Bram Van Dun

The relationship between cortical auditory evoked potential (CAEP) detection and estimated audibility in infants with sensorineural hearing loss

Abstract Objective: To determine the effectiveness of objective statistical detection in CAEP testing to evaluate audibility in young infants with sensorineural hearing loss. Design: CAEP recordings to speech-based stimuli were made at three presentation levels (55, 65, or 75 dB SPL) when a group of hearing-impaired infants were either aided or unaided. Later-obtained behavioral audiograms were used as the gold standard against which to evaluate the accuracy of the automatic detection of the presence/absence of CAEP responses. Study sample: Participants were 18 infants with confirmed sensorineural hearing loss. Results: Higher sensation levels led to a greater number of present CAEP responses being detected. More CAEP waveforms were detected in the aided condition than in the unaided condition. Conclusion: Our results suggest that the presence/absence of CAEP responses defined by the automatic statistical criterion was effective in showing whether increased sensation levels provided by amplification were sufficient to reach the cortex. This was clearly apparent from the significant increase in cortical detections when comparing unaided with aided testing.

Sensitivity of cortical auditory evoked potential detection for hearing-impaired infants in response to short speech sounds

Cortical auditory evoked potentials (CAEPs) are an emerging tool for hearing aid fitting evaluation in young children who cannot provide reliable behavioral feedback. It is therefore useful to determine the relationship between the sensation level of speech sounds and the detection sensitivity of CAEPs, which is the ratio between the number of detections and the sum of detections and non-detections. Twenty-five sensorineurally hearing impaired infants with an age range of 8 to 30 months were tested once, 18 aided and 7 unaided. First, behavioral thresholds of speech stimuli /m/, /g/, and /t/ were determined using visual reinforcement orientation audiometry. Afterwards, the same speech stimuli were presented at 55, 65, and 75 dB sound pressure level, and CAEPs were recorded. An automatic statistical detection paradigm was used for CAEP detection. For sensation levels above 0, 10, and 20 dB respectively, detection sensitivities were equal to 72±10, 75±10, and 78±12%. In 79% of the cases, automatic detection P-values became smaller when the sensation level was increased by 10 dB. The results of this study suggest that the presence or absence of CAEPs can provide some indication of the audibility of a speech sound for infants with sensorineural hearing loss. The detection of a CAEP might provide confidence, to a degree commensurate with the detection probability, that the infant is detecting that sound at the level presented. When testing infants where the audibility of speech sounds has not been established behaviorally, the lack of a cortical response indicates the possibility, but by no means a certainty, that the sensation level is 10 dB or less.

Least-squares deconvolution of evoked potentials and sequence optimization for multiple stimuli under low-jitter conditions.

OBJECTIVE Rapid presentation of stimuli in an evoked response paradigm can lead to overlap of multiple responses and consequently difficulties interpreting waveform morphology. This paper presents a deconvolution method allowing overlapping multiple responses to be disentangled. METHODS The deconvolution technique uses a least-squared error approach. A methodology is proposed to optimize the stimulus sequence associated with the deconvolution technique under low-jitter conditions. It controls the condition number of the matrices involved in recovering the responses. Simulations were performed using the proposed deconvolution technique. RESULTS Multiple overlapping responses can be recovered perfectly in noiseless conditions. In the presence of noise, the amount of error introduced by the technique can be controlled a priori by the condition number of the matrix associated with the used stimulus sequence. The simulation results indicate the need for a minimum amount of jitter, as well as a sufficient number of overlap combinations to obtain optimum results. An aperiodic model is recommended to improve reconstruction. CONCLUSIONS We propose a deconvolution technique allowing multiple overlapping responses to be extracted and a method of choosing the stimulus sequence optimal for response recovery. SIGNIFICANCE This technique may allow audiologists, psychologists, and electrophysiologists to optimize their experimental designs involving rapidly presented stimuli, and to recover evoked overlapping responses.

