Utilizing Technology and AI Approaches to Facilitate Independence and Resilience in Older Adults

利用技术和人工智能方法促进老年人的独立性和适应能力

• 批准号: 10652026
• 负责人: Peter M. Abadir
• 金额: $ 35.58万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-30 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10652026
• 关键词: 3-Dimensional; Alzheimer' s Disease; Alzheimer' s disease patient; Attention; Behavior; Behavior Therapy; Biological Markers; Caregivers; Cognition; Cognitive; Data; Dementia; Diagnostic; Ecological momentary assessment; Elderly; Environment; Future; Health; Heart Rate; Home; Impaired cognition; Incidence; Individual; Instruction; Measurement; Measures; Memory; Music; Nature; Neurobehavioral Manifestations; Neurobiology; Patients; Pattern; Psychometrics; Reporting; Sampling; Sleep; Technology; Test Result; Time; Work; auditory stimulus; base; cognitive change; cognitive testing; diaries; evidence base; executive function; insight; mobile computing; new therapeutic target; resilience; response; sensor; statistical and machine learning; wearable device

Abstract Dementia research has focused almost exclusively on the deleterious aspects of AD, including memory loss, cerebral atrophy, and the molecular consequences of Aβ/tau pathology. Unfortunately, despite advances in our understanding of AD, the toolbox of viable treatments is no greater today than 20 years ago. An astonishing, yet underappreciated, aspect of AD/ADRD is the moment-to-moment fluctuation in cognitive health. Cognitive fluctuations, defined as spontaneous alterations in attention, arousal, and cognition, are evaluated based on the occurrence of symptoms such as impaired consciousness or confusion. However, the exact features and causes of cognitive fluctuations are still unclear. A greater understanding of the factors that lead to cognitive fluctuations and the precise behaviors that are present would allow us to identify strategies for preventing and managing dementia symptoms. We plan to provide a robust framework for quantifying cognitive fluctuations and lucid intervals in individuals with Alzheimer’s disease (AD) using a mobile technology platform applied within one’s home or local environment. Psychometric test results collected using a diagnostic app will be integrated with caregiver reports of cognitive changes to determine the features and incidence of these moments in AD patients (Aim 1). We then aim to identify reliable predictors of cognitive fluctuations and lucid intervals using wearable health sensors to uncover data-driven patterns of cognitive change (Aim 2). This three-dimensional view of cognition (in-home cognitive testing, caregiver reports, health sensors) will provide unprecedented insight into the nature of cognitive decline, cognitive fluctuations, and potentially incidences of lucidity.

摘要