Audiology services provided via connected health care
AI-assisted Diagnosis for Middle Ear Pathologies
AI-assisted Diagnosis for Middle Ear Pathologies
Remote Audiology Delivery Care-COVID19
Remote Audiology Delivery Care COVID-19
Test-retest analysis of aggregated audiometry testing data using Jacoti Hearing Center self- testing application
Test-retest analysis of aggregated audiometry testing data using Jacoti Hearing Center self-testing application
Diotic and antiphasic digits-in-noise to detect and classify types of hearing loss
Diotic and antiphasic digits-in-noise to detect and classify types of hearing loss
A simple at-home self-check to screen for aberrant loudness growth in hearing aid and cochlear implant users
A simple at-home self-check to screen for aberrant loudness growth in hearing aid and cochlear implant users
Use of air conduction thresholds to predict bone conduction asymmetry and air-bone gap
This study used machine learning methods to predict bone conduction abnormalities from air conduction pure tone audiometric thresholds.
Musi-CI: music as brain fitness in hearing training for cochlear implant users.
During the Musi-CI training methods are developed for CI users primarily to enhance music enjoyment and secondary to improve perception of daily sounds and speech.
Preliminary evaluation of the Speech Reception Threshold measured using a new language-independent screening test as a predictor of hearing loss
We developed a new, automated, language-independent speech in noise screening test, we evaluated its performance in 150 subjects against the WHO criteria for slight/mild and moderate hearing loss, and we observed an accuracy >80%, with an area under the ROC curves equal to 0.83 and 0.89, respectively.
Dynamically Masked Audiograms with Machine Learning Audiometry
Dynamically masked audiograms achieve accurate true threshold estimates and reduce test time compared to current clinical masking procedures.
Aladdin: Automatic LAnguage-independent Development of the Digits-In-Noise test
The Automatic LAnguage-independent Development of the Digits-In-Noise test (Aladdin)-project aims to create a fully automatic test development procedure for digit-in-noise hearing tests in various languages and for different target populations.
A guide to remote working in Audiology
Here is a synopsis of the new guidelines by the BAA and ManCAD about audiology care beyond COVID-19.
Making Audiology Work During COVID-19 and Beyond
De Wet Swanepoel, PhD, and James W. Hall III, PhD recently published an article about delivering audiology service in times of COVID-19.
Speech recognition apps for the hearing impaired and deaf
Speech recognition software has become increasingly sophisticated and accurate due to progress in information technology. This project aims to examine the performance of speech recognition apps and to explore which audiological tests are a representative measure of the ability of these apps to convert speech into text.
Research Agenda & Mission
Looking for questions Here’s an idea. Collect the problems in audiology that need AI solutions (Instead of solutions looking for a problem, we are looking for genuine problems looking for a solution.)…
Computational Audiology: new ways to address the global burden of hearing loss
Computational audiology, the augmentation of traditional hearing health care by digital methods, has potential to dramatically advance audiological precision and efficiency to address the global burden of hearing loss.