (SD), Adaptive Noise Cancellation (ANC) based on Least-Mean-Square error (LMS) and normalized LMS error (nLMS), and a multi-adaptive cascade combination of SD and LMS. The performance of the adaptive filters was assessed on speech ABR data gathered from several subjects and compared with coherent averaging using the overall Signal-to-Noise Ratio (SNR), the local SNR around the fundamental frequency and the first formant, and Mean-Square-Error (MSE) in the time and frequency domains. The adaptive filters could reduce the time needed, by at least one order of magnitude, for obtaining comparable signal quality as that obtained with coherent averaging.

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Maternal iron deficiency is a world wide and major public health issue. Despite recent researchers’ interest related to this topic, its impact in the offspring still remains unclear. The aim of this study is to understand the impact of maternal iron deficiency on the auditory functions and serum cortisol levels in the young and adult guinea pig at post-natal day (PNd) 24 and PNd84, respectively. Pregnant guinea pigs were given an iron deficient (ID) or iron sufficient (IS) diet during gestation and lactation. An iron sufficient diet was provided to all pups after weaning day. No significant difference was observed in the hearing threshold and latencies in siblings from both groups at PNd24 and PNd84. However, ID offspring showed a significant higher interpeak latency I-IV at 100 dB than IS pups at PNd24. ID offspring also had significant elevated cortisol levels at PNd24 compared to IS control group. Maternal iron deficiency affects negatively the auditory functions and raises the serum cortisol levels, a biomarker of stress in the offspring.

Maternal iron deficiency is a world wide and major public health issue. Despite recent researchers’ interest related to this topic, its impact in the offspring still remains unclear. The aim of this study is to understand the impact of maternal iron deficiency on the auditory functions and serum cortisol levels in the young and adult guinea pig at post-natal day (PNd) 24 and PNd84, respectively. Pregnant guinea pigs were given an iron deficient (ID) or iron sufficient (IS) diet during gestation and lactation. An iron sufficient diet was provided to all pups after weaning day. No significant difference was observed in the hearing threshold and latencies in siblings from both groups at PNd24 and PNd84. However, ID offspring showed a significant higher interpeak latency I-IV at 100 dB than IS pups at PNd24. ID offspring also had significant elevated cortisol levels at PNd24 compared to IS control group. Maternal iron deficiency affects negatively the auditory functions and raises the serum cortisol levels, a biomarker of stress in the offspring.

The primary objective of the project was to survey recognized “experts” in the field of neurodiagnostic audiology and practicing audiologists regarding their referral criteria and referral patterns for administering an auditory brainstem response test (ABR). For purposes of this study, “expert” was defined as any recognized audiologist with at least two or more publications and/or seminars in the field of auditory evoked potentials. Responses of experts and practicing audiologists were compared and contrasted to establish: a) if there was a standard referral pattern; b) what, if any, were the apparent critical components of referral patterns; and, c) whether or not current practice reflected the utilization of such critical components. The survey was designed to establish whether the respondent was practicing, in what type of practice setting, and how often ABRs were performed. Specificity and sensitivity of ABR outcomes was also requested. The survey was administered verbally, via telephone, to 3 experts and was sent via e-mail to 178 randomly selected audiologists in the United States. Of the latter 53 returned, 38 reported conducting ABRs. Thus, data analysis was reported on 38 respondents. The survey results did not reveal a consistent standard referral pattern. Critical components for referral were hypothesized based on the “expert” majority response. These include ABR referral based on the presence of: (1) asymmetric sensorineural hearing loss; (2) unilateral tinnitus; (3) positive reflex decay; and, (4) word recognition rollover. The majority of “non-expert” practitioners surveyed reported that these symptoms warranted consideration for referral, thus reflecting utilization of apparent critical components.

Autistic people frequently experience sensory processing difficulties. For many on the autism spectrum, such difficulties can significantly impact important functions and quality of life. We are only beginning to understand the neural mechanisms of atypical sensory processing. However, one established way to measure certain levels of auditory processing is with auditory brainstem responses (ABR). While ABR has been primarily hypothesized in the current literature as a means of early detection/diagnosis in autism, additional research is needed to determine the ABR’s utility in examining sensory processing in this population. Thus, we evaluated ABR in 19 young children with autism during various stimulus (click and tone burst) and intensity conditions by comparing ABR waveform characteristics, such as absolute peak latencies and amplitudes, inter-peak latencies (IPL), inter-aural latency differences (IAD) between age-matched groups of autistic and typically developing children. We also examined within ear waveform cross correlations and inter-aural cross correlations (IACC) to assess replicability and synchrony of participants’ auditory brainstem responses. Though we observed longer peak latencies (esp. wave III and V) and IPLs in both the autism and typically developing groups in different conditions, there were no statistically significant results in cross correlation or IACC. These results indicate that at the level of the brainstem, auditory processing may differ slightly, but is mostly similar between autistic and typically developing children. In terms of sensory processing in autism, future studies should examine the connection between ABR responses and behavioral measures of sensory processing, as well as function at more central levels of the auditory system.

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The speech auditory brainstem response (sABR) is a promising technique for assessing the function of the auditory system. This non-invasive technique has shown utility as a marker of central processing disorders, some types of learning difficulties in children, and potentially for fitting hearing aids. However, the sABR needs a long recording time to obtain a reliable signal due to the high background noise, which limits its clinical applicability. The objective of this work is to develop methods to detect the sABR in high background noise and enhance it based on a modeling approach and through experimental testing. First, sABR noise estimation based on LQ/QR decomposition is derived, and its mathematical proof is shown. Second, an autoregression model is used to estimate the single-trial sABR which is then used to test several sABR detection and enhancement methods. Third, a novel Artificial Neural Network (ANN) based detection approach is proposed and compared using modeled and recorded data to other detection methods in the literature: Optimal Linear Filter (LF), Online Estimator (OE), Mutual Information (MI) and Artificial Neural Network based on the Discrete Wavelet Transform and Approximate Entropy (ANN DA). Finally, comprehensive evaluation of several sABR enhancement methods is performed, based on the Wiener Filter (WF), Maximum-SNR Filter (Max-SNR), Adaptive Noise Cancellation (ANC) with Least-Mean-Square (LMS), Affine Projection (AP) and Recursive-Least-Square (RLS) adaptation algorithm. The results show that the developed LQ/QR decomposition estimated noise is similar to the actual noise, and the modeled data are statistically similar to the recorded data. Moreover, the proposed ANN-based detection method is more accurate and requires less processing time than other methods, and the comprehensive evaluation of enhancement methods shows that RLS has best overall performance in enhancing the sABR. Therefore, the methods developed and evaluated in this work have the potential to reduce the required recording time for the sABR, and thus make it more practical as a clinical tool.