AI Article Synopsis
- Auditory brainstem response (ABR) testing evaluates hearing function, but current automated methods for determining thresholds are not reliable, relying mainly on trained personnel for visual identification.
- This study introduces a new automatic procedure for determining ABR thresholds in both animals and humans, using cross-correlation analysis to detect time-locked waveforms.
- The proposed method adjusts level averaging based on signal quality, demonstrating a strong correlation with human results and leading to more reliable, fully automated ABR tests.
Article Abstract
Auditory brainstem response (ABR) serves as an objective indication of auditory perception at a given sound level and is nowadays widely used in hearing function assessment. Despite efforts for automation over decades, ABR threshold determination by machine algorithms remains unreliable and thereby one still relies on visual identification by trained personnel. Here, we described a procedure for automatic threshold determination that can be used in both animal and human ABR tests. The method terminates level averaging of ABR recordings upon detection of time-locked waveform through cross-correlation analysis. The threshold level was then indicated by a dramatic increase in the sweep numbers required to produce "qualified" level averaging. A good match was obtained between the algorithm outcome and the human readouts. Moreover, the method varies the level averaging based on the cross-correlation, thereby adapting to the signal-to-noise ratio of sweep recordings. These features empower a robust and fully automated ABR test.
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Source |
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8571499 | PMC |
| http://dx.doi.org/10.1016/j.isci.2021.103285 | DOI Listing |
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