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

项目摘要 运动伪影消除是用于动态ECG监测设备的关键要素，因为ECG 当患者进行手术时，应长时间连续记录波形 现实生活中的活动，如工作，锻炼，甚至睡觉。然而，现有的ECG运动 伪影消除方案需要密集的计算、复杂的电路和高功率 因此，不适合用于连续的长期监测设备。而且为了 为了顺应可穿戴生物医学传感器的趋势，ECG运动伪影消除 这些技术应当导致具有小形状因子、低功耗和低成本的设备。 本研究的基本原理是通过处理被破坏的图像来消除运动伪影 ECG传感器前端内的模拟域中的ECG信号将具有显著的优点， 现有的ECG运动伪影消除技术主要通过软件算法来实现 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ECG运动伪影消除技术开发; 2）验证 提出了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早期发现和预防心力衰竭 以及由心律失常和心房纤颤引起的中风，这些疾病目前影响着 占美国人口的很大一部分。此外，这项工作还可以提高质量， 由于社会的发展，目前预期需求会增加的远程ECG监测设备 距离要求，以防止COVID-19的传播。

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.