Claire Bourgeois-République

Interactive evolution for cochlear implants fitting

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.

An interactive evolutionary algorithm for cochlear implant fitting: first results

In a previous SAC-COMPAHEC paper[1], a method was presented using an interactive evolutionary algorithm for cochlear implants fitting.The method has recently been put to test, with very unexpected and encouraging results: in a few words, it seems that the algorithm is capable to obtain much better results than an expert practitioner in many cases.The solutions proposed by the algorithm are counter-intuitive, yet they improve speech recognition drastically. If these preliminary results are confirmed by many more cases, it could mean that experts have been deterministically tuning cochlear implants the wrong way for many years.However, it seems that the very good results obtained by the algorithm depend a lot on the acoustic environment in which the fitting is performed. A broader fitting scheme has therefore been implemented that should overcome this problem, by allowing the patient to sample typical background noises for which the prosthesis should be specifically tuned.In the future, a piece of software will be added to the cochlear implant signal processor that will automatically choose the best setting depending on the kind of sound environment picked up by the microphone.

Using an interactive evolutionary algorithm to help fitting a cochlear implant

Cochlear implants are electronic devices that stimulate directly the auditory nerve to allow totally deaf patients to hear again. This paper presents an interactive evolutionary algorithm (IEA) designed to help finding the best parameters of a cochlear implant for a specific patient.If early cochlear implants only featured one electrode, modern devices now offer up to 22 electrodes, with the hope to be able to transmit more details and help the patient hear better. The work presented in this paper shows however that having more electrodes is not necessarily better.Tests on a patient show surprisingly that some combinations of electrodes yield better results than others, with the problem that there is no real way to determine which electrode is beneficial to speech understanding and which is not.The best result obtained by the patient on a speech understanding evaluation protocol was 48.5/100 after 10 years of fitting sessions by an expert practitioner. For many reasons explained in this paper, the evaluation of the best parameter setting found by the IEA in one day was 91.5/100.

Evolutionary algorithms for a mixed stereovision uncalibrated 3D reconstruction

This paper proposes an original 3D shape reconstruction which is a mixture of the passive and active stereovision systems. Similarly to the passive stereovision systems, two cameras are used to acquire the images. As for the active stereovision methods, the detection of the points of interest (POIs) and the matching problem are solved by using a structured-light pattern projected onto the analysed object. An encoding is proposed to ease the matching procedure. Then, Evolutionary Algorithms (EAs) are designed to calculate the depth of the detected POIs. Numerous experiments are conducted to validate the different steps of the proposed method.

A Structured Light System Encoding for an Uncalibrated 3D Reconstruction Based on Evolutionary Algorithms

This paper deals with 3D shape reconstruction based on a structured-light projector and two cameras using Evolutionary Algorithms (EAs). Two main problems are solved: first, the correspondence problem (also called the stereo matching problem) which allows the matching of different views of a same point in the two images, and second, the camera calibration which takes into account the camera parameters and the camera relative locations through a fundamental matrix. Concerning the correspondence problem, the main issue is the detection of the points to be matched, i.e. the points of interest (POIs). In this paper we propose a structured pattern to be projected on the object to analyse. The structured pattern is composed of triangles with different colors and different orientations. The POIs to be matched are the vertices of the triangles. Then we define an encoding method allowing the recovery of all the POIs that are detected in both images. In previous work, we showed that EAs can be used to obtain the fundamental matrix, thus providing an uncalibrated 3D reconstruction approach. However the method processed too small a number of POIs. The proposed acquisition system allows a high number of POIs to be obtained. The initial EAs are improved to use the new set of POIs. The experiments show that the proposed encoding method allows an efficient matching. In addition, accurate 3D reconstruction results are obtained and the process converges correctly.

3D Panoramic Reconstruction with an Uncalibrated System of Stereovision Using Evolutionary Algorithms

In this paper, a new method to reconstruct a 3D panoramic shape is introduced. It is based on an uncalibrated stereovision system composed of five cameras circularly located around the object to be analysed. The method is based on the detection of interesting points and their matching from one image to another. An evolutionary algorithm provides two basic elements: on the one hand, the interesting point depth values and on the other hand, the transformation matrix between the two images. Experimental results validate the proposed method.

Automatic fitting of cochlear implants with evolutionary algorithms

This paper presents an optimisation algorithm designed to perform in-situ automatic fitting of cochlear implants.All patients are different, which means that cochlear parametrisation is a difficult and long task, with results ranging from perfect blind speech recognition to patients who cannot make anything out of their implant and just turn it off.The proposed method combines evolutionary algorithms and medical expertise to achieve autonomous interactive fitting through a Personal Digital Assistant (PDA).

Direct 3D Information Determination in an Uncalibrated Stereovision System by Using Evolutionary Algorithms

This paper proposes a 3D panoramic shape reconstruction method based on an uncalibrated stereovision system USS composed of five cameras circularly located around the object to be analysed. First, some interesting points are detected from markers placed on the object such that they are visible by two successive cameras of the USS. These points are then matched on both images acquired by a couple of successive cameras. This process is repeated for all the couples of cameras. Second, by using an evolutionary algorithm, the depth values of the different interesting points are calculated. A comparison with a traditional method based on calibrated cameras validates the accuracy of 3D information provided by the proposed method. Finally, by combining all the interesting points, a panoramic view of the object is obtained.

An Evolutionary-Based 3D Reconstruction Using an Uncalibrated Stereovision System

In this paper, we offer an original method for 3D shape reconstruction based on an uncalibrated stereovision system (USS). The USS is composed of five cameras located on an arc around the object to be analysed. The method operates in two steps. First, points of interest are detected in pairs of images acquired by two consecutive cameras of the USS and matched. Then, using evolutionary algorithms, we compute the transform matrix between the two images and the respective depths of the points of interest. The accuracy of the proposed method is validated through a comparison with the depth values obtained by a traditional method based on calibrated cameras.

Algorithme évolutionnaire interactif. Application au réglage automatique d'implant cochléaire

This paper describes an interactive evolutionary algorithm dedicated to Cochlear Implants fitting. The algorithm automatically suggests different fittings that are evaluated by the patient along predefined criteria: comfort and speech undedrstanding. The evolutionary process is guided by the evaluation of the patient. The interaction with the patient is done through a PDA (Personal Data Assistant). The main advantage to use this lightweight terminal for the evaluation is to give the patient a full autonomy, and lift all constraints (hospital, environmental, temporal...) allowing him to optimise his CI fitting in any noise environment. This work exposes the first medical application of such an algorithm for Cochlear Implant fitting. Obtained results on a patient are presented and discussed.