Evidence map›Paper›PMID 37194477›Full record

ArticleTrends in hearing

Clinical Feasibility and Familiarization Effects of Device Delay Mismatch Compensation in Bimodal CI/HA Users.

Julian Angermeier, Werner Hemmert, Stefan Zirn

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Article in Trends in hearing. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Julian AngermeierFaculty of Electrical Engineering, Medical Engineering and Computer Sciences, Peter Osypka Institute of Medical Engineering, University of Applied Sciences Offenburg, Offenburg, Germany.ORCID 0000-0002-2041-0723
Werner HemmertBio-Inspired Information Processing, Munich Institute of Biomedical Engineering, Technical University of Munich, Garching, Germany.ORCID 0000-0002-2905-6118
Stefan ZirnFaculty of Electrical Engineering, Medical Engineering and Computer Sciences, Peter Osypka Institute of Medical Engineering, University of Applied Sciences Offenburg, Offenburg, Germany.ORCID 0000-0003-2901-0328

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Subjects utilizing a cochlear implant (CI) in one ear and a hearing aid (HA) on the contralateral ear suffer from mismatches in stimulation timing due to different processing latencies of both devices. This device delay mismatch leads to a temporal mismatch in auditory nerve stimulation. Compensating for this auditory nerve stimulation mismatch by compensating for the device delay mismatch can significantly improve sound source localization accuracy. One CI manufacturer has already implemented the possibility of mismatch compensation in its current fitting software. This study investigated if this fitting parameter can be readily used in clinical settings and determined the effects of familiarization to a compensated device delay mismatch over a period of 3-4 weeks. Sound localization accuracy and speech understanding in noise were measured in eleven bimodal CI/HA users, with and without a compensation of the device delay mismatch. The results showed that sound localization bias improved to 0°, implying that the localization bias towards the CI was eliminated when the device delay mismatch was compensated. The RMS error was improved by 18% with this improvement not reaching statistical significance. The effects were acute and did not further improve after 3 weeks of familiarization. For the speech tests, spatial release from masking did not improve with a compensated mismatch. The results show that this fitting parameter can be readily used by clinicians to improve sound localization ability in bimodal users. Further, our findings suggest that subjects with poor sound localization ability benefit the most from the device delay mismatch compensation.

Indexed as

Cochlear ImplantationCochlear ImplantsHearing AidsSound LocalizationSpeech PerceptionFeasibility StudiesHumansbimodal hearingdevice delay mismatchsound localization

Identifiers

PMID37194477
PMCPMC10196534

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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.