Background: Hearing threshold estimation based on cortical auditory evoked potentials (CAEPs)
has been applied for some decades. However, available research is scarce evaluating
the accuracy of this technique with an automated paradigm for the objective detection
of CAEPs.
Purpose: To determine the difference between behavioral and CAEP thresholds detected using
an objective paradigm based on the Hotelling’s T
2 statistic. To propose a decision tree to choose the next stimulus level in a sample
of hearing-impaired adults. This knowledge potentially could increase the efficiency
of clinical hearing threshold testing.
Research Design: Correlational cohort study. Thresholds obtained behaviorally were compared with thresholds
obtained through cortical testing.
Study Sample: Thirty-four adults with hearing loss participated in this study.
Data Collection and Analysis: For each audiometric frequency and each ear, behavioral thresholds were collected
with both pure-tone and 40-msec tone-burst stimuli. Then, corresponding cortical hearing
thresholds were determined. An objective cortical-response detection algorithm based
on the Hotelling’s T
2 statistic was applied to determine response presence. A decision tree was used to
select the next stimulus level. In total, 241 behavioral-cortical threshold pairs
were available for analysis. The differences between CAEP and behavioral thresholds
(and their standard deviations [SDs]) were determined for each audiometric frequency.
Cortical amplitudes and electroencephalogram noise levels were extracted. The practical
applicability of the decision tree was evaluated and compared to a Hughson-Westlake
paradigm.
Results: It was shown that, when collapsed over all audiometric frequencies, behavioral pure-tone
thresholds were on average 10 dB lower than 40-msec cortical tone-burst thresholds,
with an SD of 10 dB. Four percent of CAEP thresholds, all obtained from just three
individual participants, were more than 30 dB higher than their behavioral counterparts.
The use of a decision tree instead of a Hughson-Westlake procedure to obtain a CAEP
threshold did not seem to reduce test time, but there was significantly less variation
in the number of CAEP trials needed to determine a threshold.
Conclusions: Behavioral hearing thresholds in hearing-impaired adults can be determined with an
acceptable degree of accuracy (mean threshold correction and SD of both 10 dB) using
an objective statistical cortical-response detection algorithm in combination with
a decision tree to determine the test levels.
Key Words
cortical auditory evoked potentials - hearing impairment - hearing thresholds - automated
objective detection - estimation techniques
