Unobtrusive and continuous monitoring of cognitive changes using smartphones

使用智能手机不引人注目且持续监测认知变化

• 批准号: 10045835
• 负责人: Maciej Rafal Kos
• 金额: $ 4.68万
• 依托单位: NORTHEASTERN UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10045835
• 关键词: Accounting; Adult; Aging; Alzheimer' s Disease; Alzheimer' s disease related dementia; Android; Attention; Biological Markers; Brain imaging; Caregivers; Caring; Cellular Phone; Characteristics; Clinical; Clinical Trials; Clinical assessments; Cognition; Cognitive; Cognitive Science; Cognitive deficits; Cross-Sectional Studies; Data; Dementia; Development; Diagnosis; Early Diagnosis; Ecological momentary assessment; Effectiveness; Elderly; Frequencies; Functional disorder; Goals; Health; Healthcare Systems; Impaired cognition; Individual; Informed Consent; Location; Longitudinal Studies; Measures; Methods; Modeling; Monitor; Motor; Names; Nature; Nerve Degeneration; Neurocognitive; Neurodegenerative Disorders; Neurology; Neuropsychology; Participant; Patients; Pattern; Phase; Psychometrics; Psychomotor Performance; Recording of previous events; Reporting; Research; Research Personnel; Research Project Grants; Selection for Treatments; Services; Short-Term Memory; Signal Transduction; Social Interaction; Speed; System; Testing; Training; Transportation; Traumatic Brain Injury; Validation; Visit; accurate diagnosis; base; care providers; cognitive change; cognitive function; cost; digital; health data; improved; instrumental activity of daily living; mHealth; middle age; mild cognitive impairment; mobile application; mobile computing; neurocognitive disorder; novel strategies; open source; socioeconomics; software development; time use; tool; touchscreen; walking speed; web site; young adult

Project Summary Acquired cognitive impairment associated with aging, neurocognitive disorders, like Alzheimer’s disease, and traumatic brain injury (TBI) pose major challenges to healthcare systems throughout the world. To facilitate successful aging, effective methods are needed for monitoring cognition in order to detect early signs of impaired cognition and dementia. However, the effectiveness of existing neuropsychological assessments is thwarted by their sporadicity, difficulty in accounting for the context-dependent nature of patients’ health (e.g., having a “good” or a “bad” day), and reliance on frequently inaccurate patient and caregiver reports. Thus, new approaches are needed for objective and ecologically valid assessment of cognitive function and for early detection of impaired cognition associated with neurocognitive disorders like Alzheimer’s disease and TBI. Current mHealth and AI approaches enable continuous context inference from smartphone use and location data. Patient reports of Instrumental Activities of Daily Living (IADLs) can be greatly enhanced with continuous, objective context inferences from passively collected smartphone-based data that can contribute to earlier and more accurate diagnoses of neurocognitive disorder including Alzheimer’s disease and related dementia. Cross-sectional studies involving younger and older adults suggest that characteristics of an individual’s mobile application use and typing speed correlate with working memory, attention, and psychomotor function. Therefore, the proposed augmentation of clinical assessments with continuous and objective estimates of cognitive changes derived computationally and unobtrusively from mobile application use characteristics and motor interactions has the potential to inform both the early detection and diagnosis of impaired cognition associated with neurocognitive disorders, such as Alzheimer’s disease and TBI, and potentially treatment selection for their amelioration. The central hypothesis to be tested in this longitudinal study is that changes in cognition, including impaired cognition associated with Alzheimer’s disease and other neurocognitive disorders, can be inferred from smartphone data. In the F99 phase, Mr. Kos will a) augment existing measures derived from IADLs and lifespace mobility with analogous measures inferred from mobile location-finding systems (e.g., GPS) and application use data, and b) propose a digital biomarker for tracking cognitive changes and impaired cognition based on temporal patterns in application use and motor interactions with smartphones. Validation will be conducted on 80 middle-aged individuals; 20 with subjective cognitive impairment, 20 with diagnosed Mild Cognitive Impairment, 20 with TBI, and 20 cognitively intact controls. In the K00 phase, Mr. Kos will select the subset of these measures determined to be most applicable to tracking cognitive changes and impaired cognition and, thus, prime for detecting early signs of Alzheimer’s disease and other types of neurocognitive disorder in older adults. Their refinement and validation in clinical trials using biomarkers and brain imaging data will enable developing a mechanistic understanding of a) the relationships between impaired cognition, Alzheimer’s disease, and neurocognitive changes including TBI and b) how these relationships are reflected in interactions with mobile technologies.

项目摘要 与衰老相关的获得性认知障碍、阿尔茨海默病等神经认知障碍以及创伤性脑损伤(TBI)对世界各地的医疗体系构成了重大挑战。为了促进成功的衰老，需要有效的方法来监测认知，以便发现认知受损和痴呆的早期迹象。然而，现有的神经心理学评估的有效性受到以下因素的阻碍：它们是零星的，很难解释患者健康的上下文相关性质(例如，有“好”或“坏”的一天)，以及对经常不准确的患者和照顾者报告的依赖。因此，需要新的方法来客观和生态上有效地评估认知功能，并早期发现与阿尔茨海默病和脑外伤等神经认知障碍相关的认知受损。 目前的移动健康和人工智能方法支持从智能手机使用和位置数据进行持续的上下文推理。患者对日常生活工具活动(IADL)的报告可以通过从被动收集的基于智能手机的数据进行连续、客观的上下文推断而大大增强，这有助于更早、更准确地诊断包括阿尔茨海默病和相关痴呆症在内的神经认知障碍。涉及年轻人和老年人的横断面研究表明，个人使用移动应用程序的特征和打字速度与工作记忆、注意力和精神运动功能相关。因此，拟议通过计算和不引人注意地从移动应用程序使用特征和运动交互中获得认知变化的连续和客观估计来加强临床评估，有可能为与神经认知障碍(如阿尔茨海默病和脑外伤)相关的认知障碍的早期发现和诊断提供信息，并有可能为其改善选择治疗方案。 在这项纵向研究中要检验的中心假设是，认知的变化，包括与阿尔茨海默病和其他神经认知障碍相关的认知受损，可以从智能手机的数据中推断出来。 在F99阶段，Kos先生将a)用从移动定位系统(例如GPS)和应用程序使用数据推断出的类似方法来扩充源自IADL和生活空间移动性的现有测量方法，以及b)提出一个数字生物标记物，用于基于应用程序使用的时间模式和与智能手机的运动交互来跟踪认知变化和认知障碍。验证将在80名中年个体中进行，其中20名为主观认知障碍，20名诊断为轻度认知障碍，20名为脑外伤，20名为认知正常的对照组。 在K00阶段，科斯先生将选择这些方法中被确定为最适用于跟踪认知变化和认知受损的子集，从而最适合于检测阿尔茨海默病和其他类型的老年人神经认知障碍的早期迹象。在使用生物标记物和脑成像数据的临床试验中，它们的完善和验证将有助于从机制上理解a)认知受损、阿尔茨海默病和包括脑损伤在内的神经认知变化之间的关系，以及b)这些关系如何在与移动技术的互动中反映出来。