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

适用于紧凑型低功耗 A-ECG 监测设备的全模拟运动伪影消除电路

• 批准号: 10374161
• 负责人: Kye-Shin Lee
• 金额: $ 7.34万
• 依托单位: UNIVERSITY OF AKRON
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-05-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10374161
• 关键词: Affect; Algorithmic Software; Arrhythmia; Atrial Fibrillation; Behavioral Model; Breathing; COVID-19; Cause of Death; Cellular Phone; Clinical; Computer software; Computers; Consumption; Development; Devices; Early Diagnosis; Electrocardiogram; Electrodes; Elements; Event; Exercise; Gender; Goals; Heart failure; Investigation; Lead; Life; Measures; Monitor; Morphologic artifacts; Motion; Movement; Outcome; Output; Participant; Patients; Performance; Plant Roots; Population; Prevention; Process; Public Health; Research; Running; Sample Size; Sampling; Scheme; Signal Transduction; Skin; Sleep; Social Distance; Stroke; Techniques; Testing; Time; United States; Validation; Walking; Work; age group; analog; base; cost; design; digital; improved; integrated circuit; monitoring device; operation; power analysis; prevent; prototype; recruit; remote monitoring; sensor; technique development; treadmill; trend

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.

项目总结