Digits-in-noise test in Brazilian Portuguese: preliminary study in schoolchildren
DIN had a better signal-to-noise ratio in antiphasic mode in schoolchildren with less hearing loss
Audiology services provided via connected health care
The Global Burden of Hearing Loss and Future Hearing Aids
This post covers the VCCA discussions on hearing devices of the future, and hearing diagnostics and services of the future. Both specifically discussed solutions and ideas for low-income countries.
Illustration of the differences between the clinical test and speech audiometry at home, which can be performed with a smart speaker.
Hearing test using smart speakers: Speech audiometry with Alexa
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.
dbTrack (Westone) technology
Sound-Level monitoring earphones with smartphone feedback as an intervention to promote healthy listening behaviors in young adults
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.
Figure 1 A: Data streamed from the hearables to a PC running a recording script. B. Data from two different activities, recorded over 5 minutes each. C. Results from a classification using Naïve Bayes classification and a 5-fold cross-validation procedure.
Automatic detection of human activities from accelerometer sensors integrated in hearables
Using a Naive Bayes classifier, we could show that twelve different activities were classified above chance.
Results for V1 with both cochlear implant (CI) and hearing aid (HA) (top), CI only (middle) and HA only (bottom) in response to a set of 30 sentences extracted from Speech Banana auditory training app
Visualization of speech perception errors through phoneme alignment
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
A) Flowchart of the "Meniere Calendar" application, B) Final psychometric function fitted to data from a normal hearing participant (left) and a Meniere's patient (right). C) Screenshots of the application's environment
Systematic monitoring of Meniere’s disease: A smartphone-based approach for the periodical assessment of audiometric measures and fluctuating symptoms
This study developed an application software that periodically records the course of Meniere's disease patients through the performance of automated, binaural audiometric tests.
Topics found with Latent Dirichlet Allocation on 100k Reddit posts. The top rectangle of each block is the topic's name assessed through the algorithm's output: the lemmatised words shown in the middle rectangle. The proportion of messages that mention the topic is displayed in the lower rectangle.
What can we learn about tinnitus from social media posts?
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.
Outline of the RCT
Outcomes and experiences of delivering an internet-based intervention for tinnitus during the COVID-19 pandemic
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.
Evaluation of multivariate classification algorithms for hearing loss detection through a speech-in-noise test
A new online hearing screening procedure integrated with artificial intelligence for the identification of slight/mild hearing loss in older adults.
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.
Final masked AMLAG results for one participant (127) with a left cochlear implant and no residual hearing. Red diamonds denote unheard tones and blue pluses denote heard tones. The most intense tones at lower frequencies in the left ear were effectively masked.
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.
Flow Chart for service delivery options during COVID-19
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.
Example of a no-touch audiology service journey.
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.)…
Source: https://www.stripepartners.com/our_writing_article/the-age-of-the-ear/
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.