Heart rate measurement based on a time-lapse image

被引:250
|
作者
Takano, Chihiro [1 ]
Ohta, Yuji [1 ]
机构
[1] Ochanomizu Univ, Grad Sch Human & Sci, Tokyo 112, Japan
关键词
respiratory rate; heart rate; time-lapse image; non-contact measurement;
D O I
10.1016/j.medengphy.2006.09.006
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Using a time-lapse image acquired from a CCD camera, we developed a non-contact and non-invasive device, which could measure both the respiratory and pulse rate simultaneously. The time-lapse image of a part of the subject's skin was consecutively captured, and the changes in the average image brightness of the region of interest (ROI) were measured for 30 s. The brightness data were processed by a series of operations of interpolation as follows a first-order derivative, a low pass filter of 2 Hz, and a sixth-order auto-regressive (AR) spectral analysis. Fourteen sound and healthy female subjects (22-27 years of age) participated in the experiments. Each subject was told to keep a relaxed seating posture with no physical restriction. At the same time, heart rate was measured by a pulse oximeter and respiratory rate was measured by a thermistor placed at the external naris. Using AR spectral analysis, two clear peaks could be detected at approximately 0.3 and 1.2 Hz. The peaks were thought to correspond to the respiratory rate and the heart rate. Correlation coefficients of 0.90 and 0.93 were obtained for the measurement of heart rate and respiratory rate, respectively. (c) 2006 IPEM. Published by Elsevier Ltd. All rights reserved.
引用
下载
收藏
页码:853 / 857
页数:5
相关论文
共 50 条
  • [31] Prediction of spatial patterns of saturation time-lapse from time-lapse seismic
    Wu, JB
    Mukerji, T
    Journel, AG
    GEOSTATISTICS BANFF 2004, VOLS 1 AND 2, 2005, 14 : 671 - 680
  • [32] Time-Lapse Image Classification Using a Diffractive Neural Network
    Rahman, Md Sadman Sakib
    Ozcan, Aydogan
    ADVANCED INTELLIGENT SYSTEMS, 2023, 5 (05)
  • [33] Time-lapse image registration using the local similarity attribute
    Fomel, Sergey
    Jin, Long
    GEOPHYSICS, 2009, 74 (02) : A7 - A11
  • [34] Compressive Tracking Moving Cells in Time-Lapse Image Sequences
    Ding, Chen
    Li, Ying
    Pan, Yongsheng
    Zhou, Tao
    Gao, Pengcheng
    Xia, Yong
    PROCEEDINGS OF 2015 INTERNATIONAL CONFERENCE ON ORANGE TECHNOLOGIES (ICOT), 2015, : 75 - 78
  • [35] Robust and generalizable embryo selection based on artificial intelligence and time-lapse image sequences
    Berntsen, Jorgen
    Rimestad, Jens
    Lassen, Jacob Theilgaard
    Tran, Dang
    Kragh, Mikkel Fly
    PLOS ONE, 2022, 17 (02):
  • [36] Generation of Synthetic Image Datasets for Time-Lapse Fluorescence Microscopy
    Svoboda, David
    Ulman, Vladimir
    IMAGE ANALYSIS AND RECOGNITION, PT II, 2012, 7325 : 473 - 482
  • [37] Neural image enhancement and restoration for time-lapse SPM images
    Yasue, Fuma
    Shinjo, Kota
    Kondo, Yuki
    Akita, Kazutoshi
    Mitsuboshi, Hibiki
    Yoshimura, Masamichi
    Ukita, Norimichi
    JAPANESE JOURNAL OF APPLIED PHYSICS, 2022, 61 (10)
  • [38] An example of the measurement and practical applications of time-lapse seismic attenuation
    Blanchard, Thomas D.
    Delommot, Pauline
    GEOPHYSICS, 2015, 80 (02) : WA25 - WA34
  • [39] Sibling oocytes cultured in a time-lapse versus benchtop incubator: how time-lapse incubators improve blastocyst development and euploid rate
    Nobrega, N. G.
    Abdala, A.
    El-Damen, A.
    Arnanz, A.
    Bayram, A.
    Elkhatib, I.
    Lawrenz, B.
    Fatemi, H.
    De Munck, N.
    ZYGOTE, 2023, 31 (04) : 402 - 409
  • [40] TIME-LAPSE CINEMATOGRAPHY IN RESEARCH
    Evans, Raymond
    JOURNAL OF THE SOCIETY OF MOTION PICTURE ENGINEERS, 1931, 16 (05): : 547 - 552