SBIR/STTR Research Award

Individualized Vestibular Rehabilitation for Elderly with Self-Management and Gaming Elements

Award identifier f581f5e4add3d3728c0e6e7bbbac05b1ecd1fb9efe59c6c55a0379f21d790f00Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$1,473,956

Program and phase

SBIR · Phase II

Award year

2020

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
CFD Research Corporation
Proposal award date
2020-09-10
Contract end date
2022-08-31
UEI
V3KCP1HNFM33
Solicitation number
PA19-272
Topic code
NIDCD

Research abstract

Project Summary/Abstract: Vestibular rehabilitation has been proven to be effective in reducing dizziness and falls in older adults, but patient adherence is a major problem. Recent research shows that less than half of patients complete their rehabilitation. Some of the main reasons for this are the numerous visits that are required and accessibility. In particular for older individuals who experience dizziness and/or falls, it may be difficult to travel to attend rehabilitation sessions. Additionally, rehabilitation programs become expensive in terms of equipment and health professional’s time. Programs may also not be available to all who may benefit because of geographical limitations. Previous research has shown that remote monitoring and gaming elements have great potential to solve these issues, even in an older population. However, current solutions are generic and effectiveness can be inconsistent. The overall goal of this project is to develop a vestibular rehabilitation app to be used by older adults at home. The app will improve adherence through gaming, self-management, and remote monitoring. Patients will use low-cost sensors placed on their bodies (head and waist) to play the games on the app. This allows simultaneous monitoring of patient progress while performing the exercises. This data can be shared with a clinician via email or the cloud, allowing the patient to perform the rehabilitation at their home and the clinician to monitor how well the patients performed their exercises. The vestibular rehabilitation components are packaged in a phone and tablet app that is easy to navigate for older individuals and has a modular design that allows individualized rehabilitation. By improving patient engagement and enjoyment, rehabilitation adherence should be improved as well. Phase I demonstrated feasibility of this approach. In Phase II, games will be added to cover a full at-home rehabilitation session and improve usability of the app. In addition, machine learning algorithms will be developed to provide real-time feedback if exercises are performed incorrectly. This ensures patients will perform their exercises correctly when at home. As in Phase I, clinical collaborators will provide continued guidance and testing throughout development to ensure clinical relevance and promote adoption during commercialization. This project uses a novel approach in that it develops rehabilitation games specifically designed for vestibular rehabilitation through a mobile app tailored for an older population. Current gaming approaches for rehabilitation typically use existing or commercial games. The use of sensors for remote monitoring is also novel in this area and allows patients to perform rehabilitation at their home, while being monitored by a clinician. This project is therefore likely to have a high clinical impact. It will advance clinical practice, make vestibular rehabilitation more accessible to older individuals, and help adherence to programs. Successful implementation of this program will reduce falls and improve quality of life of for patients.Project Narrative: The overall goal of this project is to develop an app for older individuals that will improve accessibility of vestibular rehabilitation and that will improve compliance compared to current rehabilitation programs. The proposed effort uses a novel approach that combines low-cost inertial sensors and machine learning algorithms with mobile device technology to measure performance, provide real-time feedback, and present data in a comprehensible way to the clinician via email or the cloud, removing the patients’ need to travel for rehabilitation sessions. These features are packaged in an app that is appropriate for and appealing to older users to improve compliance, and uses novel gaming elements specifically developed for vestibular rehabilitation rather than repurposing existing commercial games designed for younger users and entertainment.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

947 SBIR/STTR records share this UEI (1987–2026). Reported award amounts total $350,893,199. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense, National Aeronautics and Space Administration, Department of Health and Human Services, National Science Foundation, Department of Commerce, Department of Energy

Agency intelligence

Department of Health and Human Services

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