Yang Zihan, Liu Yinzhe, Yang Hao, Shi Jing, Hu Anyong, Xu Jun, Zhuge Xiaodong, Miao Jungang
School of Electronics and Information Engineering, Beihang University, Beijing 100191, China.
Emergency Department, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing 100730, China.
Biosensors (Basel). 2025 Jul 28;15(8):486. doi: 10.3390/bios15080486.
Continuous monitoring of respiratory patterns is essential for disease diagnosis and daily health care. Contact medical devices enable reliable respiratory monitoring, but can cause discomfort and are limited in some settings. Radar offers a noncontact respiration measurement method for continuous, real-time, high-precision monitoring. However, it is difficult for a single radar to characterize the coordination of chest and abdominal movements during measured breathing. Moreover, motion interference during prolonged measurements can seriously affect accuracy. This study proposes a dual radar system with customized narrow-beam antennas and signals to measure the chest and abdomen separately, and an adaptive dynamic time warping (DTW) algorithm is used to effectively suppress motion interference. The system is capable of reconstructing respiratory waveforms of the chest and abdomen, and robustly extracting various respiratory parameters via motion interference. Experiments on 35 healthy subjects, 2 patients with chronic obstructive pulmonary disease (COPD), and 1 patient with heart failure showed a high correlation between radar and respiratory belt signals, with correlation coefficients of 0.92 for both the chest and abdomen, a root mean square error of 0.80 bpm for the respiratory rate, and a mean absolute error of 3.4° for the thoracoabdominal phase angle. This system provides a noncontact method for prolonged respiratory monitoring, measurement of chest and abdominal asynchrony and apnea detection, showing promise for applications in respiratory disorder detection and home monitoring.
持续监测呼吸模式对于疾病诊断和日常医疗保健至关重要。接触式医疗设备能够实现可靠的呼吸监测，但会带来不适，且在某些情况下存在局限性。雷达提供了一种用于连续、实时、高精度监测的非接触式呼吸测量方法。然而，单个雷达很难在测量呼吸过程中表征胸部和腹部运动的协调性。此外，长时间测量过程中的运动干扰会严重影响准确性。本研究提出了一种双雷达系统，该系统采用定制的窄波束天线和信号分别测量胸部和腹部，并使用自适应动态时间规整（DTW）算法有效抑制运动干扰。该系统能够重建胸部和腹部的呼吸波形，并通过运动干扰稳健地提取各种呼吸参数。对35名健康受试者、2名慢性阻塞性肺疾病（COPD）患者和1名心力衰竭患者进行的实验表明，雷达信号与呼吸带信号之间具有高度相关性，胸部和腹部的相关系数均为0.92，呼吸频率的均方根误差为0.80 bpm，胸腹相位角的平均绝对误差为3.4°。该系统提供了一种用于长时间呼吸监测、测量胸腹不同步和检测呼吸暂停的非接触方法，在呼吸障碍检测和家庭监测应用中显示出前景。
