Archive · dataset · 2026
Design of customisable audible brainstem response data for training and testing of audiological AI-software
Listed in PTB-OAR
This document comprises a compendium of the design of electroencephalography data for an application to train and test deep-learning networks to be applied on auditory brainstem responses.
Description
Despite their essentially artificial nature, the data are derived from experimental sources and are representative of the characteristic behaviour of audiological practice. It is possible to customise them to meet specific requirements, such as different levels of loudness, noise levels, and the amplitude and latency relationship between the six waves, which is characteristic of the responses.
The data set under consideration comprises a total of 105 time series, which are divided into three distinct loudness classes: loud (70 dB), medium loud (50 dB), and silent (30 dB).
Links
Where it is published
- PTB-OAR record oar.ptb.de/resources/show/10.7795/710.20260210 ↗
landing page · from oar ptb de
- DOI doi.org/10.7795/710.20260210 ↗
DOI / persistent id · from oar ptb de
Catalogue records · 1
- OAI-PMH record oar.ptb.de/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Aoar.… ↗
metadata API · from oar ptb de
Topics
- From keywords
- Chemistry · Computer Science & AI · Earth & Environmental Science · Engineering · Physics
- Inferred from text
- Neural engineering 76%
Provenance · 1 source records, 11 field assertions
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|---|---|---|---|
| PTB-OAR | oai:oar.ptb.de:10.7795/710.20260210 | 3 d ago | JSON v1 |
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| title | source · oar ptb de | connector:oar_ptb_de@1.0.0 | /metadata/dc/title |