Automatic audiometry using auditory steady-state response and sequential test strategy applied to volunteers with normal hearing.

PURPOSE: In the present study, a new procedure to perform automatic audiometry using multifrequency Auditory Steady-State Response (ASSR) is proposed. METHODS: The automatic audiometry procedure consists of detecting the presence of multifrequency ASSR in real-time using the sequential test strategy and by adjusting the stimulus intensity independently. The ASSR audiometric thresholds of 18 adult volunteers with normal hearing were determined by automatically (four simultaneous frequencies per ear) at modulation frequencies in the 80 Hz range. The exam time and the difference between ASSR thresholds and pure-tone behavioural hearing thresholds were estimated as performance measures. RESULTS: The results showed that automatic audiometry can reduce the number of intensity levels used to obtain the ASSR threshold by up to 58% when compared to audiometry without using the techniques applied in automatic audiometry. In addition, the average of the difference between ASSR thresholds and Pure-Tone Behavioural Hearing thresholds was around 19 dB, which is similar to the results reported in similar studies. CONCLUSIONS: The audiometric procedure proposed in this study is fully automatic, i.e., does not require any human supervision throughout the exam, and is able to significantly reduce the conventional exam time.

Faster automatic ASSR detection using sequential tests.

Objective: Objective Response Detection (ORD) can be used for auditory steady-state response (ASSR) detection. In conventional ORD methods, the statistical tests are applied at the end of data collection ('single-shot tests'). In sequential ORD methods, statistical tests are applied repeatedly, while data is being collected. However, repeated testing can increase False Positive (FP) rates. One solution is to infer that response is present only after the test remains significant for a predefined number of consecutive detections (NCD). Thus, this paper describes a new method for finding the required NCD that control the FP rate for ASSR detection.Design: NCD values are estimated using Monte Carlo simulations.Study sample: ASSR signals were recorded from 8 normal-hearing subjects.Results: The exam time was reduced by up to 38.9% compared to the single-shot test with loss of approximately 5% in detection rate. Alternatively, lower gains in time were achieved for a smaller (non-significant) loss in detection rate. The FP rates at the end of the test were kept at the nominal level expected (1%).Conclusion: The sequential test strategy with NCD as the stopping criterion can improve the speed of ASSR detection and prevent higher than expected FP rates.

Automated detection of auditory response: applying sequential detection strategies with constant significance level to magnitude-squared coherence.

Abstracts Objective: The detection of the auditory steady-state responses is usually performed by an appropriate objective response detector applied to stimulus-related epochs of the raw electroencephalogram (EEG). In order to improve the detection time, sequential detection strategies are usually used. These multiple tests strategies increase the probability of mistakenly detecting a response. The aim of this study was to develop strategies to determine the critical values for the sequential detection strategies based on constant significance level tests. Design: Extensive Monte Carlo simulations were used to test these strategies for the magnitude-squared coherence (MSC) detector. The performances of these strategies were compared with previous works found in the literature. Study sample: All strategies were applied to synthetic and real EEG datasets. Results: The strategies ensure the desired significance level at the end of the sequential detection strategy. The simulated results are in accordance with the real data results. Conclusions: For the MSC detector, where the critical value depends on the number of epochs, the proposed sequential detection strategies obtain better performance regarding test time and detection rate, but worse overall detection rate compared to applying a test only once.

Multi-channel and multi-harmonic analysis of Auditory Steady-State Response detection.

The Auditory Steady-State Response (ASSR) is a type of auditory evoked potential (AEP) generated in the auditory system that can be automatically detected by means of objective response detectors (ORDs). ASSRs are usually registered on the scalp using electroencephalography (EEG). ORD are univariate techniques, i.e. only uses one data channel. However, techniques involving more than one channel - multi-channel objective response detectors (MORDs) - have been showing higher detection rate (DR) when compared to ORD techniques. When ASSR is evoked by amplitude stimuli, the responses could be detected by analyzing the modulation frequencies and their harmonics. Despite this, ORD techniques are traditionally applied only in its first harmonic. This approach is known as one-sample test. The q-sample tests, however, considers harmonics beyond the first. Thus, this work proposes and evaluates the use of q-sample tests using a combination of multiple EEG channels and multiple harmonics of the stimulation frequencies and compare them with traditional one-sample tests. The database used consists of EEG channels from 24 volunteers with normal auditory threshold collected following a binaural stimulation protocol by amplitude modulated (AM) tone with modulating frequencies near 80 Hz. The best q-sample MORD result showed an increase in DR of 45.25% when compared with the best one-sample ORD test. Thus, it is recommended to use multiple channels and multiple harmonics, whenever available.

Dealing with correlations in the multichannel EEG using bipolar derivations and Monte Carlo simulations: application to the detection of auditory steady-state responses.