Latencies of Auditory Steady-State Responses Recorded in Early Infancy

Multiple-stimulus auditory steady-state responses (ASSRs) were assessed in 111 ears of 70 infants between –4 and 19 weeks of age at risk for hearing loss. ASSR thresholds obtained in infants with normal hearing (n = 69 ears) were compared with normal adult ASSR thresholds (n = 32 ears), and the linear relation between ASSR thresholds and behavioral thresholds (BHTs) was investigated in normal-hearing and hearing-impaired infants (n = 79 ears). Furthermore, latency estimates of significant responses to stimuli of 50 dB SPL were compared between the normal-hearing infants (n = 171 data points) and adults (n = 124 data points) and developmental changes in latency were evaluated within the infant group. Normal ASSR thresholds were on average 12 dB higher in infants compared with adults. Correlations between ASSR thresholds and BHTs were 0.75, 0.87, 0.87 and 0.79 for 500, 1000, 2000 and 4000 Hz, respectively. There was a significant effect of carrier frequency on ASSR latency, with higher carrier frequencies evoking shorter latencies in both infants and adults. Mean latencies in adults were 24.3 ± 1.5, 22.3 ± 1.1, 19.4 ± 1.0 and 18.0 ± 1.1 ms for 500, 1000, 2000 and 4000 Hz, respectively. Depending on the data fit of the infant latency estimates, mean latencies were 1.0 ms shorter or 9.5 ms longer in infants compared with adults. In infants, latencies were on average 2.0 ms longer in the youngest infant group (≤0 weeks) relative to the oldest infant group (3–8 weeks). These age-related trends, together with other arguments, point to longer latencies in infants compared with adults. The results of this study are valuable as a clinical reference for interpreting ASSR results obtained in high-risk infants within their first months of life and indicate that developmental changes occur regarding ASSR latency.

Deconvolution of overlapping cortical auditory evoked potentials recorded using short stimulus onset-asynchrony ranges.

OBJECTIVE The first aim of this study is to validate the theoretical framework of least-squares (LS) deconvolution on experimental data. The second is to investigate the waveform morphology of the cortical auditory evoked potential (CAEP) for five stimulus onset-asynchronies (SOAs) and effects of alternating stimulus frequency in normally hearing adults. METHODS Eleven adults (19-55 years) with normal hearing were investigated using tone-burst stimuli of 500 and 2000 Hz with SOAs jittered around 150, 250, 450, and 850 ms in a paired-interval paradigm with fixed or alternating stimulus frequency. RESULTS The LS deconvolution technique disentangled the overlapping responses, which then provided the following insights. The CAEP amplitude reached a minimum value for SOAs jittered around 450 ms, in contrast with significantly larger amplitudes for SOAs jittered around 150 and 850 ms. Despite this, longer latencies of N1 and P2 consistently occurred for decreasing SOAs. Alternating stimulus frequency significantly increased the amplitude of the CAEP response and decreased latencies for SOAs jittered around 150 ms. Effects of SOAs and alternating stimuli on CAEP amplitude can be modelled using a quantitative model of latent inhibition. CONCLUSIONS LS deconvolution allows correction for cortical response overlap. The amplitude of the CAEP is sensitive to SOA and stimulus frequency alternation. SIGNIFICANCE CAEPs are emerging as an important tool in the objective evaluation of hearing aid and cochlear implant fittings. Responses to closely spaced stimuli provide objective information about integration and inhibition mechanisms in the auditory cortex.

Analysis of alertness status of subjects undergoing the cortical auditory evoked potential hearing test

In this paper, we analyze the EEG rhythms of subjects undergoing the cortical auditory evoked potential (CAEP) hearing test. Investigation of the importance of the different EEG rhythms in terms of their capability in differentiating between the different alertness states when considering 64 channel EEG montage is conducted. This is followed by considering subsets that contain 2, 3, 4 as well as all 5 EEG rhythms. Finally, a feature subset selection method based on differential evolution (DE) that has particularly been proposed to deal with multi-channel signals is used to search for the best subset of EEG rhythms for the various channels.

