Why the study?
Existing cardiac monitoring methods like ECG and Holter cause discomfort from body-attached electrodes, while wearable photoplethysmography sacrifices accuracy and faces environmental interference.
Does a contactless radio frequency sensing system accurately monitor heart rate variability and identify heartbeat abnormalities compared to clinical-grade ECG?
Does a contactless radio frequency sensing system accurately monitor heart rate variability and identify heartbeat abnormalities compared to clinical-grade ECG?
A novel contactless radio frequency sensing system can monitor heart rate variability and identify basic cardiac abnormalities with clinical-grade accuracy, offering a potential tool for long-term proactive cardiovascular health monitoring.
May enable electrode-free home HRV tracking but should not yet change practice; leaves open arrhythmia detection accuracy.
Cardiovascular diseases claim over 10 million lives annually, highlighting the critical need for long-term monitoring and early detection of cardiac abnormalities. Existing techniques like electrocardiograms (ECG) and Holter are accurate but suffer from discomfort caused by body-attached electrodes. While wearable devices using photoplethysmography offer more convenience, they sacrifice accuracy and are susceptible to environmental interference. Here we present a radio frequency (RF)-based (60 to 64 GHz) sensing system that monitors long-term heart rate variability (HRV) with clinical-grade accuracy. Our system successfully overcomes the orders-larger interference from respiration motion in far-field conditions without any model training. By identifying previously undiscovered frequency ranges (beyond 10-order heartbeat harmonics) where heartbeat information predominates over other motions, we generate prominent heartbeat patterns with harmonics typically considered detrimental. Extensive evaluations, including a large-scale outpatient setting involving 6,222 eligible participants and a long-term daily life scenario, where sleep data was collected over 5 separate random nights over two months and a continuous 21-night period, demonstrate that our system can monitor HRV and identify abnormalities with comparable performance to clinical-grade ECG-based systems. This RF-based HRV sensing system has the potential to support active self-assessment and revolutionize medical prevention with long-term and precise health monitoring.
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Zhang et al. (2024) studied this question.