ArticleiScience2021
Real-time threshold determination of auditory brainstem responses by cross-correlation analysis.
Article in iScience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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Who cites it
10 citing papers in PubMed.
- Developing a Calibration Method to Minimize Variability in Auditory Evoked Potentials.Journal of the Association for Research in Otolaryngology : JARO · 2025Article
- ABRpresto: An algorithm for automatic thresholding of the Auditory Brainstem Response using resampled cross-correlation across subaverages.bioRxiv : the preprint server for biology · 2024Article
- Spatial patterns of noise-induced inner hair cell ribbon loss in the mouse mid-cochlea.iScience · 2024Article
- Rapid hearing threshold assessment with modified auditory brainstem response protocols in dogs.Frontiers in veterinary science · 2024Article
- Bats experience age-related hearing loss (presbycusis).Life science alliance · 2023Article
- Subtle alterations of vestibulomotor functioning in conductive hearing loss.Frontiers in neuroscience · 2023Article
- A New Adaptive GCC Method and Its Application to Slug Flow Velocity Measurement in Small Channels.Sensors (Basel, Switzerland) · 2022Article
- Volume electron microscopy reveals age-related circuit remodeling in the auditory brainstem.Frontiers in cellular neuroscience · 2022Article
- Objectification of intracochlear electrocochleography using machine learning.Frontiers in neurology · 2022Article
- Comparison of Deep Learning Models for Objective Auditory Brainstem Response Detection: A Multicenter Validation Study.Trends in hearingArticle
Corrections and comments
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.