Psychophysical based channel selection

  • Research type

    Research Study

  • Full title

    Psychophysics for Optimising Cochlear Implant Channel Selection

  • IRAS ID

    224548

  • Contact name

    Patrick Boyle

  • Contact email

    pjb79@cam.ac.uk

  • Sponsor organisation

    University of Cambridge

  • Duration of Study in the UK

    0 years, 5 months, 28 days

  • Research summary

    Cochlear implants (CIs) are devices that provide some hearing to people who have profound or total hearing loss via electrical stimulation of the auditory nerve. CIs work by filtering the sound picked up by a microphone into several frequency bands or “channels”. The pattern of amplitude modulation in each channel is extracted and used to stimulate a single electrode within the cochlea.

    The benefit obtained from a CI varies widely across users. Poor performance may occur when one or more electrodes stimulates a place in the cochlea where there are few or no surviving neural processes. The channels driving those electrodes are referred to as “bad” channels. A CI user may perform better if the bad channels are deactivated. The experiment proposed here will evaluate a method for identifying bad channels.

    The “target signal” will be amplitude modulation applied to a sinusoidal carrier frequency that falls at the centre frequency of the “target channel”. The task will be discriminate a change in the pattern of amplitude modulation in the target signal. Interfering sounds will also be amplitude modulated sounds, but the carrier frequencies of these sounds will be chosen so that they stimulate channels adjacent to the target channel. We will measure the ability to detect changes in the target amplitude modulation as a function of the depth of amplitude modulation on the adjacent interfering channels channels. This process will be repeated using each channel in turn as the target channel. Bad channels will be identified as those that are strongly affected by the amplitude modulation in the interfering channels.

    Having identified any bad channels for a specific CI user, we will assess whether deactivating the bad channels improves the ability to understand speech using the CI.

  • REC name

    East Midlands - Nottingham 1 Research Ethics Committee

  • REC reference

    17/EM/0222

  • Date of REC Opinion

    28 Jun 2017

  • REC opinion

    Further Information Favourable Opinion