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

基本信息

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
项目类别：
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&apos s Disease Alzheimer&apos 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

项目摘要

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.

抽象的认知衰弱（CF）是身体衰弱和认知障碍的结合，是一种严重且严重的疾病。随着时间的推移认知能力下降的独立预测因子。和国际营养与衰老学院建议使用认知脆弱评估追踪轻度认知障碍 (MCI) 向痴呆、阿尔茨海默病 (AD) 的进展，以及然而，在远程医疗就诊期间没有评估 CF 的实用工具。尤其重要的是，远程医疗在老年人中越来越受欢迎，并且越来越被人们所接受。医疗保健支付者，以及持续的 COVID-19 大流行显着加速了这些趋势。因此，对基于软件的解决方案的需求尚未得到满足，该解决方案可以在运行期间对 CF 进行远程评估远程医疗就诊，可以集成到现有的远程医疗系统中。在第一阶段，我们成功设计了一种新型CF测量工具的原型，称为Tele-CF，它使用基于深度学习的图像处理远程测量 CF Tele-CF 算法提取运动学。从 20 秒肘部屈曲和伸展的视频中了解前臂运动的特征，并量化弱点，缓慢、僵硬和疲惫（这是虚弱的表型）产生的虚弱指数（FI）范围为 0 到 1，数值越高，表明在双重任务下应用时虚弱的严重程度逐渐增加。 Tele-CF 还可以筛选认知条件（例如，同时执行工作记忆任务）在第一阶段，我们展示了 Tele-CF 在老年人中使用的可行性和概念有效性。成年人群（n=29，年龄：78.6±6.5），包括 18 名患有 MCI 或轻度痴呆的受试者，通过比较结果对照经过验证的工具（基于传感器的工具，用于临床虚弱评估、双任务步态和临床认知在成功实现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 12 个月期间的 CF 并预测 12 个月时 CF 的下降为了实现该研究的临床目标，我们将招募 100 名临床确诊患有 MCI 或轻度痴呆症的成年人（60 岁以上），其中包括 50 名没有患有 MCI 或轻度痴呆症的受试者。身体虚弱和 50 名身体虚弱的受试者所有受试者都将在临床上使用常规方法进行评估。认知运动评估工具，在基线、6 个月和 12 个月，以及从远程开始使用 Tele-CF 每两个月进行一次基线。 Tele-CF 提供了一个易于使用的桌面应用程序，用于远程评估 CF，可与 Tele-CF 桌面应用程序将使现有的远程医疗平台的忠实用户能够识别、记录和跟踪。此外，Tele-CF 在视频采集和分析方面将有更广泛的应用。远程医疗和临床试验中的生物标志物。

项目成果

期刊论文数量（3）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

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
影响因子：
0
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。