Non-intrusive Human Vital Sign Detection Using mmWave Sensing Technologies: A Review

Author:

Wu Yingxiao1ORCID,Ni Haocheng1ORCID,Mao Changlin1ORCID,Han Jianping1ORCID,Xu Wenyao2ORCID

Affiliation:

1. Hangzhou Dianzi University, China

2. University at Buffalo, USA

Abstract

Non-invasive human vital sign detection has gained significant attention in recent years, with its potential for contactless, long-term monitoring. Advances in radar systems have enabled non-contact detection of human vital signs, emerging as a crucial area of research. The movements of key human organs influence radar signal propagation, offering researchers the opportunity to detect vital signs by analyzing received electromagnetic (EM) signals. In this review, we provide a comprehensive overview of the current state-of-the-art in millimeter-wave (mmWave) sensing for vital sign detection. We explore human anatomy and various measurement methods, including contact and non-contact approaches, and summarize the principles of mmWave radar sensing. To demonstrate how EM signals can be harnessed for vital sign detection, we discuss four mmWave-based vital sign sensing (MVSS) signal models and elaborate on the signal processing chain for MVSS. Additionally, we present an extensive review of deep learning-based MVSS and compare existing studies. Finally, we offer insights into specific applications of MVSS (e.g., biometric authentication) and highlight future research trends in this domain.

Funder

Zhejiang Provincial Natural Science Foundation of China

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications

Reference139 articles.

1. Fortune Business Insights. Remote Patient Monitoring Devices Market Global Report [2028]. Retrieved from https://www.fortunebusinessinsights.com/remote-patient-monitoring-devices-market-106328

2. World Health Organization. Cardiovascular diseases (CVDs). Retrieved from https://www.who.int/en/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds)

3. World Health Organization. Noncommunicable diseases. Retrieved from https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases

4. Fengyu Wang Xiaolu Zeng Chenshu Wu Beibei Wang and K. J. Ray Liu. 2022. Driver vital signs monitoring using millimeter wave radio. IEEE Internet of Things Journal 9 13 (2022) 11283–11298.

5. Study on a novel UWB linear array human respiration model and detection method;Wu Shiyou;IEEE J. Select. Topics Appl. Earth Observ. Rem. Sens.,2016

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3