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Smartphone Machine Learning Speech Enhancement System for Hearing Aid Devices for the Underserved and Rural Populations

Award Number: R43AG088131
ORGANIZATION: NATIONAL INSTITUTE ON AGING
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 08/15/2024
PERIOD OF PERFORMANCE END DATE: 07/31/2026

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Smartphone Machine Learning Speech Enhancement System for Hearing Aid Devices for the Underserved and Rural Populations - Abstract This proposal responds directly to the purpose of the RFA-MD-23-003 SBIR Funding Opportunity Announcement (FOA). Nearly 44 million Americans experience hearing loss, but as much as 86% of adults who could benefit from hearing aid devices (HAD) do not use them. Untreated hearing loss is almost twice as prevalent in rural areas. More than 46 million people live in rural America, but these communities face significant barriers and delays in accessing care and experience a lack of providers for audiology services. The average retail price of HADs was $4,700, making it prohibitively expensive for the rural and minority populations who have lower incomes. Hearing loss is also highly prevalent in black and Latino/Hispanic communities and growing, but older black adults were 58% and Mexican American older adults were 78% less likely to use HADs, due to reasons of high cost and lack of insurance coverage. Aside from cost, concerns about comfort, effectiveness and satisfaction are the other significant barriers to HAD usage. The FDA made over-the-counter (OTC) HADs a reality in 2022, creating a new hearing option for many adults with perceived mild to moderate hearing loss. The introduction of OTC HADs is set to increase accessibility and affordability of hearing care for underserved populations. A common complaint of HAD users is the HAD inability to reduce ambient background noise completely, instead, the background noise is amplified along with the human voice. Speech enhancement algorithms continue to be developed and the most advanced found on high-end costly HAD platforms. This project will develop machine learning (ML) based smartphone software with a Graphical User Interface (GUI), to bring these advanced speech enhancement and noise reduction algorithms to the OTC HAD users. With smartphone assistive software and the predictive power of ML, our proposed solution to reduce background noise and enhance speech, will significantly improve OTC HAD accessibility, affordability, and acceptance, thus benefitting the rural and minority populations the most.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2025 ( Subtotal = $0 )
2025	2024	APPLIED UNIVERSAL DYNAMICS, CORP	23875 CHESTNUT DR	LORETTO	MN	55357	HENNEPIN	USA	Aging Research	000	1	8/14/2025	NEW	$0
														Subtotal = $0

Issue Date FY: 2024 ( Subtotal = $295,825 )
2024	2024	APPLIED UNIVERSAL DYNAMICS, CORP	23875 CHESTNUT DR	LORETTO	MN	55357	HENNEPIN	USA	Aging Research	000	1	8/8/2024	NEW	$295,825
														Subtotal = $295,825

Grand Total All Awards = $295,825

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Smartphone Machine Learning Speech Enhancement System for Hearing Aid Devices for the Underserved and Rural Populations

Award Number: R43AG088131

ORGANIZATION: NATIONAL INSTITUTE ON AGING

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 08/15/2024

PERIOD OF PERFORMANCE END DATE: 07/31/2026

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