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.

总结 目的是设计和临床评估ETAware，一种自适应的可穿戴系统，以监测影响 震颤对日常生活活动（ADL）的影响，用于评估和优化 原发性震颤（ET）患者，因为目前没有技术可以评估功能影响 日常生活活动能力ETAware将专注于ET，最常见的运动障碍，影响1000万人 然而，在商业上，该系统将应用于其他阻碍参与的条件 影响日常生活，影响生活质量。目前，普萘洛尔和扑米酮是两种主要的药物用于 治疗特发性震颤，同时进行脑深部电刺激（DBS）和MRI引导等手术干预 聚焦超声（MgFUS）是医学难治性ET的保证。然而，患者对所有 治疗的形式可以有很大的不同，需要顺序使用不同的药物。评价 为了提高干预措施的有效性，量化ET中震颤的严重程度及其对ADL的影响至关重要。 目前，为了显示临床改善，使用主观问卷和评定量表。但是，在这方面， 这些问卷和评定量表受临床判断和偏见的影响，仅提供 离散时间点，并且不能用于日常连续监测。ETAware将持续监测 震颤严重程度和震颤对ADL的功能影响，这将有助于临床医生进行治疗调整， 帮助患者控制他们的疾病管理，并通过提供 客观的生活质量测量和尽量减少与诊所访问和管理相关的费用， 问卷和评级量表。 我们之前已经将目前用于药物临床试验的可穿戴设备和移动的应用程序商业化 用于监测上肢震颤的严重程度。然而，现有的系统不量化下肢震颤或下肢震颤。 提供震颤对ADL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的连续测量 震颤对ADL的影响，2）临床医生优化治疗的系统，研究人员评估和开发 新的治疗方法，以及患者继续参与疾病管理。 为了证明I期研究的可行性，将从20名特发性震颤患者中收集运动数据 同时他们正在执行基于TETRAS的震颤表现和ADL任务以及附加功能任务。 成功标准包括：1）开发和验证与（r ≥ 0.76， 均方根误差≤0.5）运动学数据与临床医生基于TETRAS的震颤表现和ADL 分数，以及2）开发和验证机器学习模型，准确（灵敏度/ 特异性/AUC > 0.8）识别身体活动，例如行走、坐、站立、离开椅子、行走、站立、站立。 上下楼梯