Using gamification, predictive analytics, artificial intelligence, and Alexa Voice to optimize user experience for individuals living with AD/ADRD and their caregivers

使用游戏化、预测分析、人工智能和 Alexa Voice 来优化 AD/ADRD 患者及其护理人员的用户体验

• 批准号: 10590558
• 负责人: Matthew Golden
• 金额: $ 2.05万
• 依托单位: MAPHABIT, INC.
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-15 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10590558
• 关键词: Activities of Daily Living; Alzheimer' s Disease; Alzheimer' s disease diagnosis; Alzheimer' s disease related dementia; American; Artificial Intelligence; Award; Behavior; Behavior Therapy; Behavioral; Biometry; Caregivers; Clinical Trials; Cohort Studies; Computer software; Cues; Data; Dementia; Development; Disease; Effectiveness; Family; Friends; Goals; Healthcare; Impaired cognition; Individual; Legal patent; Marketing; Memory; Memory impairment; Motivation; Neuropsychology; Neurosciences; Patients; Persons; Pharmacotherapy; Phase; Predictive Analytics; Public Health; Quality of life; Science; Self Care; Self-Help Devices; Small Business Innovation Research Grant; Social Network; Social isolation; Societies; Standardization; Symptoms; System; Technology; United States National Institutes of Health; Visual; Visual system structure; Voice; base; behavioral outcome; commercialization; daily functioning; data streams; decision-making capacity; dementia caregiving; diagnostic tool; evidence base; experience; health goals; human old age (65+); improved; innovation; multiple data sources; novel; predictive modeling; social; social anxiety; virtual reality; vision science; visual map

More than 5.8 million Americans live with dementia and one in 10 Americans over the age of 65 suffer from a diagnosis of Alzheimer’s disease and Alzheimer’s related dementias (AD/ADRD). There are no cures for AD and drug treatments have little overall impact on the course and symptoms of disease. There are no diagnostic tools that can reliably identify people in the early stages of the disease. Individuals living with AD/ADRD have the same quality of life needs as individuals without dementia, including the ability to successful complete routine activities of daily living and maintain satisfying levels of independence and autonomy. However, in the setting of progressively diminishing memory and worsening abilities for self-care, individuals living with AD/ADRD experience progressive losses in independent decision- making capacity and quality of life. Social isolation and anxiety are disabling consequences of this condition. The MapHabitTM system (MHS), is an award-winning (NIH/NIA 1st place Eureka Award) patented, neuroscience-based assistive technology app that helps the memory-impaired accomplish activities of daily living, maintain their independence, and improves overall quality of life for users. The MHS product leverages the science of visual mapping to cue appropriate behavior in the AD setting. In this SBIR Phase II application, MapHabit will further develop the utility and effectiveness of the MHS visual mapping technology to enhance its commercialization and marketing potential by increasing its “stickiness” (i.e., motivation to engage with the app) and to establish a more substantive evidence base for its effects on improved quality of life and daily functioning. We propose two specific aims: Aim 1 – MapHabit will optimize the user experience for individuals with AD/ADRD by supplementing its visual mapping software with gamification technology via a partnership with a virtual reality and in-app games company that serves healthcare needs. Social networking (via gaming with friends and other residents) will be developed to build social connectivity and increase competition, both of which are known to increase “stickiness” and keep users engaged and motivated to adhere to behavioral interventions such as ADLs. We will conduct a 6-month clinical trial to assess behavioral outcomes. Aim 2 – MapHabit will develop a predictive analytics framework using the biometric and behavioral data streams from individuals as they use visual maps to carry out their ADLs. Partnering with a healthcare artificial intelligence company, we will conduct an observational cohort study to collect and integrate 16 months of data streams from 15 dyads from multiple data sources, including gamification and social networking using the MHS, standardized neuropsychological assessments of the patients, and assessments from caregivers. These novel data will be used to explore new predictive models that will potentially indicate early warnings of oncoming cognitive decline.

超过580万美国人患有痴呆症，65岁以上的美国人中有十分之一患有痴呆症。 阿尔茨海默病和阿尔茨海默病相关性痴呆（AD/ADRD）。目前还没有治愈AD和药物治疗 对疾病的进程和症状的总体影响不大。没有诊断工具可以可靠地识别 在疾病的早期阶段。AD/ADRD患者的生活质量需求与 没有痴呆症的人，包括成功完成日常生活和维持日常活动的能力 令人满意的独立性和自主性。然而，在记忆逐渐减少的情况下， 生活在AD/ADRD中的个体在独立决策方面经历逐渐丧失， 使生活的能力和质量。社交孤立和焦虑是这种情况的后果。的 Mapsilon TM系统（MHS）是一种屡获殊荣的（NIH/NIA尤里卡奖第一名）专利，基于神经科学 辅助技术应用程序，帮助记忆力受损的人完成日常生活活动， 独立性，并提高用户的整体生活质量。MHS产品利用视觉映射科学， 提示AD设置中的适当行为。在SBIR第二阶段应用中，MapHabit将进一步开发实用程序， MHS视觉绘图技术的有效性，以提高其商业化和营销潜力， 增加其“粘性”（即，与应用程序互动的动机），并建立更实质性的证据基础， 其对改善生活质量和日常功能的影响。我们提出了两个具体目标：目标1 - MapHabit将 优化AD/ADRD患者的用户体验，通过补充其视觉映射软件， 通过与一家服务于医疗保健需求的虚拟现实和应用内游戏公司合作， 社交网络（通过与朋友和其他居民的游戏）将被开发，以建立社会联系， 增加竞争，这两者都可以增加“粘性”，让用户参与并激励他们 坚持行为干预，如ADL。我们将进行为期6个月的临床试验，以评估行为结果。 目标2 - MapHabit将使用来自 当他们使用视觉地图来进行他们的ADL时，个体。与一家医疗保健人工智能公司合作， 我们将进行一项观察性队列研究，收集并整合来自15对夫妇的16个月数据流， 多个数据源，包括使用MHS的游戏化和社交网络，标准化神经心理学 对病人的评估和护理人员的评估。这些新数据将用于探索新的预测 这些模型可能会对即将到来的认知能力下降发出早期预警。