I-corps: translation potential of eye movement patterns as early indicators of alzheimer's disease

Ended Project Grant Awarded Last action

Award ID
2444897
Recipient
Awarding agency
Obligated
$50,000

Award facts

Assistance listing
47.084 NSF Technology, Innovation, and Partnerships
Completion date
Place of performance
Canton, NY 13617, USA

Award details come from USAspending.gov.

Description

As the agency reported it.

Abstract
The broader impact of this I-corps project is the development of a non-invasive eye-tracking system designed for the early detection of alzheimer?S disease (ad). Current diagnostic methods used to detect ad such as magnetic resonance imaging (MRI) and positron emission tomography (pet) scans are expensive and inaccessible for many, particularly in under-resourced areas. The new technology aims to change how ad is diagnosed by enabling healthcare providers to identify cognitive decline at its earliest stages, with the goal of improving patient outcomes. By offering a more affordable and user-friendly solution, this system has the potential to be integrated into routine healthcare settings, making early ad detection more widely available. In addition, this eye-tracking system may meet the growing demand for diagnostic tools in neurology, with applications extending to both clinical and research environments. This I-corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of an advanced eye-tracking technology integrated with machine learning algorithms to diagnose alzheimer?S disease (ad). The technology leverages bidirectional long short-term memory (BI-LSTM) networks and attention mechanisms, and analyzes subtle changes in eye movement patterns that are indicative of early cognitive decline associated with alzheimer?S disease. Preliminary research has demonstrated that changes in ocular biomarkers may serve as reliable early indicators of ad, and this system capitalizes on that discovery. Through technical validation, the project has shown promising results in accurately detecting early signs of ad, offering a non-invasive alternative to traditional neuroimaging and cognitive assessments. The technology combines machine learning with practical, real-world applications, offering a solution for early diagnosis in neurodegenerative diseases. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.- subawards are not planned for this award.

Quick answers

Who received award 2444897?

2444897 was awarded to The Research Foundation For The State University Of New York by National Science Foundation on November 15, 2024.

How much is award 2444897 worth?

$50,000 has been obligated on 2444897.

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