Sensor array and electrode selection for non-invasive fetal electrocardiogram extraction by independent component analysis

被引：0
|
作者：
Vrins, F
Jutten, C
Verleysen, M
机构：
[1] Catholic Univ Louvain, Machine Learning Grp, B-1380 Louvain, Belgium
[2] Inst Natl Polytech Grenoble, Image & Signals Lab, F-38031 Grenoble, France
来源：
INDEPENDENT COMPONENT ANALYSIS AND BLIND SIGNAL SEPARATION | 2004年 / 3195卷
关键词：
D O I：
暂无
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Recently, non-invasive techniques to measure the fetal electrocardiogram (FECC) signal have given very promising results. However, the important question of the number and the location of the external sensors has been often discarded. In this paper, an electrode-array approach is proposed, it is combined with a sensor selection algorithm using a mutual information criterion. The sensor selection algorithm is run in parallel to an independent component analysis of the selected signals. The aim of this method is to make a real time extraction of the FECG possible. The results are shown on simulated biomedical signals.
引用
收藏
页码：1017 / 1024
页数：8
相关论文
共 50 条
  • [21] A Modified Independent Component Analysis Algorithm for Extrating the Fetal Electrocardiogram
    Yang Junchao
    Cheng, Peng
    Xiang, Qian
    2014 INTERNATIONAL CONFERENCE ON AUDIO, LANGUAGE AND IMAGE PROCESSING (ICALIP), VOLS 1-2, 2014, : 73 - 77
  • [22] Non-invasive fetal ECG analysis
    Clifford, Gari D.
    Silva, Ikaro
    Behar, Joachim
    Moody, George B.
    PHYSIOLOGICAL MEASUREMENT, 2014, 35 (08) : 1521 - 1536
  • [23] Electrode selection for noninvasive fetal electrocardiogram extraction using mutual information criteria
    Sameni, R.
    Vrins, F.
    Parmentier, F.
    Herail, C.
    Vigneron, V.
    Verleysen, M.
    Jutten, C.
    Shamsollahi, M. B.
    BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING, 2006, 872 : 97 - +
  • [24] Non-invasive heart rate monitor applying independent component analysis in videos
    Portilla, Karla
    Santos, Victor
    Fernanda Trujillo, Maria
    Rosales, Andres
    2017 INTERNATIONAL CONFERENCE ON INFORMATION SYSTEMS AND COMPUTER SCIENCE (INCISCOS), 2017, : 121 - 127
  • [25] Fetal electrocardiogram signal extraction and analysis method combining fast independent component analysis algorithm and convolutional neural network
    Yang Y.
    Hao J.
    Wu S.
    Shengwu Yixue Gongchengxue Zazhi/Journal of Biomedical Engineering, 2023, 40 (01): : 51 - 59
  • [26] The influence of betamethasone on fetal heart rate variability, obtained by non-invasive fetal electrocardiogram recordings
    Verdurmen, Kim M. J.
    Warmerdam, Guy J. J.
    Lempersz, Carlijn
    Hulsenboom, Alexandra D. J.
    Renckens, Joris
    Dieleman, Jeanne P.
    Vullings, Rik
    van Laar, Judith O. E. H.
    Oei, S. Guid
    EARLY HUMAN DEVELOPMENT, 2018, 119 : 8 - 14
  • [27] A Fetal Electrocardiogram Signal Extraction Algorithm Based on Fast One-Unit Independent Component Analysis with Reference
    Jia, Yanfei
    Yang, Xiaodong
    COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE, 2016, 2016
  • [28] Temporally Nonstationary Component Analysis; Application to Noninvasive Fetal Electrocardiogram Extraction
    Jamshidian-Tehrani, Fahimeh
    Sameni, Reza
    Jutten, Christian
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2020, 67 (05) : 1377 - 1386
  • [29] Extraction of Fetal ECG in a Non-invasive Way and Estimation of Fetal Heart Rate
    Khondakar, Md Fazlul Karim
    Sarowar, Md Hasib
    Hossain, Quazi Delwar
    2020 IEEE REGION 10 SYMPOSIUM (TENSYMP) - TECHNOLOGY FOR IMPACTFUL SUSTAINABLE DEVELOPMENT, 2020, : 358 - 361
  • [30] Independent component analysis with learning algorithm for electrocardiogram feature extraction and classification
    Jayasanthi, M.
    Rajendran, G.
    Vidhyakar, R. B.
    SIGNAL IMAGE AND VIDEO PROCESSING, 2021, 15 (02) : 391 - 399
12345