LifeBio-ALZ: AI driven digital biomarker engine leveraging natural conversation to widely scale accessibility for early detection and assessment of Alzheimers disease progression

LifeBio-ALZ:人工智能驱动的数字生物标记引擎,利用自然对话来广泛扩展可访问性,以早期检测和评估阿尔茨海默病的进展

基本信息

  • 批准号:
    10381308
  • 负责人:
  • 金额:
    $ 44.85万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2021
  • 资助国家:
    美国
  • 起止时间:
    2021-09-30 至 2023-08-31
  • 项目状态:
    已结题

项目摘要

Alzheimer’s Disease (AD) is one of the most common forms of dementia to occur in elderly populations, affecting over 30 million individuals worldwide. As the U.S. elderly population continues to increase, AD incidence rises as well, as there is no neuroprotective therapy or cure. Common symptoms include memory loss, cognitive impairment, disorientation, and psychiatric issues. Traditionally, diagnosis is achieved through a combination of clinical criteria such as neurological examination, mental status tests & brain imaging. However, these strategies are challenging for detection of early AD or patients with mild symptoms, specifically during the mild cognitive impairment (MCI) stage. Mental status tests & subjective journals, kept by patients or caregivers, can track AD progression, but have low sensitivity and reliability. The most strongly established biomarkers for AD, including amyloid beta, tau protein, & phosphorylated tau, are all obtained thru CSF requiring invasive lumbar puncture. The LifeBio-ALZ technology will provide a convenient and accessible, yet comprehensive digital biomarker and analytics suite to detect & assess Alzheimer’s progression. The platform will integrate a suite of assessment domains all seamlessly captured through a single, patient-centric app that engages users in natural video chat conversation via smart digital assistant. During brief, but regular sessions, an individual answers questions following a smart sequence to evaluate awareness, engagement, cognition, reaction time, speech patterns, & emotional state. The platform will record audio/video during the conversation. Type and timing of assessments, as well as specific questions will be adaptively modulated based on AD stage, personal demographics and previous analytics to minimize user burden while still providing rich data for algorithms. Quantitative features across multiple domains will be extracted from digital speech and eye movements, and then used as inputs to an AI engine to detect and assess Alzheimer’s’ disease progression. Data will be aggregated in secure cloud storage with clinician access to dashboard visualization tools. Phase I will demonstrate core feasibility. Development will build on a strong tech foundation of an existing LifeBio platform to increase likelihood of success. Currently, LifeBio is deployed in several formats including web, phone, & mobile apps to record life histories of people reaching advanced age or facing life-threatening illnesses or memory loss. Natural language processing tools parse information into life stories shared by family or used by staff to personalize engagement in care facilities. While the existing tech provides a base, significant enhancements will be executed in Phase I. More specifically, Phase I tasks will first update platform architecture to integrate novel data domains, build on smart sequenced multidimensional questions, and enhance patient workflow interfaces. Once the enhanced app passes all technical verification testing, it will be deployed in a field data collection and usability study with wide ranging AD patient demographics and stages. Finally, collected data will be used to build and validate an AI engine for detection and assessment of Alzheimer’s progression.
阿尔茨海默病(AD)是老年人群中最常见的痴呆症之一, 影响到全球3000多万人。随着美国老年人口的持续增加,AD的发病率 也会上升,因为没有神经保护性疗法或治愈方法。常见症状包括记忆力丧失、认知能力下降 精神障碍、定向障碍和精神问题。传统上,诊断是通过组合以下各项来实现的 临床标准,如神经学检查、精神状态测试和脑成像。然而,这些战略 对于检测早期AD或有轻微症状的患者具有挑战性,特别是在轻度认知障碍期间 损害(MCI)期。精神状态测试&由患者或照顾者保存的主观日记可以跟踪AD 进展性差,但敏感性和可靠性低。AD最可靠的生物标记物,包括 淀粉样β蛋白、tau蛋白和磷酸化tau都是通过脑脊液获得的,需要有创性的腰椎穿刺术。 LifeBio-ALZ技术将提供一个方便、可访问但全面的数字生物标记物 和分析套件,以检测和评估阿尔茨海默氏症的进展。该平台将整合一套评估 通过单个以患者为中心的应用程序无缝捕获所有域名,该应用程序可让用户参与自然的视频聊天 通过智能数字助理进行对话。在简短但定期的会议中,个人回答问题 遵循智能顺序来评估意识、参与度、认知度、反应时间、言语模式和 情绪状态。该平台将在对话过程中录制音频/视频。评估的类型和时间, 以及特定的问题将根据AD阶段、个人人口统计和 以前的分析将用户负担降至最低,同时仍为算法提供丰富的数据。数量特征 将从数字语音和眼动中提取跨多个领域的信息,然后用作输入 一个人工智能引擎,用于检测和评估阿尔茨海默氏症的疾病进展。数据将在安全的云中聚合 允许临床医生访问仪表板可视化工具的存储。 第一阶段将展示核心可行性。开发将建立在现有的强大技术基础上 LifeBio平台,增加成功的可能性。目前,LifeBio以几种格式部署,包括Web、 手机和移动应用程序,用于记录人到高龄或面临危及生命的疾病的生活史 或者是失忆。自然语言处理工具将信息解析为家庭共享或使用的生活故事 由工作人员在护理设施中进行个性化参与。虽然现有技术提供了基础,但意义重大 增强功能将在第一阶段执行。更具体地说,第一阶段任务将首先更新平台架构 集成新的数据域,构建智能排序的多维问题,并增强患者的能力 工作流界面。一旦增强的应用程序通过所有技术验证测试,它将部署在现场 数据收集和可用性研究与广泛的AD患者的人口统计和阶段。最后,收集到的数据 将用于构建和验证人工智能引擎,以检测和评估阿尔茨海默氏症的进展。

项目成果

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Lisbeth Sanders其他文献

Lisbeth Sanders的其他文献

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{{ truncateString('Lisbeth Sanders', 18)}}的其他基金

Development of a reminiscence therapy online platform with machine learning to increase engagement with people living with dementia and their care partners
开发具有机器学习功能的回忆疗法在线平台,以增加与痴呆症患者及其护理伙伴的互动
  • 批准号:
    10079369
  • 财政年份:
    2020
  • 资助金额:
    $ 44.85万
  • 项目类别:
Development of a reminiscence therapy online platform with machine learning to increase engagement with people living with dementia and their care partners
开发具有机器学习功能的回忆疗法在线平台,以增加与痴呆症患者及其护理伙伴的互动
  • 批准号:
    10227234
  • 财政年份:
    2020
  • 资助金额:
    $ 44.85万
  • 项目类别:

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