Miniaturized Forced Oscillation Technique Wearable Device

在北美，大约有2000万人被诊断患有睡眠呼吸暂停，然而，由于不适，只有800万人使用他们规定的睡眠辅助设备，例如他们的持续气道正压通气设备（CPAP）。 NovaResp Technologies Incorporated（“NovaResp”）正在开发设备和技术，这些设备和技术将减少阻塞性睡眠呼吸暂停（OSA）造成的短期和长期损害，并将直接解决当前市场对使睡眠辅助设备更舒适的需求。 虽然使用先进的强制振荡技术（FOT）将导致OSA的更快检测和反应性治疗，以及患者呼吸健康的更好管理，但当前的CPAP机器不能在不干扰患者的情况下结合这种方法。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，如OSA中的阻塞。 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的设置来抢先避免阻塞。 然而，在这种呼吸机/CPAP装置上结合现代FOT方法将需要传统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技术设计一种新型小型化、节能、高性价比的FOT可穿戴设备。该设备将能够用作机械呼吸机（如CPAP机器）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动力学，并能够早期发现慢性阻塞性肺疾病（COPD）。

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).