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

临床前阿尔茨海默病(AD)在发病前较长潜伏期的早期发现 显性痴呆症为促进疾病的发展提供了重要机会 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 对潜在的AD病理具有很高的敏感性。一种极具前景的临床前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增加和 皮质萎缩。虽然即使是简单的步态速度测量也能预测老年人的痴呆症发生率 成人，目前的研究表明，临床前AD的病理被更准确地捕捉到 通过3D运动学和时空测量的组合。性价比高的移动设备 可以在临床试验中使用的应用程序，也可以由医护人员用来捕获 有效的参数，与经过验证的系统相结合，将测量转换为可量化的 几分钟内的广告风险，将导致高危广告筛查可用性的范式转变 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 使用计算机视觉和人工智能(AI)计算临床精确度的产品 时空和3D运动学数据，来自一个人行走的简单视频。GaitIQTM 与格伦·比格斯阿尔茨海默氏症和神经退行性疾病研究所合作 德克萨斯大学圣安东尼奥分校健康和西南研究院为这个SBIR项目。 预期的结果是先进的步态运动学/时空测量 由GaitIQTM系统捕获的步态特征将显示敏感和特定的高 西班牙裔老年人样本中临床前阿尔茨海默病的诊断准确性。 该项目将开发和验证GaitIQ™检测数字步态生物标记的能力 区分临床前AD患者和对照组的签名。 最终的数字平台将是一个易于使用的强大工具，用于识别和监控患者 仅使用iPad/平板电脑拍摄他们的步态并将其提交到云中进行分析的临床前AD 由GaitIQTM精密、专有的分析软件。

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.