Tele-CF: A practical platform for remote monitoring of cognitive frailty

Tele-CF：认知脆弱性远程监测的实用平台

• 批准号: 10472738
• 负责人: Bijan Najafi
• 金额: $ 125万
• 依托单位: BIOSENSICS, LLC
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-30 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10472738
• 关键词: Academy; Address; Adopted; Adult; Age; Aging; Algorithms; Alzheimer' s Disease; Alzheimer' s disease related dementia; Articular Range of Motion; Assessment tool; Award; Biological Markers; COVID-19 pandemic; Clinic; Clinical; Clinical Research; Clinical Trials; Cognitive; Cognitive deficits; Collection; Computer software; Cross-Sectional Studies; Data; Databases; Dementia; Development; Disasters; Elbow; Elderly; Engineering; Forearm; Gait; Geriatrics; Gerontology; Grant; Health Insurance Portability and Accountability Act; Healthcare; Home; Image; Impaired cognition; International; Joints; Legal patent; Measurement; Measures; Modeling; Monitor; Motion; Motor; National Institute on Aging; Participant; Patients; Performance; Persons; Phase; Phenotype; Pilot Projects; Population; Recovery; Screening procedure; Severities; Short-Term Memory; Small Business Innovation Research Grant; Speed; System; Tablet Computer; Technology; Testing; Time; Visit; Walking; Work; base; body position; cognitive function; commercialization; comorbidity; cost; deep learning; deep learning algorithm; design; exhaustion; flexibility; frailty; image processing; indexing; kinematics; meter; mild cognitive impairment; novel; nutrition; older patient; prototype; recruit; remote assessment; remote monitoring; remote patient monitoring; remote screening; screening; sensor; telehealth; telehealth systems; tool; trend

ABSTRACT Cognitive frailty (CF), the combined presence of physical frailty and cognitive impairment, is a strong and independent predictor of cognitive decline over time. The International Association of Gerontology and Geriatrics and the International Academy on Nutrition and Aging have recommended the use of cognitive frailty assessment to track the progression of mild cognitive impairment (MCI) towards dementia, Alzheimer's disease (AD), and loss of independence. However, there is no practical tool for assessment of CF during telehealth visits. This is especially important as telehealth is growing in popularity amongst older adults and increasingly accepted by healthcare payers, and as the ongoing COVID-19 pandemic has significantly accelerated these trends. Therefore, there is an unmet need for a software-based solution that enables remote assessment of CF during telehealth visit and can be integrated into existing telehealth systems. In Phase I, we successfully designed a prototype of a novel CF measurement tool, called Tele-CF, that uses deep learning-based image processing to remotely measure CF. The Tele-CF algorithms extracts kinematic features of the forearm motion from a video of 20-second elbow flexion and extension, and quantifies weakness, slowness, rigidity, and exhaustion (which are phenotypes of frailty) to generate a frailty index (FI). FI ranges from zero to one, with higher values indicating progressively greater severity of frailty. When applied under dual-task conditions (e.g., while simultaneously performing a working memory task), Tele-CF can also screen cognitive impairment. In Phase I, we demonstrated the feasibility and proof of concept validity of Tele-CF for use in older adult population (n=29, age: 78.6±6.5), including 18 subjects with MCI or mild dementia, by comparing the results against validated tools (a sensor-based tool for in-clinic frailty assessment, dual-task gait, and a clinical cognitive scale, MMSE). After successfully achieving all milestones of Phase I, we are proposing to complete the development of Tele-CF and carry out a clinical study to demonstrate the ability of Tele-CF for remote tracking of CF over a 12-month period and to predict decline in CF at 12 months. To achieve the clinical aim of the study, we will recruit 100 adults (age 60+) with clinically confirmed MCI or mild dementia including 50 subjects without physical frailty and 50 subjects with physical frailty. All subjects will be assessed in clinic using conventional cognitive-motor assessment tools, at baseline, 6 months, and 12 months, and also remotely starting from the baseline every two months using Tele-CF. Tele-CF provides an easy-to-use desktop application for remote assessment of CF for clinicians that works with existing telehealth platforms. Tele-CF desktop application will enable clinicians to identify, document, and track CF in older patients. In addition, Tele-CF will have broader applications in collection and analysis of video biomarkers in telehealth and clinical trials.

