Otoacoustic emmisions
Project ID: 2228bd1235 (You will need this ID for your application)
Research Theme: Healthcare Technologies
UCL Lead department: Ear Institute
Lead Supervisor: Torsten Marquardt
Project Summary:
Hearing impairment is the most common disability, affecting 1 in 5 persons above an age of 60. Hearing loss is also proven to have links to dementia. Sadly, treatments today are largely limited to hearing aids. But new strategies are now on the horizon! Pharmacological treatments of hearing impairment require differential diagnostic tests to understand the patient-specific underlying pathology. This remains problematic because the cochlea is encased deep into the skull and is therefore difficult to access. The analysis of otoacoustic emissions (OAEs) is one way to test the function of the cochlea, but to date, only basic OAE measurements have found their way into the clinic. OAEs arise due to nonlinear electromechanical processes inside the healthy cochlea and can be measured non-invasively with a miniature microphone inside the ear canal. There are different types of OAEs, including spontaneous OAEs and OAEs in response to various kinds of acoustic and electrical stimulation. Many questions remain about their complex generation mechanism and transmission to the ear canal. For an improved understanding of their information-rich, complex characteristics, better acoustic instrumentation and advanced analysis techniques are crucial to enable their full diagnostic potential as a non-invasive diagnostic tool that is needed for upcoming treatments. Working within a small team of renowned cochlear experts, and combining simultaneous OAE measurements and nanometre-scale vibration measurements made inside the cochlea (using the latest in-house developed OCT-technology), you will develop a detailed model of OAE generation, devise new stimulation paradigms and use this to engineer novel acoustic instrumentation for future use in new diagnostic OAE tests. We are looking for applicants with a solid knowledge in Signals & Systems and good programming skills, who are interested in multidisciplinary research combining physiological experiments, modelling, and engineering.