Camera-Based Seismocardiogram for Heart Rate Variability Monitoring

被引:4
作者
Liu, Lin [1 ]
Yu, Dongfang [2 ]
Lu, Hongzhou [3 ]
Shan, Caifeng [1 ,4 ,5 ]
Wang, Wenjin [2 ]
机构
[1] Shandong Univ Sci & Technol, Coll Elect Engn & Automat, Qingdao 266590, Peoples R China
[2] Southern Univ Sci & Technol, Coll Engn, Dept Biomed Engn, Shenzhen 518000, Peoples R China
[3] Third Peoples Hosp Shenzhen, Shenzhen 518000, Peoples R China
[4] Nanjing Univ, State Key Lab Novel Software Technol, Nanjing 210023, Peoples R China
[5] Nanjing Univ, Sch Intelligence Sci & Technol, Nanjing 210023, Peoples R China
基金
国家重点研发计划;
关键词
Heart rate variability; speckle vibrometry; seismocardiogram; non-contact monitoring; SHORT-TERM ANALYSIS; RELIABILITY; NONCONTACT;
D O I
10.1109/JBHI.2024.3370394
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Heart rate variability (HRV) is a crucial metric that quantifies the variation between consecutive heartbeats, serving as a significant indicator of autonomic nervous system (ANS) activity. It has found widespread applications in clinical diagnosis, treatment, and prevention of cardiovascular diseases. In this study, we proposed an optical model for defocused speckle imaging, to simultaneously incorporate out-of-plane translation and rotation-induced motion for highly-sensitive non-contact seismocardiogram (SCG) measurement. Using electrocardiogram (ECG) signals as the gold standard, we evaluated the performance of photoplethysmogram (PPG) signals and speckle-based SCG signals in assessing HRV. The results indicated that the HRV parameters measured from SCG signals extracted from laser speckle videos showed higher consistency with the results obtained from the ECG signals compared to PPG signals. Additionally, we confirmed that even when clothing obstructed the measurement site, the efficacy of SCG signals extracted from the motion of laser speckle patterns persisted in assessing the HRV levels. This demonstrates the robustness of camera-based non-contact SCG in monitoring HRV, highlighting its potential as a reliable, non-contact alternative to traditional contact-PPG sensors.
引用
收藏
页码:2794 / 2805
页数:12
相关论文
共 52 条
  • [41] An Efficient Algorithm for Automatic Peak Detection in Noisy Periodic and Quasi-Periodic Signals
    Scholkmann, Felix
    Boss, Jens
    Wolf, Martin
    [J]. ALGORITHMS, 2012, 5 (04): : 588 - 603
  • [42] An Overview of Heart Rate variability Metrics and Norms
    Shaffer, Fred
    Ginsberg, J. P.
    [J]. FRONTIERS IN PUBLIC HEALTH, 2017, 5
  • [44] Heart Rate Variability Analysis on Electrocardiograms, Seismocardiograms and Gyrocardiograms on Healthy Volunteers
    Siecinski, Szymon
    Kostka, Pawel S.
    Tkacz, Ewaryst J.
    [J]. SENSORS, 2020, 20 (16) : 1 - 16
  • [45] Siecinski S, 2019, IEEE ENG MED BIO, P4913, DOI [10.1109/EMBC.2019.8857452, 10.1109/embc.2019.8857452]
  • [46] Comparison of HRV indices obtained from ECG and SCG signals from CEBS database
    Siecinski, Szymon
    Tkacz, Ewaryst J.
    Kostka, Pawel S.
    [J]. BIOMEDICAL ENGINEERING ONLINE, 2019, 18 (1)
  • [47] Siecinski S, 2018, IEEE ENG MED BIO, P5697, DOI 10.1109/EMBC.2018.8513551
  • [48] Noncontact imaging photoplethysmography to effectively access pulse rate variability
    Sun, Yu
    Hu, Sijung
    Azorin-Peris, Vicente
    Kalawsky, Roy
    Greenwaldc, Stephen
    [J]. JOURNAL OF BIOMEDICAL OPTICS, 2013, 18 (06)
  • [49] Recent Advances in Seismocardiography
    Taebi, Amirtaha
    Solar, Brian E.
    Bomar, Andrew J.
    Sandler, Richard H.
    Mansy, Hansen A.
    [J]. VIBRATION, 2019, 2 (01): : 64 - 86
  • [50] A Hidden Markov Model for Seismocardiography
    Wahlstrom, Johan
    Skog, Isaac
    Handel, Peter
    Khosrow-Khavar, Farzad
    Tavakolian, Kouhyar
    Stein, Phyllis K.
    Nehorai, Arye
    [J]. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2017, 64 (10) : 2361 - 2372