Clinical feasibility of a non-invasive, low-cost wearable for measuring air trapping in COPD

用于测量 COPD 空气滞留的非侵入性低成本可穿戴设备的临床可行性

• 批准号: 10080272
• 负责人: Maria Artunduaga
• 金额: $ 35万
• 依托单位: SAMAY, INC.
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-20 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10080272
• 关键词: Acoustics; Activities of Daily Living; Adult; Air; Algorithmic Analysis; Algorithms; American; Asthma; Bluetooth; Bronchoconstriction; Caring; Cellular Phone; Chronic Bronchitis; Chronic Obstructive Airway Disease; Clinic; Clinical; Clinical Data; Clinical Research; Clinical Trials; Computer software; Cross-Sectional Studies; Data; Data Analyses; Detection; Deterioration; Development; Device Designs; Devices; Diagnosis; Disease Progression; Dyspnea; Early Intervention; Edema; Emergency department visit; Exhalation; Exposure to; Flare; Frequencies; Functional disorder; Future; General Hospitals; Goals; Health; Health Care Costs; Heart Rate; Home environment; Hospitalization; Hospitals; Humidity; Individual; Inhalators; Intervention; Laboratories; Lung; Machine Learning; Measurement; Measures; Medical; Medical History; Medical center; Methods; Military Personnel; Miniaturization; Minor; Monitor; Morbidity - disease rate; Mucous body substance; Noise; Oral; Oxygen saturation measurement; Particulate; Patients; Pharmaceutical Preparations; Phase; Physicians; Physiology; Plethysmography; Population; Pulmonary Emphysema; Pulmonary function tests; Pulse Oximetry; Quality of life; Questionnaires; Refractory; Regulatory Pathway; Reporting; Respiratory Muscles; Respiratory physiology; Risk; Running; San Francisco; Secure; Signal Transduction; Small Business Technology Transfer Research; Smoker; Spirometry; Standardization; Symptoms; System; Technology; Temperature; Testing; Therapeutic Intervention; Time; Translating; Ultrasonography; Veterans; Whole Body Plethysmography; Wireless Technology; X-Ray Computed Tomography; accurate diagnosis; air monitoring; base; cloud based; cohort; cost; design; experience; improved; indexing; machine learning algorithm; meter; microphone; miniaturize; mobile application; mortality; novel; ozone exposure; prevent; prototype; recruit; respiratory; screening; sensor; smartphone Application; software development; success; tool; usability; user-friendly; wearable device

ABSTRACT Chronic Obstructive Pulmonary Disease (COPD) is the third leading cause of hospitalization in the US. Exacerbations - a worsening or “flare up” of symptoms - cause most COPD hospitalizations. Since most exacerbations can be treated with changes of inhalers and/or oral medications, at-home detection of lung function deterioration may facilitate earlier intervention and help delay or prevent hospitalizations. The Standards of Care for monitoring lung function are spirometry, plethysmography, and CT scan. However, these are expensive methods and unsuited for continuous monitoring or at-home use. Various patient self-monitoring approaches have been tried, for example, pulse oximetry, respiratory rate monitoring, and peak flow metering, but their efficacy in reducing hospitalizations has been limited. A common finding for all forms of COPD is air trapping, defined, as an abnormal increase in the volume of air remaining in the lungs after exhalation is complete. A body of evidence definitively shows that air trapping increases during exacerbations and decreases when exacerbations resolve. Recent reports show that air trapping is an earlier harbinger of deteriorating lung function than spirometric changes, and can be measured by low-frequency ultrasound (1-40 kHz). Acoustic monitoring of air trapping could provide clinicians with a non- invasive tool when medical intervention is needed to avoid unnecessary ER visits and hospitalizations. Respira Labs has developed a low-cost, non-invasive, acoustic-based wearable device that can continually monitor lung resonance: Sylvee. The device uses known acoustic-based technology with machine- learning algorithms to detect minor changes in lung resonance, which our preliminary results suggest correspond to changes in air trapping. The overall objective of this project is to validate Sylvee's air trapping algorithms in a cohort of 20 healthy controls and 40 COPD patients with and without air trapping, respectively. In Aims 1 and 2, we will miniaturize and add sensors to the Sylvee device and develop a user interface (UI) and a mobile application. In Aims 3 and 4, we will create an Air Trapping Index Report and validate it in a cross-sectional study vis-à-vis whole body plethysmography as a control. Results of this project provide a go/no-go development decision based on device function. We can apply these results in STTR Phase II, in a larger clinical study to evaluate Sylvee as an at-home monitoring system, with a goal of reducing hospitalizations by at least 30%. Ultimately, Sylvee will allow physicians to remotely monitor their patients' lung function and adjust their medications to reduce healthcare costs and improve patients' quality of life.

抽象的 慢性阻塞性肺疾病（COPD）是美国住院的第三大原因。 大多数慢性阻塞性肺病患者住院都是由于病情加重——症状恶化或“突然发作”。 可以通过更换吸入器和/或口服药物、在家检测肺部来治疗病情加重 功能恶化可能有助于早期干预并有助于推迟或防止住院治疗。 监测肺功能的护理标准是肺活量测定法、体积描记法和 CT 扫描。 是昂贵的方法，不适合连续监测或家庭使用。 已经尝试过一些方法，例如脉搏血氧测定法、呼吸频率监测和峰值流量计量， 但它们在减少住院治疗方面的效果有限。 所有形式的慢性阻塞性肺病的一个共同发现是空气滞留，定义为体积异常增加 呼气完成后肺部残留的空气量 大量证据明确表明空气滞留。 恶化期间增加，恶化消退时减少。最近的报告显示，空气。 与肺活量变化相比，滞留是肺功能恶化的更早先兆，并且可以测量 通过低频超声波（1-40 kHz）对空气滞留进行声学监测可以提供非- 当需要医疗干预以避免不必要的急诊室就诊和住院治疗时，可使用侵入性工具。 Respira Labs 开发了一种低成本、非侵入性、基于声学的可穿戴设备，可以 持续监测肺部共振：Sylvee 使用已知的基于声学的技术和机器。 学习算法来检测肺共振的微小变化，我们的初步结果表明 对应于空气滞留的变化 该项目的总体目标是验证 Sylvee 的空气滞留。 分别在 20 名健康对照者和 40 名 COPD 患者（有或没有空气滞留）的队列中进行了算法研究。 在目标 1 和 2 中，我们将小型化并向 Sylvee 设备添加传感器，并开发用户界面 (UI) 在目标 3 和 4 中，我们将创建空气滞留指数报告并在其中进行验证。 相对于全身体积描记法作为对照的横断面研究提供了一个结果。 我们可以根据设备功能做出进行/不进行的开发决策，并将这些结果应用于 STTR 第二阶段。 更大规模的临床研究评估 Sylvee 作为家庭监测系统，目标是减少 最终，Sylvee 将允许医生远程监测患者的肺部情况。 发挥作用并调整药物以降低医疗成本并提高患者的生活质量。