Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Hearing

Hearing

When we hear a sound, our nervous system is detecting sound waves—pressure waves of mechanical energy traveling through a medium. The frequency of the wave is perceived as pitch, while the amplitude is perceived as loudness.

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

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·2025

Same author

Toward Alleviating the Stigma of Hearing Aids: A Review.

Audiology research·2024

Same author

A Continuously Worn Dual Temperature Sensor System for Accurate Monitoring of Core Body Temperature from the Ear Canal.

Sensors (Basel, Switzerland)·2023

Same author

Impact of Hearing Loss and Universal Face Masking in the COVID-19 Era.

Mayo Clinic proceedings·2020

Same author

The Future of Private Practice in Audiology.

Seminars in hearing·2016

Same author

Analysis of a dual-twist Pancharatnam phase device with ultrahigh-efficiency large-angle optical beam steering.

Applied optics·2016

Search research articles

Related Experiment Video

Updated: Oct 18, 2025

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

Improving Speech Understanding and Monitoring Health with Hearing Aids Using Artificial Intelligence and Embedded

David A Fabry¹, Achintya K Bhowmik¹

¹Starkey Hearing Technologies, Eden Prairie, Minnesota.

Seminars in Hearing

|October 1, 2021

Summary

Modern hearing aids use artificial intelligence (AI) and machine learning to enhance speech understanding in noisy environments. These advancements also integrate health and wellness tracking through embedded sensors and AI.

Keywords:

artificial intelligence background noise deep neural networks embedded sensors fall detection hearing aid machine learning speech intelligibility

More Related Videos

Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages

Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages

Published on: March 24, 2023

Author Spotlight: Optimizing EAS with Long Electrodes for Enhanced Cochlear Coverage and Hearing Preservation

Author Spotlight: Optimizing EAS with Long Electrodes for Enhanced Cochlear Coverage and Hearing Preservation

Published on: October 11, 2024

Related Experiment Videos

Last Updated: Oct 18, 2025

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Asthma Detection Research Based on Voice Signal Processing and Machine Learning

Published on: July 22, 2025

Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages

Systematic Hearing Performance Evaluation Process for Adolescents with Cochlear Implantation at Early Ages

Published on: March 24, 2023

Author Spotlight: Optimizing EAS with Long Electrodes for Enhanced Cochlear Coverage and Hearing Preservation

Author Spotlight: Optimizing EAS with Long Electrodes for Enhanced Cochlear Coverage and Hearing Preservation

Published on: October 11, 2024

Area of Science:

Audiology
Artificial Intelligence
Machine Learning

Background:

Traditional hearing aids primarily focus on amplifying sound.
Background noise significantly impairs speech intelligibility for hearing aid users.
There is a growing need for hearing solutions that offer additional health benefits.

Purpose of the Study:

To explore the integration of machine learning and AI in modern hearing aids.
To detail how these technologies improve speech understanding in complex auditory environments.
To review the emerging role of hearing aids in health and wellness monitoring.

Main Methods:

Onboard hearing aid signal processing and machine learning algorithms for speech optimization.
Smartphone-based deep neural network processing for enhanced intelligibility.
Utilizing wireless hearing aid accessories to augment functionality.
Incorporating embedded sensors for health and wellness data collection.

Main Results:

AI and machine learning algorithms demonstrably improve speech understanding in background noise.
Automatic and user-driven optimization enhances speech intelligibility.
Integrated sensors enable comprehensive health and wellness tracking capabilities within hearing aids.

Conclusions:

Machine learning and AI are revolutionizing hearing aid technology, enhancing audiological performance.
Hearing aids are evolving into multi-functional devices, offering both improved hearing and health monitoring.
The future of hearing aids lies in intelligent, connected devices that support overall well-being.