Convolutional Neural Networks for the Real-Time Monitoring of Vital Signs Based on Impulse Radio Ultrawide-Band Radar during Sleep

被引:9
|
作者
Choi, Sang Ho [1 ]
Yoon, Heenam [2 ]
机构
[1] Kwangwoon Univ, Sch Comp & Informat Engn, Seoul 01897, South Korea
[2] Sangmyung Univ, Dept Human Ctr Artificial Intelligence, Seoul 03016, South Korea
基金
新加坡国家研究基金会;
关键词
IR-UWB radar; noncontact; vital-sign monitoring; real time; deep learning; UWB; GESTURES;
D O I
10.3390/s23063116
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Vital signs provide important biometric information for managing health and disease, and it is important to monitor them for a long time in a daily home environment. To this end, we developed and evaluated a deep learning framework that estimates the respiration rate (RR) and heart rate (HR) in real time from long-term data measured during sleep using a contactless impulse radio ultrawide-band (IR-UWB) radar. The clutter is removed from the measured radar signal, and the position of the subject is detected using the standard deviation of each radar signal channel. The 1D signal of the selected UWB channel index and the 2D signal applied with the continuous wavelet transform are entered as inputs into the convolutional neural-network-based model that then estimates RR and HR. From 30 recordings measured during night-time sleep, 10 were used for training, 5 for validation, and 15 for testing. The average mean absolute errors for RR and HR were 2.67 and 4.78, respectively. The performance of the proposed model was confirmed for long-term data, including static and dynamic conditions, and it is expected to be used for health management through vital-sign monitoring in the home environment.
引用
收藏
页数:15
相关论文
共 50 条
  • [1] Principles of space-time array processing for ultrawide-band impulse radar and radio communications
    Hussain, MGM
    IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2002, 51 (03) : 393 - 403
  • [2] Real-time Monitoring of Vital Signs based on Miniaturized Ultra-wideband Radar
    Guo, Yuchao
    Du, Naike
    Ye, Xiuzhu
    2022 IEEE MTT-S INTERNATIONAL MICROWAVE BIOMEDICAL CONFERENCE (IMBIOC), 2022, : 93 - 95
  • [3] Challenges in Real-Time Vital Signs Monitoring for Persons During Exercises
    Hara S.
    Yomo H.
    Miyamoto R.
    Kawamoto Y.
    Okuhata H.
    Kawabata T.
    Nakamura H.
    Hara, Shinsuke (hara@info.eng.osaka-cu.ac.jp), 1600, Springer Science and Business Media, LLC (24): : 91 - 108
  • [4] A Real-Time Recognition Algorithm for Speed Limit Signs Based on Convolutional Neural Networks
    Sun, Wencai
    Li, Wei
    Li, Shiwu
    CICTP 2020: ADVANCED TRANSPORTATION TECHNOLOGIES AND DEVELOPMENT-ENHANCING CONNECTIONS, 2020, : 3914 - 3927
  • [5] Real-Time and Noncontact Impulse Radio Radar System for μm Movement Accuracy and Vital-Sign Monitoring Applications
    Hung, Wei-Ping
    Chang, Chia-Hung
    Lee, Tsern-Huei
    IEEE SENSORS JOURNAL, 2017, 17 (08) : 2349 - 2358
  • [6] The vital signs real-time monitoring system based on Internet of things
    Shu, Minglei
    Tang, Meiyu
    Yang, Ming
    Wei, Nuo
    2017 4TH INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND CONTROL ENGINEERING (ICISCE), 2017, : 747 - 751
  • [7] Real-time ultrawide-band group delay profile monitoring through low-noise incoherent temporal interferometry
    Park, Yongwoo
    Malacarne, Antonio
    Azana, Jose
    OPTICS EXPRESS, 2011, 19 (05): : 3937 - 3944
  • [8] Demonstration on a Real-Time Vital Signs Monitoring System for Men during Exercise
    Hara, Shinsuke
    Shimazaki, Takunori
    2014 IEEE 16TH INTERNATIONAL CONFERENCE ON E-HEALTH NETWORKING, APPLICATIONS AND SERVICES (HEALTHCOM), 2014, : 122 - 123
  • [9] Real-time apnea-hypopnea event detection during sleep by convolutional neural networks
    Choi, Sang Ho
    Yoon, Heenam
    Kim, Hyun Seok
    Kim, Han Byul
    Kwon, Hyun Bin
    Oh, Sung Min
    Lee, Yu Jin
    Park, Kwang Suk
    COMPUTERS IN BIOLOGY AND MEDICINE, 2018, 100 : 123 - 131
  • [10] Elements of a Real-Time Vital Signs Monitoring System for Players during a Football Game
    Hara, Shinsuke
    Tsujioka, Tetsuo
    Shimazaki, Takunori
    Tezuka, Kouhei
    Ichikawa, Masayuki
    Ariga, Masato
    Nakamura, Hajime
    Kawabata, Takashi
    Watanabe, Kenji
    Ise, Masanao
    Arime, Noa
    Okuhata, Hiroyuki
    2014 IEEE 16TH INTERNATIONAL CONFERENCE ON E-HEALTH NETWORKING, APPLICATIONS AND SERVICES (HEALTHCOM), 2014, : 460 - 465