# GaitIQ: Establishing a Digital Biomarker of Preclinical Alzheimer's Disease

> **NIH NIH R44** · GAITIQ, LLC · 2020 · $1,549,244

## Abstract

Early detection of pre-clinical Alzheimer’s Disease (AD) during the long latent period prior to
manifest dementia offers significant opportunities to advance the development of disease
modifying interventions and effectively slow the disease’s progression. To achieve this objective,
there is a critical need for new technologies that accelerate the development of biomarkers with
high sensitivity for underlying AD pathology. A highly promising biomarker for preclinical AD
is gait, as subtle gait changes have been correlated with elevated amyloid burden and
cortical atrophy. While even simple measures of gait speed predict incident dementia in older
adults, current research indicates that preclinical AD pathology is more precisely captured
by a combination of 3D kinematic and spatio-temporal measures. A cost-effective mobile
application that can be used in clinical trials and by healthcare personnel to capture these
parameters efficiently, combined with a validated system to translate the measures to quantifiable
AD risk in minutes, would result in a paradigm shift in availability of AD screening for at-risk
individuals.
GaitIQ™ is an innovative digital health startup company developing an online software-based
product that employs computer vision and artificial intelligence (AI) to compute clinically accurate
spatio-temporal and 3D kinematic data, from a simple video of a person walking. GaitIQTM
collaborates with The Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases at
UT Health San Antonio and Southwest Research Institute for this SBIR project.
The expected outcome is that advanced kinematic/spatio-temporal measures of gait
captured by the GaitIQTM system will reveal a sensitive and specific gait signature with high
diagnostic accuracy for pre-clinical AD in a sample of Hispanic older adults.
The project will develop and validate the capacity of GaitIQ™ to detect a digital gait biomarker
signature that distinguishes between individuals with preclinical AD and controls.
The final digital platform will be an easy-to-use, powerful tool to identify and monitor patients with
pre-clinical AD using just an iPad/tablet to video their gait and submit it for analysis in the cloud
by GaitIQTM sophisticated, proprietary analysis software.

## Key facts

- **NIH application ID:** 10078206
- **Project number:** 2R44AG060855-02
- **Recipient organization:** GAITIQ, LLC
- **Principal Investigator:** Mini Elizabeth Jacob
- **Activity code:** R44 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $1,549,244
- **Award type:** 2
- **Project period:** 2018-09-15 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10078206

## Citation

> US National Institutes of Health, RePORTER application 10078206, GaitIQ: Establishing a Digital Biomarker of Preclinical Alzheimer's Disease (2R44AG060855-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10078206. Licensed CC0.

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