ETAware: Continuous monitoring of the functional impact of essential tremor

ETAware：持续监测特发性震颤的功能影响

• 批准号: 10819790
• 负责人: Rabie Fadil
• 金额: $ 28.95万
• 依托单位: GREAT LAKES NEUROTECHNOLOGIES
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-30 至 2024-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10819790
• 关键词: Activities of Daily Living; Affect; Algorithms; Alzheimer' s Disease; Caring; Clinic Visits; Clinical; Clinical Trials; Clinical assessments; Data; Data Collection; Decision Making; Deep Brain Stimulation; Development; Device Approval; Disease; Disease Management; Disparity population; Drug Approval Processes; Drug usage; Dystonia; Effectiveness; Effectiveness of Interventions; Essential Tremor; Evaluation; Fingers; Focused Ultrasound; Improve Access; Individual; Judgment; Limb Tremors; Living Wills; Lower Extremity; Magnetic Resonance Imaging; Measurement; Measures; Medical; Monitor; Monitoring Clinical Trials; Motion; Movement Disorders; Observational Study; Operative Surgical Procedures; Orthostatic Hypotension; Outcome; Outcome Measure; Output; Parkinson Disease; Participant; Patient Care; Patients; Performance; Persons; Pharmaceutical Preparations; Phase; Physical activity; Primidone; Process; Propranolol; Quality of life; Questionnaires; Refractory; Research; Research Personnel; Rest; Rural Population; Sensitivity and Specificity; Severities; Stroke; Symptoms; System; Technology; Therapeutic Intervention; Time; Titrations; Tremor; Underserved Population; Upper Extremity; Validation; Visual; Walking; Work; clinical decision-making; commercialization; cost; design; effectiveness evaluation; evidence base; geographic disparity; health care availability; improved; innovation; kinematics; machine learning model; mobile application; motion sensor; novel therapeutics; patient response; sensor; signal processing; success; symptomatic improvement; treatment optimization; wearable device

Summary The objective is to design and clinically assess ETAware, an adaptive, wearable system to monitor the impact of tremor on activities of daily living (ADL) for the evaluation and optimization of therapeutic interventions in patients with essential tremor (ET) as there is currently no technology that can assess the functional impact of tremor on ADL. ETAware will focus on ET, the most common movement disorder, affecting 10 million people in the US; however, commercially, the system will have applications for other conditions that hinder engagement in daily activities and affect quality of life. Currently, propranolol and primidone are the two main drugs used for treating essential tremor, while surgical interventions such as deep brain stimulation (DBS), and MRI-guided focused ultrasound (MgFUS) are warranted in medically refractory ET. Nevertheless, patients' responses to all forms of therapy can vary substantially, necessitating the sequential use of different drugs. To evaluate the effectiveness of interventions, it is critical to quantify both tremor severity and its impact on ADL in ET. Currently, to show clinical improvement, subjective questionnaires and rating scales are used. However, these questionnaires and rating scales are subject to clinical judgment and bias, only provide information at a discrete point in time, and cannot be utilized for daily continuous monitoring. ETAware will continuously monitor tremor severity AND the functional impact of tremor on ADL, which will help clinicians with therapy adjustments, help patients take control of their disease management, and improve research and clinical trials by providing an objective quality of life measure and minimizing the costs associated with clinic visits and the administration of questionnaires and rating scales. We have previously commercialized wearables and mobile apps that are currently used in drug clinical trials for monitoring upper limb tremor severity. However, the existing systems do not quantify lower limb tremor or give any information on the impact of tremor on ADL. The primary innovations of ETAware are 1) signal processing algorithms to analyze motion sensor data and provide continuous measurements of the functional impact of tremor on ADL, 2) a system for clinicians to optimize therapy, researchers to evaluate and develop new therapies, and patients to stay involved in their disease management. To demonstrate feasibility in Phase I, motion data will be collected from 20 patients with essential tremor while they are performing TETRAS-based tremor performance and ADL tasks as well additional functional tasks. Success criteria include 1) development and validation of signal processing algorithms that correlate (r ≥ 0.76, root-mean-square error ≤0.5) kinematic data with clinician's TETRAS-based tremor performance and ADL scores, and 2) development and validation of machine learning models that accurately (sensitivity/ specificity/AUC > 0.8) identify physical activities such as walking, sitting, standing, getting out of a chair, going up and down stairs.

概括 目的是设计和临床评估Etaware，这是一种自适应，可穿戴系统，以监视影响 Tremori关于日常生活活动（ADL）的评估和优化治疗干预措施 具有必需树（ET）的患者，因为目前没有技术可以评估功能影响 在ADL上的Tremori。 Etaware将重点关注ET，这是最常见的运动障碍，影响1000万人 在美国；但是，在商业上，该系统将针对阻碍参与度的其他条件申请 在日常活动中，影响生活质量。目前，普萘洛尔和原酮是使用的两种主要药物 治疗必需树，而手术干预措施，例如深脑刺激（DB）和MRI引导 在医学上难治性的ET中保证了聚焦超声（MGFU）。然而，患者对所有人的反应 治疗形式可能有很大的不同，对于使用不同药物的顺序使用所必需的。评估 干预的有效性，量化震颤严重程度及其对ET中ADL的影响至关重要。 目前，为了显示临床改进，使用主题问卷和评级量表。然而， 这些问卷和评级量表受到临床判断和偏见的约束，仅提供信息 离散的时间点，不能用于每日连续监视。 etaware将继续监视 震颤的严重程度和震颤对ADL的功能影响，这将帮助临床医生进行治疗调整， 帮助患者控制疾病管理，并通过提供 客观的生活质量测量和最小化与诊所访问相关的成本和管理 问卷和评分量表。 我们以前有商业化的可穿戴设备和移动应用程序，目前用于药物临床试验 用于监视上肢震颤的严重程度。但是，现有系统不会量化下肢震颤或 提供有关Tremori对ADL的影响的任何信息。 etaware的主要创新是1）信号 处理算法以分析运动传感器数据并提供功能性的连续测量 Tremori对ADL的影响，2）临床医生优化治疗的系统，研究人员评估和发展 新疗法和患者参与其疾病管理。 为了证明第一阶段的可行性，将从20例必不可少的患者中收集运动数据 当他们执行基于Tetras的震颤性能和ADL任务以及其他功能任务时。 成功标准包括1）相关的信号处理算法的开发和验证（r≥0.76， 根平方误差≤0.5）具有临床基于Tetras的震颤性能和ADL的运动学数据 分数和2）准确的机器学习模型的开发和验证（灵敏度/ 特异性/AUC> 0.8）确定体育活动，例如步行，坐着，站立，摆脱椅子，去 楼下。