Evidence map›Paper›PMID 38289498›Full record

ArticleHNO2024

[Concept and implementation of an adaptive digital hearing training system for cochlear implant aftercare].

Maika Werminghaus, Florian Gnadlinger, Jutta G Richter, André Selmanagić, Susann Thyson, Dorothee Schatton, Thomas Klenzner

Erratum issuedOpen access · hybridAbstract readEnglish Abstract
In one paragraph

Article in HNO, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 99% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

  • Erratum issued
    2025
5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Maika WerminghausKlinik für Hals-Nasen-Ohrenheilkunde, Hörzentrum, Medizinische Fakultät und Universitätsklinikum Düsseldorf, Heinrich-Heine-Universität Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Deutschland. Maika.Werminghaus@med.uni-duesseldorf.de.
Florian GnadlingerMasrayk University, Brünn, Tschechien.
Jutta G RichterKlinik für Rheumatologie, Medizinische Fakultät und Universitätsklinikum Düsseldorf, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Deutschland.
André SelmanagićForschungs- & Weiterbildungszentrum für Kultur und Informatik, Hochschule für Technik und Wirtschaft Berlin, Berlin, Deutschland.
Susann ThysonKlinik für Hals-Nasen-Ohrenheilkunde, Hörzentrum, Medizinische Fakultät und Universitätsklinikum Düsseldorf, Heinrich-Heine-Universität Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Deutschland.
Dorothee SchattonKlinik für Hals-Nasen-Ohrenheilkunde, Hörzentrum, Medizinische Fakultät und Universitätsklinikum Düsseldorf, Heinrich-Heine-Universität Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Deutschland.
Thomas KlenznerKlinik für Hals-Nasen-Ohrenheilkunde, Hörzentrum, Medizinische Fakultät und Universitätsklinikum Düsseldorf, Heinrich-Heine-Universität Düsseldorf, Moorenstr. 5, 40225, Düsseldorf, Deutschland.
Heinrich Heine University Düsseldorf · DEDüsseldorf University Hospital · DEHTW Berlin - University of Applied Sciences · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectiveWithin the context of an interdisciplinary research project, we created a cutting-edge prototype of an adaptive digital auditory training system designed for cochlear implant (CI) users. By leveraging the evidence-centered design (ECD) framework, we integrated a dynamic difficulty adjustment feature that tailors the experience to the unique performance capabilities of each individual user.

methodsThe ECD provides a conceptual design framework suitable for complex assessments of competence and dynamic performance. In the first phase, the domain of hearing was first defined in the context of CI users. In the development phase the three core models of the ECD, the competence model, the evidence model, and the task model, were developed and implemented. In addition, an asset pool of sound and language files was created, which included comprehensive linguistic feature descriptions for calculating item difficulties.

resultsBased on the requirements described, an adaptive exercise generator, an AI service, and other components were implemented. This included the development of a game environment and a dashboard for patient data management. The exercises' difficulty levels were determined based on various parameters (e.g., sound, word frequency and number of words, grammatical properties) in combination with defined task types and levels.

conclusionAn adaptive digital auditory training system can help to supervise and train CI patients in a continuous, interactive process based on their individual needs. We see the ECD as an effective way to build a user-based adaptive system.

Indexed as

Cochlear ImplantsAftercareComputer-Assisted InstructionCorrection of Hearing ImpairmentGermanyHearing LossHumansPatient Education as TopicTherapy, Computer-AssistedCochlea-ImplantatDigital healthGame based learningLearning health systemRehabilitation

Identifiers

PMID38289498
PMCPMC11422247
OpenAlexW4391353521

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.