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Algorithm-Based Hearing and Speech Therapy Rehabilitation after Cochlear Implantation.

Authors :
Eichler T
Rötz W
Kayser C
Bröhl F
Römer M
Witteborg AH
Kummert F
Sandmeier T
Schulte C
Stolz P
Meyer K
Sudhoff H
Todt I
Source :
Brain sciences [Brain Sci] 2022 Apr 29; Vol. 12 (5). Date of Electronic Publication: 2022 Apr 29.
Publication Year :
2022

Abstract

Introduction: Due to the changes in the indication range for cochlear implants and the demographic development towards an aging society, more and more people are in receipt of cochlear implants. An implantation requires a close-meshed audiological and logopedic aftercare. Hearing therapy rehabilitation currently requires great personnel effort and is time consuming. Hearing and speech therapy rehabilitation can be supported by digital hearing training programs. However, the apps currently on the market are to a limited degree personalized and structured. Increasing digitalization makes it possible, especially in times of pandemics, to decouple hearing therapy treatment from everyday clinical practice.<br />Material and Methods: For this purpose, an app is in development that provides hearing therapy tailored to the patient. The individual factors that influence hearing outcome are considered. Using intelligent algorithms, the app determines the selection of exercises, the level of difficulty and the speed at which the difficulty is increased.<br />Results: The app works autonomously without being connected to local speech therapists. In addition, the app is able to analyze patient difficulties within the exercises and provides conclusions about the need for technical adjustments.<br />Conclusions: The presented newly developed app represents a possibility to support, replace, expand and improve the classic outpatient hearing and speech therapy after CI implantation. The way the application works allows it to reach more people and provide a time- and cost-saving alternative to traditional therapy.

Details

Language :
English
ISSN :
2076-3425
Volume :
12
Issue :
5
Database :
MEDLINE
Journal :
Brain sciences
Publication Type :
Academic Journal
Accession number :
35624970
Full Text :
https://doi.org/10.3390/brainsci12050580