I-Corps: Digital Biomarkers Combined with Wearable Devices to Monitor Alzheimer’s Disease and other Neurological Disorders

I-Corps：数字生物标记与可穿戴设备相结合，监测阿尔茨海默病和其他神经系统疾病

• 批准号: 2127407
• 负责人: Devin Collins
• 金额: $ 5万
• 依托单位: University of North Carolina at Charlotte
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-01 至 2022-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2127407&HistoricalAwards=false
• 关键词: Corps; Digital; Biomarkers; Combined; Wearable

The broader impact/commercial potential of this I-Corps project is the development of a cloud-based, predictive analytics platform to identify, develop, and validate digital biomarkers that identify early signs of neurodegeneration and other significant health-related concerns related to aging. Existing methods of collecting longitudinal data from aging populations for clinical and nonclinical research are slow, expensive, labor-intensive and often introduce flawed data. This project may improve research with qualitative and quantitative behavioral and biophysical information using passive and unobtrusive patient-generated data aggregated in real-life environments using smartwatches. At scale, this platform may be used to build models that predict disease onset in at-risk populations and help millions of individuals around the world identify means to delay the onset or slow the progression of Alzheimer’s disease and related dementias. In addition, this platform may enable pharmaceutical companies with licensed access to data to conduct focused clinical trials in aging populations. The proposed technology may improve health-related applications offered by wearable/smartwatch manufacturers, and may provide health-concerned individuals with personalized low-cost behavior modification intervention recommendations in order to delay, prevent, or slow the progression of neurogenerative diseases and other health issues. This I-Corps project is based on the development of analytical models deployable within the cloud to identify, measure, and predict those behavioral and clinical features impacting people at high-risk for Alzheimer’s Disease and related dementias. The proposed technology is an end-to-end patient monitoring solution that benefits patients, caregivers and medical researchers by combining data from widely available consumer smartwatches with a cloud-based analytics and artificial intelligence platform to deliver improved health and behavior information. This proposed software solution advances high-frequency data aggregation to a centralized cloud-based platform where it is possible to generate insights and identify, develop, and clinically validate digital biomarkers for Alzheimer’s disease, dementias, and other potential illnesses and comorbidities in aging populations. The development of this prototype artificial intelligence-driven platform may provide a solution to passively and unobtrusively capture patient-generated data beyond conventional clinical trials, in real-life settings, and advance capabilities to analyze digital health information from broad demographic populations.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.

这个i-Corps项目的更广泛的影响/商业潜力是开发一个基于云的预测性分析平台，以识别、开发和验证数字生物标记物，识别神经退化的早期迹象和其他与衰老相关的重大健康问题。现有的从老龄化人口中收集纵向数据用于临床和非临床研究的方法速度慢、成本高、劳动密集型，而且往往会引入有缺陷的数据。该项目可能会使用在现实生活环境中使用智能手表收集的被动和不引人注目的患者生成的数据来改进研究，获得定性和定量的行为和生物物理信息。在规模上，这个平台可以用来建立预测高危人群疾病发病的模型，并帮助世界各地数百万人找到延缓阿尔茨海默病和相关痴呆症发病或进展的方法。此外，这一平台可能使获得数据许可的制药公司能够在老龄化人口中进行有针对性的临床试验。拟议的技术可以改进可穿戴/智能手表制造商提供的与健康相关的应用，并可以为关注健康的个人提供个性化的低成本行为矫正干预建议，以延迟、预防或减缓神经生成性疾病和其他健康问题的进展。这个i-Corps项目基于可部署在云中的分析模型的开发，以识别、测量和预测那些影响阿尔茨海默病和相关痴呆高危人群的行为和临床特征。这项拟议的技术是一种端到端的患者监控解决方案，通过将来自广泛可用的消费者智能手表的数据与基于云的分析和人工智能平台相结合，提供更好的健康和行为信息，从而使患者、护理人员和医学研究人员受益。这一建议的软件解决方案将高频数据聚合推进到基于云的中央平台，在该平台上可以产生洞察力，并识别、开发和临床验证阿尔茨海默病、痴呆症和老龄化人口中其他潜在疾病和合并症的数字生物标志物。这一由人工智能驱动的原型平台的开发可能提供一种解决方案，以被动和隐蔽的方式在现实生活环境中捕获传统临床试验之外的患者生成的数据，并提升从广泛人口群体中分析数字健康信息的能力。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。