摘要 认知脆弱（CF），身体虚弱和认知障碍的组合存在，是一种强烈的， 随着时间的推移，认知能力下降的独立预测因素。国际老年学和老年医学协会 和国际营养与衰老学会建议使用认知脆弱评估 跟踪轻度认知障碍（MCI）向痴呆、阿尔茨海默病（AD）的进展， 失去独立性。然而，在远程保健访问期间，没有实用的CF评估工具。这是 尤其重要的是，远程医疗在老年人中越来越受欢迎，并且越来越被老年人接受 由于持续的COVID-19大流行大大加速了这些趋势。 因此，存在对基于软件的解决方案的未满足的需求，该解决方案能够在 远程保健访问，并可纳入现有的远程保健系统。 在第一阶段，我们成功地设计了一种新型CF测量工具的原型，称为Tele-CF， 基于深度学习的图像处理来远程测量CF。Tele-CF算法提取运动学 从20秒肘关节屈曲和伸展的视频中获得前臂运动的特征，并量化虚弱， 缓慢、僵硬和疲惫（它们是虚弱的表型）以产生虚弱指数（FI）。FI范围从 从0到1，数值越高表示虚弱的严重程度越大。在双重任务下应用时 条件（例如，同时执行工作记忆任务），Tele-CF还可以筛选认知 损伤在第一阶段，我们证明了远程CF用于老年人的可行性和概念有效性的证明。 成年人（n=29，年龄：78.6±6.5），包括18名MCI或轻度痴呆受试者， 与经验证的工具（用于临床虚弱评估、双任务步态和临床认知评估的基于传感器的工具）相比， 量表，MMSE）。在成功完成第一阶段的所有里程碑后，我们建议完成 开发Tele-CF并进行临床研究，以证明Tele-CF的远程跟踪能力 的CF在12个月期间，并预测CF在12个月下降。为了达到本研究的临床目的， 我们将招募100名患有临床证实的MCI或轻度痴呆的成人（年龄60岁以上），包括50名没有 50名身体虚弱者。所有受试者将在诊所使用常规方法进行评估 认知运动评估工具，在基线，6个月，12个月，也从远程开始 使用Tele-CF每两个月进行一次基线检查。 Tele-CF为临床医生提供了一个易于使用的桌面应用程序，用于CF的远程评估， 现有的远程保健平台。Tele-CF桌面应用程序将使临床医生能够识别、记录和跟踪 老年患者的CF。此外，Tele-CF在视频采集和分析方面也将有更广泛的应用 远程医疗和临床试验中的生物标志物。

项目成果

Remote Physical Frailty Monitoring-The Application of Deep Learning-Based Image Processing in Tele-Health.

• DOI: 10.1109/access.2020.3042451
• 发表时间: 2020
• 期刊: IEEE access : practical innovations, open solutions
• 作者: Zahiri M;Wang C;Gardea M;Nguyen H;Shahbazi M;Sharafkhaneh A;Ruiz IT;Nguyen CK;Bryant MS;Najafi B
• 通讯作者: Najafi B

Wearable Sensor-Based Digital Biomarker to Estimate Chest Expansion During Sit-to-Stand Transitions-A Practical Tool to Improve Sternal Precautions in Patients Undergoing Median Sternotomy.

基于可穿戴传感器的数字生物标记，用于估计从坐到站的转换过程中胸部扩张情况 - 一种改善接受正中胸骨切开术患者胸骨预防措施的实用工具。

• DOI: 10.1109/tnsre.2019.2952076
• 发表时间: 2020
• 期刊: IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
• 作者: Wang,Changhong;Goel,Rahul;Noun,Maria;Ghanta,RaviK;Najafi,Bijan
• 通讯作者: Najafi,Bijan