The Auditory Brainstem Response (ABR) is an evoked potential that originates at the auditory nerve (Cranial Nerve VIII) and the response is picked up by surface electrodes typically placed at Vertex and Left and Right mastoids. An ABR test is used to assess the auditory system’s function from the cochlea through the brainstem.
The response to auditory broad band or frequency specific stimuli is identified by “peaks” that occur typicallybetween 1 and 15 milliseconds from the stimulus onset. The ABR peaks are measured and marked traditionally as I, II, III, IV, and V. Each peak has an expected latency range to be considered “normal”. Delayed or missingpeaks are consistent with abnormal auditory function. The presence or absence of responses can be used to estimate hearing thresholds. An ABR threshold is an electrophysiological threshold that can be used to predict the behavioral audiogram. The difference between the two may vary quite a lot, but correction of 20dB at 500Hz, 15dB at 1kHz, 10dB at 2kHz and 5dB at 4kHz are typically applied correction factors.
Threshold recording using 2kHz Tone Burst. Note the large PAM response from the right side caused by the loud stimulus of 80dBnHL. The ABR threshold at 20dB nHL at 2kHz found here would be well within the range of normal hearing - applying a typical correction factor would estimate the behavioral audiogram threshold to be 10dBHL at 2kHz.
Improving Threshold testing with Eclipse
Challenges arise when evaluating hearing thresholds. They can include:
CE-Chirp® Stimulus Family
We know that as we get closer to threshold, the waveform latencies increase and the amplitudes decrease. This presents a challenge in “peak picking”. A solution is the implementation and use of the CE-Chirp® LS and NB CE-Chirp® LS. The CE-Chirp® LS Stimulus Family compares to the traditional click while the NB CE-Chirp® LS compares to traditional tone burst. Research indicates that the use of the CE-Chirp LS® and NB CE-Chirp® LS particularly at modest stimulation levels results in waveform amplitudes up to double that of traditional stimuli (Elberling & Don, 2008; Ferm et al., 2013). This is achieved by simply accounting for timing issues within the cochlea. If amplitudes can be increased, the ability of the user to quickly and accurately identify waveform peaks near threshold increases. This clearly reduces test time and increases user confidence. Please see example below.
The larger amplitudes of the CE-Chirp® LS when compared to the traditional Click allows for faster and more reliable testing. Similar benefits can be found when substituting traditional Tone Bursts with the NB CE-Chirps® LS.
Residual Noise Calculation
Noise levels also create a challenge as noise can eliminate the ability to obtain or view the necessary waveform peaks. Lower noise levels increase the ability to identify the waveform peaks and increase the confidence of the presence or absence of a response.
Traditionally, users run a set number of sweeps in an effort to reduce the amount of noise in the recording. However, the number of sweeps may tell us little about the Residual Noise in the tracing. An objective Residual Noise measure should be used instead. Typically, if Residual Noise levels are 40nV or less, the tracing is sufficiently clean to be able to reveal a response if present. Therefore, Interacoustics implemented the Residual Noise calculation. The use of Residual Noise calculation either by monitoring or as a stop criterion greatly improves the certainty. The Residual Noise bar placed on the right side of the Fmp graph indicates the Residual Noise level and will turn green with a checkmark when the criterion for residual noise is reached (e.g. 40nV).
The Fmp value (red curve) has at this point of testing passed the 99% response confidence criteria, and the Residual Noise level (black curve) has not yet reached the 40nV residual noise level suitable for quality recordings around threshold.
Fmp Calculation & Response Confidence
The Fmp is an indication of the Response Confidence of the recorded response. While looking at the waveform being recorded, a confidence level is calculated, and provided as a percentage of statistical certainty of a response being present in the recorded waveform. This statistical analysis assists the clinician in that it can reduce test time since it relies on statistical information and not solely on the experience of the user. The experienced user can encompass the Fmp values when evaluating response presence or absence. Often the Fmp will detect strong responses sooner than confident eyeballing can reach the same conclusion. On the other hand, Fmp may not identify smaller responses close to threshold, in which case eyeballing is to be applied, being the golden standard in response detection at threshold. When the response confidence reaches the set criteria (e.g. 99%) the bar indicating the Response Confidence turns green with a checkmark indicating that the Response Confidence criterion is met.
In the best testing scenario that one should always try to obtain, the patient will be very quiet or sleeping and the EEG at a constant and low level throughout the data acquisition. This is not always the case and Bayesian Weighting is of great help in such test situations. It is an averaging technique that weighs each sweep individuallygiving more “weight” or importance to quiet sweeps and less “weight” to sweeps with more noise. This is different from traditional averaging since traditional averaging simply accepts or rejects each sweep and not weighing them individually.
The use of Bayesian Weighting will assist the clinician in situations that are not ideal testing conditions, and will not alter the response waveform’s morphology.
A few additional practical hints
The Rearrange Curves and Group Curves functions in the upper tool bar ensure easy manual positioning of waveforms.
The A&B tool in the upper tool bar allows waveform reproducibility to be evaluated without the need to run repeated waveforms.
Don, M. & Elberling, C. (1996). Use of quantitative measures of auditory brain-stem response peak amplitude and residual background noise in the decision to stop averaging. J. Acoust. Soc. Am., 99(1).
Elberling, C. & Don, M. (1984). Quality Estimation of averaged auditory brainstem responses. Scand Audiol. (13) 187-197.
Elberling, C., & Don, M. (2008). Auditory brainstem responses to a chirp stimulus designed from derived-band latencies in normal-hearing subjects. J. Acoust. Soc. Am. (124) 3022-3037.
Elberling, C. & Wahlgreen (1985). Estimation of auditory brainstem response, ABR, by means of Bayesian interference. Scand. Audiol (14) 89-96.
Ferm, I., Lightfoot, G. & Stevens (2013). J. Comparison of ABR response amplitude, test time, and estimation of hearing threshold using frequency specific chirp and tone pip stimuli in newborns. International Journal of Audiology, (52) 419-423.