Interactive evolution for cochlear implants fitting

Authors:
Pierrick Legrand;Claire Bourgeois-Republique;Vincent Péan;Esther Harboun-Cohen;Jacques Levy-Vehel;Bruno Frachet;Evelyne Lutton;Pierre Collet
Affiliations:
IMB, Institut de Mathématiques de Bordeaux, UMR CNRS 5251, Université de Bordeaux 2, Bordeaux cedex, France 33076 and COMPLEX Team --- INRIA Rocquencourt, Le Chesnay cedex, France 78153;LE2I, UMR 5158 CNRS, Dijon cedex, France 21078;CRT Innotech, Bobigny cedex, France 93005;Hôpital Avicenne, Service ORL, Bobigny, France 93000;COMPLEX Team --- INRIA Rocquencourt, Le Chesnay cedex, France 78153;Hôpital Avicenne, Service ORL, Bobigny, France 93000;COMPLEX Team --- INRIA Rocquencourt, Le Chesnay cedex, France 78153;FDBT-LSIIT, ILLKIRCH Cedex, France 67412
Venue:
Genetic Programming and Evolvable Machines
Year:
2007

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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.