基于短时长毫米波雷达回波序列的心率感知方法

doi:10.1007/s12204-024-2708-1

摘要/Abstract

摘要： 针对基于毫米波雷达的心率检测方法性能较低、数据信噪比要求较高、实时性不高等问题，设计了针对低信噪比和带有数据缺失的生命体征微弱信号的心率感知方法。首先对变长回波序列设计信号掩膜，在此基础上针对干扰噪声设计基于回波形态的信号映射方法，并添加可学习的位置编码以表征信号时序特征，然后通过transformer编码器模块匹配计算，最终构建了基于深度学习框架的时间序列全局回归模型。完成数据集制备及模型训练后，经过性能分析实验、抗干扰能力实验、对比实验验证，上述方法可在2~5 s的较短信号时间段内达到96.30%的准确率，同时适用于数据缺失及噪声干扰场景，能有效地实现短时雷达回波信号的心率体征参数精确感知。

关键词: 毫米波雷达，心率感知，全局回归模型

Abstract: Addressing challenges such as low performance, high data signal-to-noise ratio requirements, and limited real-time capabilities in existing heart rate detection methods based on millimeter wave radar, this study presents a heart rate sensing approach tailored for weak vital sign signals characterized by low signal-to-noise ratio and missing data. The method applies a signal mask for echo sequences with variable length. Building upon this signal mask, a signal mapping technique that leverages morphology is devised to mitigate interference and noise. Additionally, learnable position encoding is incorporated to capture temporal features within the signal. Subsequently, a transformer encoder module is employed for matching and computation, culminating in the development of a time-series global regression model based on deep learning framework. Following the preparation of the dataset and model training, the proposed approach is validated by performance analysis experiments, interference resistance tests, and comparative experiments. Results indicate that this method achieves an impressive accuracy of 96.30% within signal durations ranging from 2 s to 5 s, and it is suitable for scenarios involving missing data and noise interference. Importantly, this approach effectively enables a precise heart rate sensing from short-duration radar signals.

Key words: millimeter wave radar, heart rate sensing, global regression model

中图分类号:

TP391
R-331

. 基于短时长毫米波雷达回波序列的心率感知方法[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(4): 683-692.

Xiao Xianzi, Miao Yubin. Heart Rate Sensing Method Based on Short Millimeter Wave Radar Sequence[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(4): 683-692.

参考文献

[1] YANG H M. Dynamic trend of China's population ageing and new characteristics of the elderly [J]. Population Research, 2022, 46(5): 104-116 (in Chinese). [2] LI C Z, LUBECKE V M, BORIC-LUBECKE O, et al. A review on recent advances in Doppler radar sensors for noncontact healthcare monitoring [J]. IEEE Transactions on Microwave Theory and Techniques, 2013, 61(5): 2046-2060. [3] XIA W J, LI Y, DONG S Q. Radar-based high-accuracy cardiac activity sensing [J]. IEEE Transactions on Instrumentation and Measurement, 2021, 70: 1-13. [4] LI C Z, LING J, LI J, et al. Accurate Doppler radar noncontact vital sign detection using the RELAX algorithm [J]. IEEE Transactions on Instrumentation and Measurement, 2010, 59(3): 687-695. [5] BECHET P, MITRAN R, MUNTEANU M. A non-contact method based on multiple signal classification algorithm to reduce the measurement time for accurately heart rate detection [J]. Review of Scientific Instruments, 2013, 84(8): 084707. [6] ALIZADEH M, SHAKER G, DE ALMEIDA J C M, et al. Remote monitoring of human vital signs using mm-wave FMCW radar [J]. IEEE Access, 2019, 7: 54958-54968. [7] SCHIRES E, GEORGIOU P, LANDE T S. Vital sign monitoring through the back using an UWB impulse radar with body coupled antennas [J]. IEEE Transactions on Biomedical Circuits and Systems, 2018, 12(2): 292-302. [8] NOSRATI M, TAVASSOLIAN N. High-accuracy heart rate variability monitoring using Doppler radar based on Gaussian pulse train modeling and FTPR algorithm [J]. IEEE Transactions on Microwave Theory and Techniques, 2018, 66(1): 556-567. [9] WANG Y, WANG W, ZHOU M, et al. Remote monitoring of human vital signs based on 77-GHz mm-wave FMCW radar [J]. Sensors, 2020, 20(10): 2999. [10] HU W, ZHAO Z Y, WANG Y F, et al. Noncontact accurate measurement of cardiopulmonary activity using a compact quadrature Doppler radar sensor [J]. IEEE Transactions on Bio-Medical Engineering, 2014, 61(3): 725-735. [11] DUAN Z Z, LIANG J. Non-contact detection of vital signs using a UWB radar sensor [J]. IEEE Access, 2019, 7: 36888-36895. [12] XIONG Y Y, PENG Z K, GU C Z, et al. Differential enhancement method for robust and accurate heart rate monitoring via microwave vital sign sensing [J]. IEEE Transactions on Instrumentation and Measurement, 2020, 69(9): 7108-7118. [13] ZHANG H Y. Heartbeat monitoring with an mm-wave radar based on deep learning: A novel approach for training and classifying heterogeneous signals [J]. Remote Sensing Letters, 2020, 11(11): 993-1001. [14] SALUJA J, CASANOVA J, LIN J. A supervised machine learning algorithm for heart-rate detection using Doppler motion-sensing radar [J]. IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology, 2020, 4(1): 45-51. [15] GONG J A, ZHANG X Y, LIN K X, et al. RF vital sign sensing under free body movement [J]. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2021, 5(3): 1-22. [16] TSAI Y C, LAI S H, HO C J, et al. High accuracy respiration and heart rate detection based on artificial neural network regression [C]//2020 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society. Montreal, Canada. IEEE, 2020: 232-235. [17] VASWANI A, SHAZEER N, PARMAR N, et al. Attention is all you need [C]// 31st International Conference on Neural Information Processing Systems. Long Beach: NIPS, 2017: 6000-6010. [18] GEHRING J, AULI M, GRANGIER D, et al. Convolutional sequence to sequence learning [C]// 34th International Conference on Machine Learning. Sydney: IMLS, 2017: 1243-1252. [19] SCHELLENBERGER S, SHI K, STEIGLEDER T, et al. A dataset of clinically recorded radar vital signs with synchronised reference sensor signals [J]. Scientific Data, 2020, 7: 291. [20] LIU L, JIANG H, HE P, et al. On the variance of the adaptive learning rate and beyond [DB/OL]. (2019-08-08). https://arxiv.org/abs/1908.03265 [21] BLAND J M, ALTMAN D G. Statistical methods for assessing agreement between two methods of clinical measurement [J]. International Journal of Nursing Studies, 2010, 47(8): 931-936. [22] LV W J, HE W D, LIN X P, et al. Non-contact monitoring of human vital signs using FMCW millimeter wave radar in the 120 GHz band [J]. Sensors, 2021, 21(8): 2732. [23] DU Y, YANG A K, LI B B, et al. 77GHz millimeter-wave radar vital signs detection based on GA-VMD algorithm [C]// 2nd International Conference on Artificial Intelligence, Big Data and Algorithms. Nanjing: VDE, 2022: 1-7. [24] WU J C, CUI H, DAHNOUN N. A novel heart rate detection algorithm with small observing window using millimeter-wave radar [C]//2022 11th Mediterranean Conference on Embedded Computing. Budva: IEEE, 2022: 1-4.