Genetic Programming and Evolvable Machines

, Volume 8, Issue 4, pp 319–354 | Cite as

Interactive evolution for cochlear implants fitting

  • Pierrick Legrand
  • Claire Bourgeois-Republique
  • Vincent Péan
  • Esther Harboun-Cohen
  • Jacques Levy-Vehel
  • Bruno Frachet
  • Evelyne Lutton
  • Pierre Collet
Original Paper

Abstract

Cochlear implants (CI) are devices that become more and more sophisticated and adapted to the need of patients, but at the same time they become more and more difficult to parameterize. After a deaf patient has been surgically implanted, a specialised medical practitioner has to spend hours during months to precisely fit the implant to the patient. This process is a complex one implying two intertwined tasks: the practitioner has to tune the parameters of the device (optimisation) while the patient’s brain needs to adapt to the new data he receives (learning). This paper presents a study that intends to make the implant more adaptable to environment (auditive ecology) and to simplify the process of fitting. Real experiments on volunteer implanted patients are presented, that show the efficiency of interactive evolution for this purpose.

Keywords

Interactive evolution Cochlear implants fitting Signal processing Classification HEVEA project 

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Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Pierrick Legrand
    • 1
    • 2
  • Claire Bourgeois-Republique
    • 3
  • Vincent Péan
    • 4
  • Esther Harboun-Cohen
    • 5
  • Jacques Levy-Vehel
    • 2
  • Bruno Frachet
    • 5
  • Evelyne Lutton
    • 2
  • Pierre Collet
    • 6
  1. 1.IMB, Institut de Mathématiques de BordeauxUMR CNRS 5251, Université de Bordeaux 2Bordeaux cedexFrance
  2. 2.COMPLEX Team – INRIA RocquencourtLe Chesnay cedexFrance
  3. 3.LE2I, UMR 5158 CNRSDijon cedexFrance
  4. 4.CRT InnotechBobigny cedexFrance
  5. 5.Hôpital Avicenne, Service ORLBobignyFrance
  6. 6.FDBT-LSIITILLKIRCH CedexFrance

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