The multichannel objective response detection (MORD) techniques are statistical methods, which use information from more than one electroencephalography (EEG) channel, to infer the presence of evoked potential. However, the correlation level between the channels can lead to a decrease in MORD performance, such as an increase in the false positive (FP) rate and/or a decrease in the detection rate (DR). The present study aims to propose a method to deal with the correlations in the multichannel EEG. The method consists of making an adjustment in the Monte Carlo simulation, considering the information between channels. The MORD techniques with and without the new method were applied to an auditory steady-state response (ASSR) database, composed of the EEG multichannel of eleven volunteers during multifrequency stimulation. The proposed method kept the FP rate at values equal to or less than the significance level of the test and led to an increase of 8.51% in the DR in relation to non-application of the method. Results of this study indicate that the proposed method is an alternative to deal with the effect of the correlation between channels in situations where MORD techniques are applied.

Multichannel search strategy for improving the detection of auditory steady-state response.

Auditory steady-state response (ASSR) is useful for hearing threshold estimation. The ASSR is usually detected with objective response detectors (ORD). The performance of these detectors depends on the signal-to-noise ratio (SNR) as well as the signal length. Since it is undesirable to increase the signal length, then, this work provides a multivariate technique for improving the SNR and consequently the detection power. We propose the insertion of a short calibration step before the detection protocol, in order to perform a search among the available electroencephalogram (EEG) derivations and select the derivation with the highest SNR. The ORD used in this work was the magnitude-squared coherence (MSC). The standard detection protocol is to use the same EEG derivation in all exams. Using 22-scalp positions, the new technique achieved a detection rate higher than that obtained in 99.13% of the standard detection protocol. When restrictions were applied to the search, a superior performance was achieved. Thus, the technique proposed was able to track the best EEG derivations before exams and seems to be able to deal with the variability between individuals and between sessions.

The global Beta test for hidden periodicities in signals and its extensions to multivariate systems.

BACKGROUND AND OBJECTIVE: There are many phenomena that lead to changes in the power spectrum of a given signal, and their detection has been a challenge that has received considerable attention over the years. Objective Response Detection (ORD) techniques are a set of tools that perform automated tests for such a task, allowing thus to automatically track changes in the spectrum. The performance of these detectors is affected by the signal-to-noise ratio (SNR) of the recorded signal as well as the length of the available data. The Global F Test (GFT) is a promising detector that can be used to test whether there is a statistically significant difference between the spectrum before and during an event. In fact, this detector has proved useful in the detection of event-related desynchronization/synchronization (ERD/ERS), where only amplitude, but not the phase, changes are locked to the stimulus. In order to improve the statistical power of the GFT (for the same length of recording), multiple channels recorded simultaneously can be included. This concept is called Multivariate Response Detection. The aim of the current work is to extend the GFT to the multivariate (multichannel) case. METHODS: Firstly, the single channel normalization of the GFT is presented as a new ORD detector - the global Beta test (GBT). After that, three multivariate extensions of this new test are derived. The critical values used in the detection of spectral changes are obtained by using theoretical distributions, and where this is intractable, by means of Monte Carlo simulations. The probability of detection (PD) of each technique was estimated using simulation and was used in order to compare the detectors performance. A practical example with the electroencephalogram (EEG) from 10 volunteers under intermittent photic stimulation was also provided. RESULTS: The statistics under both the null and alternative hypothesis could be obtained for all detectors. Simulated results for PD demonstrate the strong potential of the proposed method and the performances in EEG data are always improved with increasing number of signals. CONCLUSION: If more than one signal is available, then the multivariate extensions may provide significant benefit compared to the original GFT.

Improving the power of objective response detection of evoked responses in noise by using average and product of magnitude-squared coherence of two different signals.

Objective response detection (ORD) techniques such as the magnitude-squared coherence (MSC) are mathematical methods tailored to detect potentials evoked by an external periodic stimulation. The performance of the MSC is directly proportional to the signal-to-noise ratio (SNR) of the recorded signal and the time spent for collecting data. An alternative to increasing the performance of detection techniques without increasing data recording time is to use the information from more than one signal simultaneously. In this context, this work proposes two new detection techniques based on the average and on the product of MSCs of two different signals. The critical values and detection probabilities were obtained theoretically and using a Monte Carlo simulation. The performances of the new detectors were evaluated using synthetic data and electroencephalogram (EEG) signals during photo and auditory stimulation. For the synthetic signals, the two proposed detectors exhibited a higher detection rate when compared to the rate of the traditional MSC technique. When applied to EEG signals, these detectors resulted in an increase of the mean detection rate in relation to MSC for visual and auditory stimulation of at least 25% and 13.21%, respectively. The proposed detectors may be considered as promising tools for clinical applications. Graphical Abstract.