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Feasibility of a Novel Freezing of Gait Detection Framework for Adaptive Cueing in Parkinson's Disease

Award Number: R21EB039456
ORGANIZATION: NATIONAL INSTITUTE Of BIOMEDICAL IMAGING & BIOENGINEERING
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 08/18/2026
PERIOD OF PERFORMANCE END DATE: 05/31/2029

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Feasibility of a Novel Freezing of Gait Detection Framework for Adaptive Cueing in Parkinson's Disease - Freezing of Gait (FoG) is a sudden inability to walk that affects most people with advanced Parkinson's disease (PD) and is a primary cause of PD-related falls in older adults. While external cueing (sounds, vibrations, visual lines) can alleviate FoG, closed-loop systems that cue only when needed remain elusive because current FoG detectors lack accuracy, specificity, and real-world generalizability. The long-term goal of this research program is to develop reliable, “as-needed” cueing systems that reduce falls and preserve independence. This exploratory R21 evaluates the feasibility of an advanced FoG-detection framework – using better quality data to train a more context-aware model – built on two innovations. Aim 1 leveerages generative artificial intelligence (AI) models to synthesize high-fidelity inertial measurement unit (IMU) sensor data representing FoG, walking, and voluntary stopping. It is hypothesized that augmenting training data with these synthetic samples will significantly improve FoG detection algorithm performance, robustness, and generalization to external test sets compared to using original data or simpler augmentation techniques. Aim 2 characterizes oculomotor biomarkers captured with a lightweight wearable eye tracker. It is hypothesized that integrating gaze, blink, and pupil features with IMU signals will enhance FoG-detection sensitivity and reduce false alarms when voluntary stops occur. A prospective dataset of synchronized IMU and eye-tracking recordings from 25 adults with PD who experience daily FoG will support both aims. Successful completion will yield a proof-of-concept for a more robust detector, validated generative AI and eye-tracking methods, and a publicly available multimodal FoG dataset and codebase. By establishing a new framework for FoG detection, this project provides the foundation for clinically deployable, closed-loop cueing systems and aligns with the National Institute on Aging's mission to help older adults remain safe and independent.


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: 2026 ( Subtotal = $218,869 )
2026	2026	CASE WESTERN RESERVE UNIVERSITY	10900 EUCLID AVE	CLEVELAND	OH	44106	CUYAHOGA	USA	Discovery and Applied Research for Technological Innovations to Improve Human Health	000	1	8/18/2026	NEW	$218,869
														Subtotal = $218,869

Grand Total All Awards = $218,869

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Feasibility of a Novel Freezing of Gait Detection Framework for Adaptive Cueing in Parkinson's Disease

Award Number: R21EB039456

ORGANIZATION: NATIONAL INSTITUTE Of BIOMEDICAL IMAGING & BIOENGINEERING

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

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

PERIOD OF PERFORMANCE START DATE: 08/18/2026

PERIOD OF PERFORMANCE END DATE: 05/31/2029

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