Audiology services provided via connected health care
We present an Alexa skill that performs a speech-in-noise listening test with matrix sentences. The skill is evaluated with four subject groups and in three different acoustic conditions.
In a first of its kind study, we aimed to determine the accuracy and reliability of sound-level monitoring earphones and the effect of smartphone feedback as an intervention to encourage safe listening use among young people.
Using a Naive Bayes classifier, we could show that twelve different activities were classified above chance.
We present an automated program for aligning stimulus-response phonemes collected from speech testing in order to visualize speech perception errors in individuals with hearing loss
This study developed an application software that periodically records the course of Meniere's disease patients through the performance of automated, binaural audiometric tests.
Exploiting spontaneous messages of Reddit users discussing tinnitus, this work identifies the main topics of interest, their heterogeneity, and how they relate to one another based on cooccurrence in users' discussions; to enhance patient-centered support.
A RCT was undertaken on a US populations indicating the value of an CBT internet-intervention for both reducing tinnitus distress, tinnitus comorbidities and managing the anxiety associated with the pandemic.
A new online hearing screening procedure integrated with artificial intelligence for the identification of slight/mild hearing loss in older adults.
AI-assisted Diagnosis for Middle Ear Pathologies
Remote Audiology Delivery Care COVID-19
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
A simple at-home self-check to screen for aberrant loudness growth in hearing aid and cochlear implant users
This study used machine learning methods to predict bone conduction abnormalities from air conduction pure tone audiometric thresholds.
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.
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 achieve accurate true threshold estimates and reduce test time compared to current clinical masking procedures.
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.
Here is a synopsis of the new guidelines by the BAA and ManCAD about audiology care beyond COVID-19.
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 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.
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, 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.