Cortical Auditory Evoked Potentials in (Un)aided Normal-Hearing and Hearing- Impaired Adults

Cortical auditory evoked potentials (CAEPs) are influenced by the characteristics of the stimulus, including level and hearing aid gain. Previous studies have measured CAEPs aided and unaided in individuals with normal hearing. There is a significant difference between providing amplification to a person with normal hearing and a person with hearing loss. This study investigated this difference and the effects of stimulus signal-to-noise ratio (SNR) and audibility on the CAEP amplitude in a population with hearing loss. Twelve normal-hearing participants and 12 participants with a hearing loss participated in this study. Three speech sounds-/m/, /g/, and /t/-were presented in the free field. Unaided stimuli were presented at 55, 65, and 75 dB sound pressure level (SPL) and aided stimuli at 55 dB SPL with three different gains in steps of 10 dB. CAEPs were recorded and their amplitudes analyzed. Stimulus SNRs and audibility were determined. No significant effect of stimulus level or hearing aid gain was found in normal hearers. Conversely, a significant effect was found in hearing-impaired individuals. Audibility of the signal, which in some cases is determined by the signal level relative to threshold and in other cases by the SNR, is the dominant factor explaining changes in CAEP amplitude. CAEPs can potentially be used to assess the effects of hearing aid gain in hearing-impaired users.

Fuzzy Logic-Based Automatic Alertness State Classification Using Multi-channel EEG Data

This paper represents an attempt to automatically classify alertness state using information extracted from multi-channel EEG. To reduce the amount of data and improve the performance, a channel selection method based on support vector machine (SVM) classifier has been performed. The features used for the EEG channel selection process and subsequently for alertness classification represent the energy values of the five EEG rhythms; namely δ, θ, α, β and γ. In order to identify the feature/channel combination that leads to the best alertness state classification performance, we used a fuzzy rule-based classification system (FRBCS) that utilizes differential evolution in constructing the rules. The results obtained using the FRBCS were found to be comparable to those of SVM but with the added advantage of revealing the rhythm/channel combination associated with each alertness state.

The Cortical Automatic Threshold Estimation in Adults

W hile use of cortical auditory evoked potentials (CAEPs) has been shown to be accurate and reliable for objective threshold estimation, the procedure is in general conducted manually (i.e., using only one stimulus frequency presented at one intensity level at a time). The consequence is a lengthy test duration and a significant number of manual operations for the audiologist, which renders it impractical in clinical applications. To address this issue, the National Acoustic Laboratories (NAL), through the HEARing Cooperative Research Centre, has come up with a combination of smarter technologies.

An automatic algorithm for blink-artifact suppression based on iterative template matching: application to single channel recording of cortical auditory evoked potentials

OBJECTIVE Artifact reduction in electroencephalogram (EEG) signals is usually necessary to carry out data analysis appropriately. Despite the large amount of denoising techniques available with a multichannel setup, there is a lack of efficient algorithms that remove (not only detect) blink-artifacts from a single channel EEG, which is of interest in many clinical and research applications. This paper describes and evaluates the iterative template matching and suppression (ITMS), a new method proposed for detecting and suppressing the artifact associated with the blink activity from a single channel EEG. APPROACH The approach of ITMS consists of (a) an iterative process in which blink-events are detected and the blink-artifact waveform of the analyzed subject is estimated, (b) generation of a signal modeling the blink-artifact, and (c) suppression of this signal from the raw EEG. The performance of ITMS is compared with the multi-window summation of derivatives within a window (MSDW) technique using both synthesized and real EEG data. MAIN RESULTS Results suggest that ITMS presents an adequate performance in detecting and suppressing blink-artifacts from a single channel EEG. When applied to the analysis of cortical auditory evoked potentials (CAEPs), ITMS provides a significant quality improvement in the resulting responses, i.e. in a cohort of 30 adults, the mean correlation coefficient improved from 0.37 to 0.65 when the blink-artifacts were detected and suppressed by ITMS. SIGNIFICANCE ITMS is an efficient solution to the problem of denoising blink-artifacts in single-channel EEG applications, both in clinical and research fields. The proposed ITMS algorithm is stable; automatic, since it does not require human intervention; low-invasive, because the EEG segments not contaminated by blink-artifacts remain unaltered; and easy to implement, as can be observed in the Matlab script implemeting the algorithm provided as supporting material.