Automatic analysis of cochlear response using electrocochleography signals during cochlear implant surgery

Christofer Bester

Abstract:

Cochlear implants (CIs) provide an opportunity for the hearing impaired to perceive sound
through electrical stimulation of the hearing (cochlear) nerve. However, there is a high risk
of losing a patient’s natural hearing during CI surgery, which has been shown to reduce
speech perception in noisy environments as well as music appreciation. This is a major bar￾rier to the adoption of CIs by the hearing impaired. Electrocochleography (ECochG) has
been used to detect intra-operative trauma that may lead to loss of natural hearing. There is
early evidence that ECochG can enable early intervention to save natural hearing of the
patient. However, detection of trauma by observing changes in the ECochG response is typ￾ically carried out by a human expert. Here, we discuss a method of automating the analysis
of cochlear responses during CI surgery. We establish, using historical patient data, that
the proposed method is highly accurate (�94% and �95% for sensitivity and specificity
respectively) when compared to a human expert. The automation of real-time cochlear
response analysis is expected to improve the scalability of ECochG and improve patient
safety