Monitoring long-term cardiac activity with contactless radio frequency signals

IF 15.7 1区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES Nature Communications Pub Date : 2024-12-05 DOI:10.1038/s41467-024-55061-9
Bin-Bin Zhang, Dongheng Zhang, Yadong Li, Zhi Lu, Jinbo Chen, Haoyu Wang, Fang Zhou, Yu Pu, Yang Hu, Li-Kun Ma, Qibin Sun, Yan Chen
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Abstract

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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用非接触式射频信号监测长期心脏活动
心血管疾病每年夺去1000多万人的生命,这凸显了长期监测和早期发现心脏异常的迫切需要。现有的技术,如心电图(ECG)和动态心电图(Holter)是准确的,但受到身体附着电极引起的不适的影响。虽然使用光电容积脉搏波的可穿戴设备提供了更多的便利,但它们牺牲了准确性,而且容易受到环境干扰。在这里,我们提出了一个基于射频(RF)(60至64 GHz)的传感系统,以临床级的精度监测长期心率变异性(HRV)。我们的系统在没有任何模型训练的情况下,成功地克服了远场条件下呼吸运动的大阶干扰。通过识别以前未被发现的频率范围(超过10阶心跳谐波),其中心跳信息占主导地位的其他动作,我们产生了突出的心跳模式与谐波通常被认为是有害的。广泛的评估,包括涉及6222名合格参与者的大规模门诊设置和长期日常生活场景,其中睡眠数据在两个月和连续21个晚上的5个独立随机夜晚收集,证明我们的系统可以监测HRV并识别异常,其性能与临床级ecg系统相当。这种基于rf的HRV传感系统具有支持主动自我评估的潜力,并通过长期和精确的健康监测彻底改变医疗预防。
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来源期刊
Nature Communications
Nature Communications Biological Science Disciplines-
CiteScore
24.90
自引率
2.40%
发文量
6928
审稿时长
3.7 months
期刊介绍: Nature Communications, an open-access journal, publishes high-quality research spanning all areas of the natural sciences. Papers featured in the journal showcase significant advances relevant to specialists in each respective field. With a 2-year impact factor of 16.6 (2022) and a median time of 8 days from submission to the first editorial decision, Nature Communications is committed to rapid dissemination of research findings. As a multidisciplinary journal, it welcomes contributions from biological, health, physical, chemical, Earth, social, mathematical, applied, and engineering sciences, aiming to highlight important breakthroughs within each domain.
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