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: 10325279
• 负责人: Matthew Golden
• 金额: $ 118.99万
• 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/10325279
• 关键词: Activities of Daily Living; Address; Alzheimer' s Disease; Alzheimer' s disease diagnosis; Alzheimer' s disease related dementia; American; Area; Artificial Intelligence; Award; Behavior; Behavior Therapy; Behavioral; Biometry; Brain; Caregivers; Caring; Clinical; Clinical Trials; Cognitive; Cohort Studies; Communities; Computer software; Cues; Data; Dementia; Development; Diagnostic; Disease; Early Intervention; Early treatment; Effectiveness; Family; Family member; Friends; Goals; Habits; Health Status; Health system; Healthcare; Home Care Services; Hospitals; Impaired cognition; Independent Living; Individual; Journals; Learning; Legal patent; Link; Maps; Marketing; Memory; Memory impairment; Motivation; Neostriatum; Neuropsychology; Neurosciences; Outpatients; Paper; Patients; Pattern; Peer Review; Pharmacotherapy; Phase; Play; Predictive Analytics; Procedures; Provider; Public Health; Quality of life; Randomized Clinical Trials; Reporting; Rewards; Science; Self Care; Self-Help Devices; Services; Short-Term Memory; Signal Transduction; Small Business Innovation Research Grant; Social Interaction; Social Network; Social isolation; Societies; Standardization; Symptoms; System; Technology; Telephone; Testing; Therapeutic; Time; Translating; United States National Institutes of Health; Visual; Visual system structure; Voice; Work; base; behavioral outcome; clinically relevant; commercialization; cost; daily functioning; dashboard; data streams; decision-making capacity; dementia caregiving; design; evidence base; experience; health goals; human old age (65+); improved; innovation; intrinsic motivation; multiple data sources; novel; patient home care; predictive modeling; pressure; promoter; response; skills; social; social anxiety; tool; user-friendly; 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被诊断患有痴呆症