Evidence map›Paper›PMID 35204015›Full record

ArticleBrain sciences2022

Frequency Fitting Optimization Using Evolutionary Algorithm in Cochlear Implant Users with Bimodal Binaural Hearing.

Alexis Saadoun, Antoine Schein, Vincent Péan, Pierrick Legrand, Ludwig Serge Aho Glélé, Alexis Bozorg Grayeli

2 registry-linked trialsOpen access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Brain sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 35% 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.

NCT03202797 completednot on this map

Optimizing Regulation of a Cochlear Implant in Patients With Functional Contralateral Audition Using an Evolutionary Algorithm.

TypeobservationalSponsorCentre Hospitalier Universitaire DijonRan2017 to 2017Enrolled9ConditionsFunctional Contralateral Audition, Cochlear ImplantArmsaudiometric tests, Questionnaires, Settings of cochlear implants
NCT04888143 nacompletednot on this map

Optimization of Cochlear Implant Fitting in Patients With Functional Contralateral Hearing Using an Evolutionary Algorithm.

TypeinterventionalSponsorCentre Hospitalier Universitaire DijonRan2020 to 2020Enrolled18ConditionsProfound DeafnessArmsquestionnaires, Evolutionary algorithm
3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Review
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

6 authors at 2 institutions in 1 country.

Alexis SaadounDepartment of Otolaryngology-Head and Neck Surgery, Dijon University Hospital, 21000 Dijon, France.ORCID 0000-0003-1999-305X
Antoine ScheinDepartment of Otolaryngology-Head and Neck Surgery, Dijon University Hospital, 21000 Dijon, France.
Vincent PéanClinical Support Department, MED-EL, 75012 Paris, France.
Pierrick LegrandInstitute of Mathematics of Bordeaux, UMR CNRS 5251, ASTRAL Team, Inria Bordeaux Sud-Ouest, University of Bordeaux, 33405 Talence, France.
Ludwig Serge Aho GléléDepartment of Hospital Epidemiology and Infection Control, Dijon University Hospital, 21000 Dijon, France.ORCID 0000-0001-7590-8644
Alexis Bozorg GrayeliDepartment of Otolaryngology-Head and Neck Surgery, Dijon University Hospital, 21000 Dijon, France.
Maison des Sciences sociales et des Humanités de Dijon · FRCentre National de la Recherche Scientifique · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Optimizing hearing in patients with a unilateral cochlear implant (CI) and contralateral acoustic hearing is a challenge. Evolutionary algorithms (EA) can explore a large set of potential solutions in a stochastic manner to approach the optimum of a minimization problem. The objective of this study was to develop and evaluate an EA-based protocol to modify the default frequency settings of a MAP (fMAP) of the CI in patients with bimodal hearing.

methodsThis monocentric prospective study included 27 adult CI users (with post-lingual deafness and contralateral functional hearing). A fitting program based on EA was developed to approach the best fMAP. Generated fMAPs were tested by speech recognition (word recognition score, WRS) in noise and free-field-like conditions. By combining these first fMAPs and adding some random changes, a total of 13 fMAPs over 3 generations were produced. Participants were evaluated before and 45 to 60 days after the fitting by WRS in noise and questionnaires on global sound quality and music perception in bimodal binaural conditions.

resultsWRS in noise improved with the EA-based fitting in comparison to the default fMAP (41.67 ± 9.70% versus 64.63 ± 16.34%, respectively,

conclusionsBy modifying the default fMAPs, the EA improved the speech discrimination in noise and the sound quality in bimodal binaural conditions.

Indexed as

binaural hearingcochlear implantevolutionary algorithmfittingquality of lifespeech discrimination in noise

Identifiers

PMID35204015
PMCPMC8870060
OpenAlexW4213062766

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.