Programming Cochlear Implant With Artificial Intelligence

NCT ID: NCT03700268

Last Updated: 2018-10-09

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

UNKNOWN

Clinical Phase

NA

Total Enrollment

30 participants

Study Classification

INTERVENTIONAL

Study Start Date

2017-09-04

Study Completion Date

2021-09-30

Brief Summary

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This thesis project proposes to investigate the "state of the art" of the programming of the cochlear implant. In the center of audiophonologie Brussels, the classic 'manual programming' has been in use over 20 years and also the new way 'Artificial Intelligence programming'. The investigators want to compare, objectify, and control this new mode of programming.

The study is planned over 4 years, in order to test, randomized, 15 subjects with manual programming and 15 other subjects with Artificial Intelligence programming. To test the performance of Cochlear Implant patients, audiological, language auditory perception and questionnaire tests will be presented.

This research aims to determine the contribution and results of Artificial Intelligence programming.

Detailed Description

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Conditions

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Deafness; Perception

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

CROSSOVER

Primary Study Purpose

TREATMENT

Blinding Strategy

NONE

Study Groups

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Manual fitting

The patient is receiving the classical treatment : 10 sessions of 1 hour during one year where the clinician programs manually the Cochlear implant.

Group Type EXPERIMENTAL

Manual intervention to programme Cochlear Implant electrodes

Intervention Type OTHER

The Clinician test the 22 electrodes so that the patient is able to hear the language

Artificial Intelligence

The patient is receiving the new treatment : 4 sessions of 1 hour during one year where the clinician programs the Cochlear implant with the FOX (Fitting to Outcome eXpert) software using artificial intelligence.

Group Type EXPERIMENTAL

Manual intervention to programme Cochlear Implant electrodes

Intervention Type OTHER

The Clinician test the 22 electrodes so that the patient is able to hear the language

Interventions

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Manual intervention to programme Cochlear Implant electrodes

The Clinician test the 22 electrodes so that the patient is able to hear the language

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* unilateral cochlear implant
* post-lingual hearing loss
* a good command of French.

Exclusion Criteria

* non deaf
* bilateral cochlear implant
* deaf without cochlear implant
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Cliniques universitaires Saint-Luc- Université Catholique de Louvain

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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Cliniques Universitaires Saint-Luc

Brussels, , Belgium

Site Status RECRUITING

Countries

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Belgium

Facility Contacts

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Justine Wathour

Role: primary

+3227643169

References

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Wathour J, Govaerts PJ, Lacroix E, Naima D. Effect of a CI Programming Fitting Tool with Artificial Intelligence in Experienced Cochlear Implant Patients. Otol Neurotol. 2023 Mar 1;44(3):209-215. doi: 10.1097/MAO.0000000000003810. Epub 2023 Jan 18.

Reference Type DERIVED
PMID: 36728126 (View on PubMed)

Wathour J, Govaerts PJ, Deggouj N. Variability of fitting parameters across cochlear implant centres. Eur Arch Otorhinolaryngol. 2021 Dec;278(12):4671-4679. doi: 10.1007/s00405-020-06572-w. Epub 2021 Jan 3.

Reference Type DERIVED
PMID: 33388985 (View on PubMed)

Wathour J, Govaerts PJ, Deggouj N. From manual to artificial intelligence fitting: Two cochlear implant case studies. Cochlear Implants Int. 2020 Sep;21(5):299-305. doi: 10.1080/14670100.2019.1667574. Epub 2019 Sep 17.

Reference Type DERIVED
PMID: 31530099 (View on PubMed)

Other Identifiers

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2017/13OCT/480

Identifier Type: OTHER

Identifier Source: secondary_id

2017/04SEP/427

Identifier Type: -

Identifier Source: org_study_id

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