Contactless Acquisition and Decoupling of Respiratory and Cardiac Signals Using a 122 GHz FMCW Radar

IF 7.7 2区 医学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Laura Miro;Ruochen Wu;Albert Aguasca;Antoni Broquetas;Cosme Garcia;Oriol Estrada;Montse Najar
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Abstract

This paper presents a contactless method for the simultaneous monitoring of heart rate (HR) and respiratory rate (RR) using a Frequency Modulated Continuous Wave (FMCW) radar operating at 122.5 GHz. To address the challenges posed by spectral overlap and interference between cardiac and respiratory components, we introduce a signal separation and estimation framework based on Maximum Likelihood Estimation (MLE) combined with an orthogonal projection technique. The approach models the thoracic displacement captured by the radar as the superposition of periodic sources and applies spectral projection to isolate the fundamental frequencies and their harmonics. Theoretical performance is assessed through the derivation of the Cramér–Rao Lower Bound (CRLB) and extensive Monte Carlo simulations under varying SNR and sample size conditions. Experimental validation was conducted on 23 healthy volunteers, each providing two 20 s recordings, using a clinical-grade reference monitor. The method achieves high estimation accuracy, with a mean absolute error of 0.69 bpm for HR and 0.33 bpm for RR. The algorithm is capable of reconstructing the cardiac pulse waveform while preserving key morphological features such as the systolic peak and dicrotic notch. Furthermore, the use of the projection technique further enhanced estimation accuracy under nonphysiological conditions, including both elevated and reduced rates. These findings demonstrate the potential of the proposed method as a reliable tool for contactless monitoring of vital signs and support its future integration into biomedical applications.
基于122ghz FMCW雷达的呼吸和心脏信号非接触采集与解耦。
本文提出了一种使用工作频率为122.5 GHz的调频连续波(FMCW)雷达同时监测心率(HR)和呼吸频率(RR)的非接触式方法。为了解决频谱重叠和心脏和呼吸成分之间的干扰所带来的挑战,我们引入了一种基于最大似然估计(MLE)和正交投影技术的信号分离和估计框架。该方法将雷达捕获的胸廓位移建模为周期源的叠加,并应用谱投影分离基频及其谐波。在不同信噪比和样本量条件下,通过推导cram - rao下限(CRLB)和广泛的蒙特卡罗模拟来评估理论性能。实验验证在23名健康志愿者中进行,每个人提供两次20秒的录音,使用临床级参考监视器。该方法具有较高的估计精度,HR和RR的平均绝对误差分别为0.69 bpm和0.33 bpm。该算法能够重建心脏脉冲波形,同时保留关键的形态学特征,如收缩期峰值和dicrotic陷波。此外,投影技术的使用进一步提高了非生理条件下的估计精度,包括升高和降低的速率。这些发现证明了所提出的方法作为非接触式生命体征监测的可靠工具的潜力,并支持其未来集成到生物医学应用中。
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来源期刊
IEEE Journal of Biomedical and Health Informatics
IEEE Journal of Biomedical and Health Informatics COMPUTER SCIENCE, INFORMATION SYSTEMS-COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
CiteScore
13.60
自引率
6.50%
发文量
1151
期刊介绍: IEEE Journal of Biomedical and Health Informatics publishes original papers presenting recent advances where information and communication technologies intersect with health, healthcare, life sciences, and biomedicine. Topics include acquisition, transmission, storage, retrieval, management, and analysis of biomedical and health information. The journal covers applications of information technologies in healthcare, patient monitoring, preventive care, early disease diagnosis, therapy discovery, and personalized treatment protocols. It explores electronic medical and health records, clinical information systems, decision support systems, medical and biological imaging informatics, wearable systems, body area/sensor networks, and more. Integration-related topics like interoperability, evidence-based medicine, and secure patient data are also addressed.
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