Suppr超能文献

[基于多通道雷达数据融合的人体心率精确测量]

[Precise measurement of human heart rate based on multi-channel radar data fusion].

作者信息

Guo Hongrui, Cao Huimin, Yang Keqi, Zhang Zhushanying

机构信息

College of Biomedical Engineering, South-Central Minzu University, Wuhan 430074, P. R. China.

Key Laboratory of Cognitive Science, State Ethnic Affairs Commission, Wuhan 430074, P. R. China.

出版信息

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2024 Jun 25;41(3):461-468. doi: 10.7507/1001-5515.202307010.

Abstract

To achieve non-contact measurement of human heart rate and improve its accuracy, this paper proposes a method for measuring human heart rate based on multi-channel radar data fusion. The radar data were firstly extracted by human body position identification, phase extraction and unwinding, phase difference, band-pass filtering optimized by power spectrum entropy, and fast independent component analysis for each channel data. After overlaying and fusing the four-channel data, the heartbeat signal was separated using frost-optimized variational modal decomposition. Finally, a chirp Z-transform was introduced for heart rate estimation. After validation with 40 sets of data, the average root mean square error of the proposed method was 2.35 beats per minute, with an average error rate of 2.39%, a Pearson correlation coefficient of 0.97, a confidence interval of [-4.78, 4.78] beats per minute, and a consistency error of -0.04. The experimental results show that the proposed measurement method performs well in terms of accuracy, correlation, and consistency, enabling precise measurement of human heart rate.

摘要

为实现人体心率的非接触式测量并提高其准确性,本文提出了一种基于多通道雷达数据融合的人体心率测量方法。首先通过人体位置识别、相位提取与解缠、相位差、基于功率谱熵优化的带通滤波以及对各通道数据进行快速独立成分分析来提取雷达数据。在对四通道数据进行叠加融合后,使用经霜优化的变分模态分解来分离心跳信号。最后,引入线性调频Z变换进行心率估计。经40组数据验证,该方法的平均均方根误差为每分钟2.35次心跳,平均错误率为2.39%,皮尔逊相关系数为0.97,置信区间为每分钟[-4.78, 4.78]次心跳,一致性误差为-0.04。实验结果表明,所提出的测量方法在准确性、相关性和一致性方面表现良好,能够实现对人体心率的精确测量。

相似文献

1
[Precise measurement of human heart rate based on multi-channel radar data fusion].
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2024 Jun 25;41(3):461-468. doi: 10.7507/1001-5515.202307010.
2
[Non-contact Blood Pressure Measurement Method Using Frequency Modulated Continuous Wave Radar].
Zhongguo Yi Liao Qi Xie Za Zhi. 2022 Sep 30;46(5):481-484. doi: 10.3969/j.issn.1671-7104.2022.05.002.
3
Respiration and heart rates measurement using 77GHz FMCW radar with blind source separation algorithm.
Annu Int Conf IEEE Eng Med Biol Soc. 2022 Jul;2022:842-845. doi: 10.1109/EMBC48229.2022.9871987.
4
6
A Non-Contact Detection Method for Multi-Person Vital Signs Based on IR-UWB Radar.
Sensors (Basel). 2022 Aug 16;22(16):6116. doi: 10.3390/s22166116.
7
Millimeter-Wave Radar-Based Identity Recognition Algorithm Built on Multimodal Fusion.
Sensors (Basel). 2024 Jun 21;24(13):4051. doi: 10.3390/s24134051.
8
Heart rate detection using single-channel Doppler radar system.
Annu Int Conf IEEE Eng Med Biol Soc. 2022 Jul;2022:1953-1956. doi: 10.1109/EMBC48229.2022.9871199.
9
Non-Contact Measurement of Human Respiration and Heartbeat Using W-band Doppler Radar Sensor.
Sensors (Basel). 2020 Sep 12;20(18):5209. doi: 10.3390/s20185209.
10

本文引用的文献

1
Sparsity-Based Multi-Person Non-Contact Vital Signs Monitoring via FMCW Radar.
IEEE J Biomed Health Inform. 2023 Jun;27(6):2806-2817. doi: 10.1109/JBHI.2023.3255740. Epub 2023 Jun 5.
2
FiCA: A Fixed-Point Custom Architecture FastICA for Real-Time and Latency-Sensitive Applications.
IEEE Trans Neural Syst Rehabil Eng. 2022;30:2896-2905. doi: 10.1109/TNSRE.2022.3213010. Epub 2022 Oct 20.
4
5
[An improved peak extraction method for heart rate estimation].
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2019 Oct 25;36(5):834-840. doi: 10.7507/1001-5515.201810041.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验