J Shanghai Jiaotong Univ Sci ›› 2025, Vol. 30 ›› Issue (4): 683-692.doi: 10.1007/s12204-024-2708-1
收稿日期:
2023-10-19
接受日期:
2023-11-11
发布日期:
2025-07-31
肖显子,苗玉彬
Received:
2023-10-19
Accepted:
2023-11-11
Published:
2025-07-31
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。
中图分类号:
. 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.
[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. |
[1] | . CT-MFENet:基于全局-局部特征融合的用于视网膜血管分割的上下文Transformer和多尺度特征提取网络[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(4): 668-682. |
[2] | . 血管介入手术路径规划及三维视觉导航[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(3): 472-481. |
[3] | . 基于毫米波雷达的智能心率提取方法[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(3): 493-498. |
[4] | . 基于变换学习和结构化低秩模型的并行成像快速重构算法[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(3): 499-509. |
[5] | . 用于内窥镜图像息肉检测的实时轻量级卷积神经网络[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(3): 521-534. |
[6] | . 基于改进加权融合的胶囊内镜肠道内壁图像拼接方法[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(3): 535-544. |
[7] | . 基于外积有效和字典学习的改进灵敏度编码重建算法[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(3): 555-565. |
[8] | . 迁移学习和注意机制融合用于CT图像COVID-19病灶分割的计算机辅助诊断[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(3): 566-581. |
[9] | . 基于蝶形空洞几何蒸馏的磁共振成像重建[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(3): 591-599. |
[10] | . 基于改进差分进化极限学习机的锂离子电池健康状态估计[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(2): 252-261. |
[11] | . 基于改进FCOS算法的钢丝绳芯输送带损伤X射线图像检测[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(2): 309-318. |
[12] | . 基于双流自编码器的无监督动作识别[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(2): 330-336. |
[13] | . 基于空间特征学习与多粒度特征融合的行人重识别[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(2): 363-374. |
[14] | 丁黎辉1, 2, 付立军1, 3, 杨光4, 5, 6, 万林4, 5, 常志军7. 基于视频的婴儿癫痫性痉挛综合征检测:建模、检测与评估[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(1): 1-9. |
[15] | 孔会扬1, 王殊轶1, 张璨2, 陈赞2, 3. 手术导板辅助增强现实技术与传统技术在椎弓根螺钉放置中的比较[J]. J Shanghai Jiaotong Univ Sci, 2025, 30(1): 10-17. |
阅读次数 | ||||||
全文 |
|
|||||
摘要 |
|
|||||