AIMC Topic: Hearing Aids
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Deaf futurity: designing and innovating hearing aids.
Medical humanities
Jan 2, 2025
One of the tenets of a posthuman vision is the eradication of disability through technology. Within this site of 'no future', as Alison Kafer describes, the disabled body is merged with artificial intelligence technology or transformed into a prosthe...
Use of Hearing Aids Embedded with Inertial Sensors and Artificial Intelligence to Identify Patients at Risk for Falling.
Otology & neurotology : official publication of the American Otological Society, American Neurotology Society [and] European Academy of Otology and Neurotology
Dec 17, 2024
OBJECTIVE: To compare fall risk scores of hearing aids embedded with inertial measurement units (IMU-HAs) and powered by artificial intelligence (AI) algorithms with scores by trained observers.
Artificial intelligence enabled smart mask for speech recognition for future hearing devices.
Scientific reports
Dec 3, 2024
In recent years, Lip-reading has emerged as a significant research challenge. The aim is to recognise speech by analysing Lip movements. The majority of Lip-reading technologies are based on cameras and wearable devices. However, these technologies h...
Deep learning-based auditory attention decoding in listeners with hearing impairment.
Journal of neural engineering
May 22, 2024
This study develops a deep learning (DL) method for fast auditory attention decoding (AAD) using electroencephalography (EEG) from listeners with hearing impairment (HI). It addresses three classification tasks: differentiating noise from speech-in-n...
Optical Microphone-Based Speech Reconstruction System With Deep Learning for Individuals With Hearing Loss.
IEEE transactions on bio-medical engineering
Nov 21, 2023
OBJECTIVE: Although many speech enhancement (SE) algorithms have been proposed to promote speech perception in hearing-impaired patients, the conventional SE approaches that perform well under quiet and/or stationary noises fail under nonstationary n...
Restoring speech intelligibility for hearing aid users with deep learning.
Scientific reports
Feb 15, 2023
Almost half a billion people world-wide suffer from disabling hearing loss. While hearing aids can partially compensate for this, a large proportion of users struggle to understand speech in situations with background noise. Here, we present a deep l...
Assessing outcomes of ear molding therapy by health care providers and convolutional neural network.
Scientific reports
Sep 9, 2021
Ear molding therapy is a nonsurgical technique to correct certain congenital auricular deformities. While the advantages of nonsurgical treatments over otoplasty are well-described, few studies have assessed aesthetic outcomes. In this study, we comp...
Speech signal enhancement in cocktail party scenarios by deep learning based virtual sensing of head-mounted microphones.
Hearing research
Jun 17, 2021
The cocktail party effect refers to the human sense of hearing's ability to pay attention to a single conversation while filtering out all other background noise. To mimic this human hearing ability for people with hearing loss, scientists integrate ...
Environmental Noise Classification Using Convolutional Neural Networks with Input Transform for Hearing Aids.
International journal of environmental research and public health
Mar 27, 2020
Hearing aids are essential for people with hearing loss, and noise estimation and classification are some of the most important technologies used in devices. This paper presents an environmental noise classification algorithm for hearing aids that us...
Cascade recurring deep networks for audible range prediction.
BMC medical informatics and decision making
May 18, 2017
BACKGROUND: Hearing Aids amplify sounds at certain frequencies to help patients, who have hearing loss, to improve the quality of life. Variables affecting hearing improvement include the characteristics of the patients' hearing loss, the characteris...
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