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

GaitIQ：建立临床前阿尔茨海默病的数字生物标记

• 批准号: 10078206
• 负责人: Mini Elizabeth Jacob
• 金额: $ 154.92万
• 依托单位: GAITIQ, LLC
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-15 至 2022-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10078206
• 关键词: 3-Dimensional; Adult; Advanced Development; Alzheimer disease screening; Alzheimer' s Disease; Alzheimer' s disease pathology; Alzheimer' s disease risk; Amyloid; Artificial Intelligence; Big Data Methods; Biological Markers; Biomechanics; Brain imaging; Clinic; Clinical; Clinical Research; Clinical Trials; Cognitive; Collaborations; Computer Vision Systems; Computer software; Data; Dementia; Development; Devices; Disease; Disease Progression; Early Diagnosis; Elderly; Gait; Gait speed; Gold; Health; Health Personnel; Hispanics; Impaired cognition; Individual; Institutes; Intervention; Legal patent; Machine Learning; Magnetic Resonance Imaging; Measures; Methods; Motion; Neurobehavioral Manifestations; Neurodegenerative Disorders; Outcome; Patient Monitoring; Patients; Persons; Phase; Population Heterogeneity; Positron-Emission Tomography; Research; Research Institute; Risk; Risk stratification; Sampling; Screening procedure; Small Business Innovation Research Grant; Structure; System; Tablets; Technology; Testing; Translating; United States National Institutes of Health; Walking; base; biomarker development; care providers; cerebral atrophy; cloud based; cognitive testing; cost; cost effective; deep learning; diagnostic accuracy; digital; disorder control; effectiveness validation; follow-up; gait examination; human data; indexing; innovation; kinematics; machine vision; mobile application; new technology; novel; pre-clinical; predictive signature; spatiotemporal; tool; β-amyloid burden

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.

在阿尔茨海默氏病 (AD) 出现之前的较长潜伏期内及早发现 痴呆症明显提供了促进疾病发展的重要机会 修改干预措施并有效减缓疾病的进展为了实现这一目标， 迫切需要新技术来加速生物标记物的开发 对潜在 AD 病理学具有高敏感性，是一种非常有前途的临床前 AD 生物标志物。 是步态，因为微妙的步态变化与淀粉样蛋白负荷升高相关， 即使是简单的步态速度测量也可以预测老年人的痴呆症。 成人，当前的研究表明临床前 AD 病理学可以更精确地捕获 通过 3D 运动学和时空测量的组合 具有成本效益的移动设备。 可用于临床试验并由医护人员捕获这些信息的应用程序 有效地调整参数，结合经过验证的系统，将测量结果转化为可量化的结果 AD 风险在几分钟内就会出现，这将导致针对高危人群的 AD 筛查可用性发生范式转变 个人。 GaitIQ™ 是一家创新的数字健康初创公司，开发基于在线软件的 采用计算机视觉和人工智能 (AI) 进行临床准确计算的产品 来自人行走的简单视频的时空和 3D 运动学数据。 与格伦比格斯阿尔茨海默病和神经退行性疾病研究所合作 UT Health San Antonio 和西南研究所合作开展此 SBIR 项目。 预期结果是先进的步态运动学/时空测量 GaitIQ™ 系统捕获的数据将揭示敏感且特定的步态特征，具有高 西班牙裔老年人样本中临床前 AD 诊断的准确性。 该项目将开发并验证 GaitIQ™ 检测数字步态生物标记的能力 区分临床前 AD 个体和对照个体的签名。 最终的数字平台将成为一个易于使用、功能强大的工具，用于识别和监测患者 临床前 AD 仅使用 iPad/平板电脑来录制步态并将其提交到云端进行分析 通过 GaitIQTM 先进的专有分析软件。