Miniaturized Forced Oscillation Technique Wearable Device

小型化受迫振荡技术可穿戴设备

• 批准号: 537988-2018
• 负责人: ElSankary, Kamal
• 金额: $ 6.6万
• 依托单位: Dalhousie University
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=692423
• 关键词: Miniaturized; Forced; Oscillation; Technique; Wearable

In North America approximately 20 million people are diagnosed by sleep apnea, however, due to discomfort, only 8 million use their prescribed sleep-assistance device such as their continuous positive airway pressure device (CPAP). NovaResp Technologies Incorporated ("NovaResp") is developing devices and techniques that will reduce the short- and long-term damages caused by obstructive sleep apnea (OSA) and will directly address the current market need of making sleep-assistance device more comfortable. While using advanced forced oscillation technique (FOT) would lead to faster detection and reactive treatment of OSA, as well as better management of patients' respiratory health, current CPAP machines are incapable of incorporating such methods without disturbing the patient. NovaResp is working on a revolutionary technique to predict respiratory failure such as obstruction in OSA through machine learning techniques. Using FOT data, these machine learning methods will lead to the preemptive avoidance of obstruction by adjusting CPAP's settings before a failure occurs. However, incorporation of modern FOT methods on such ventilators/CPAP devices would require miniaturization of traditional FOT. The main objective of this research proposal is to design a new miniaturized, energy efficient, cost-effective, FOT wearable device using modern integrated circuits and signal processing. This device will be able to be used as an add-on to mechanical ventilators such as CPAP machines to detect and predict sleep apnea episodes. This device will also provide real-time respiratory impedance measurement and recording outside the clinic. This will help in the creation of a big-data database that will allow medical doctors and researchers to better understand the pulmonary dynamics as well as to enable early detection of chronic obstructive pulmonary disease (COPD).

在北美，大约 2000 万人被诊断患有睡眠呼吸暂停，然而，由于不适，只有 800 万人使用处方的睡眠辅助设备，例如持续气道正压通气设备 (CPAP)。 NovaResp Technologies Incorporated（“NovaResp”）正在开发设备和技术，以减少阻塞性睡眠呼吸暂停 (OSA) 造成的短期和长期损害，并将直接满足当前市场对提高睡眠辅助设备舒适度的需求。虽然使用先进的受迫振荡技术 (FOT) 可以更快地检测 OSA 并进行反应性治疗，并更好地管理患者的呼吸健康，但当前的 CPAP 机器无法在不干扰患者的情况下纳入此类方法。 NovaResp 正在研究一种革命性的技术，通过机器学习技术来预测呼吸衰竭，例如 OSA 阻塞。 使用 FOT 数据，这些机器学习方法将通过在故障发生之前调整 CPAP 的设置来预先避免阻塞。 然而，将现代 FOT 方法结合到此类呼吸机/CPAP 设备上需要传统 FOT 的小型化。本研究提案的主要目标是利用现代集成电路和信号处理设计一种新型小型化、节能、经济高效的 FOT 可穿戴设备。该设备将能够用作机械呼吸机（例如 CPAP 机）的附加设备，以检测和预测睡眠呼吸暂停发作。该设备还将在诊所外提供实时呼吸阻抗测量和记录。这将有助于创建一个大数据数据库，使医生和研究人员能够更好地了解肺部动态，并能够及早发现慢性阻塞性肺病（COPD）。