Fully-Analog Motion Artifact Elimination Circuit for Compact and Low Power A-ECG Monitoring Devices

项目总结 运动伪影的消除是动态心电监护设备的一个关键因素，因为心电 在患者进行检查时，应长时间连续记录波形 现实生活中的活动，比如工作、锻炼，甚至睡觉。然而，现有的心电运动 伪影消除方案需要密集的计算、复杂的电路和高功率 消耗，因此不适合连续的长期监测设备。而且，按照顺序， 为了顺应可穿戴生物医学传感器的发展趋势，心电运动伪影的消除 技术应该导致一种具有小尺寸、低功耗和低成本的设备。 这项研究的基本原理是通过处理受损的运动伪影来消除运动伪影 在心电传感器前端内的模拟域中的心电信号将具有显著的优点 现有的心电运动伪影消除技术大多是用软件算法实现的 或数字处理。我们的假设将通过以下具体目标得到验证：1)充分- 模拟心电信号运动伪影消除技术的开发；以及2)验证 提出了一种全模拟心电运动伪影消除技术。 我们相信，这项工作的成果将有助于及早发现和预防心力衰竭 以及由心律失常和房颤引起的中风，这些疾病目前正在影响 美国人口的很大一部分。此外，这项工作还可以提高产品的质量 远程心电监护设备，目前预计由于社会需求的增加 防止新冠肺炎传播的距离要求。

PROJECT SUMMARY Motion artifact elimination is a key element for ambulatory ECG monitoring devices, since ECG waveforms should be continuously recorded for a long period of time while the patient is performing real-life activities such as working, exercising, or even sleeping. However, existing ECG motion artifact elimination schemes require intensive computations, complicated circuitry, and high power consumption, thus are not suitable for continuous long-term monitoring devices. Moreover, in order to comply with the trends for wearable bio-medical sensors, the ECG motion artifact elimination techniques should lead to a device with small form factor, low power consumption, and low cost. The rationale of this research is that eliminating the motion artifacts by processing the corrupted ECG signal in the analog domain within the ECG sensor frontend will have significant merit over existing ECG motion artifact elimination techniques that are mostly realized with software algorithms or digital processing. Our hypotheses will be verified through the following specific aims: 1) fully- analog ECG motion artifact elimination technique development; and 2) validation of the proposed fully-analog ECG motion artifact elimination technique. We believe the outcomes of this work will contribute in early detection and prevention of heart failure and stroke caused by cardiac arrhythmias and atrial fibrillation, which are currently affecting a significant portion of the U.S. population. Furthermore, this work can also improve the quality of remote ECG monitoring devices that are currently expecting an increasing demand due to the social distancing requirements to prevent the spread of COVID-19.