A robust physiology-based source separation method for QRS detection in low amplitude fetal ECG recordings

被引:23
作者
Vullings, R. [1 ]
Peters, C. H. L. [2 ]
Hermans, M. J. M. [3 ]
Wijn, P. F. F. [3 ]
Oei, S. G. [4 ]
Bergmans, J. W. M. [1 ]
机构
[1] Eindhoven Univ Technol, Dept Elect Engn, NL-5600 MB Eindhoven, Netherlands
[2] Jeroen Bosch Hosp, Dept Clin Phys, Den Bosch, Netherlands
[3] Maxima Med Ctr, Dept Clin Phys, Veldhoven, Netherlands
[4] Maxima Med Ctr, Dept Obstet & Gynecol, Veldhoven, Netherlands
关键词
fetal electrocardiography; QRS detection; blind source separation; medical; signal processing; HEART-RATE-VARIABILITY; ELECTROCARDIOGRAM EXTRACTION; ALGORITHMS;
D O I
10.1088/0967-3334/31/7/005
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
The use of the non-invasively obtained fetal electrocardiogram (ECG) in fetal monitoring is complicated by the low signal-to-noise ratio (SNR) of ECG signals. Even after removal of the predominant interference (i.e. the maternal ECG), the SNR is generally too low for medical diagnostics, and hence additional signal processing is still required. To this end, several methods for exploiting the spatial correlation of multi-channel fetal ECG recordings from the maternal abdomen have been proposed in the literature, of which principal component analysis (PCA) and independent component analysis (ICA) are the most prominent. Both PCA and ICA, however, suffer from the drawback that they are blind source separation (BSS) techniques and as such suboptimum in that they do not consider a priori knowledge on the abdominal electrode configuration and fetal heart activity. In this paper we propose a source separation technique that is based on the physiology of the fetal heart and on the knowledge of the electrode configuration. This technique operates by calculating the spatial fetal vectorcardiogram (VCG) and approximating the VCG for several overlayed heartbeats by an ellipse. By subsequently projecting the VCG onto the long axis of this ellipse, a source signal of the fetal ECG can be obtained. To evaluate the developed technique, its performance is compared to that of both PCA and ICA and to that of augmented versions of these techniques (aPCA and aICA; PCA and ICA applied on preprocessed signals) in generating a fetal ECG source signal with enhanced SNR that can be used to detect fetal QRS complexes. The evaluation shows that the developed source separation technique performs slightly better than aPCA and aICA and outperforms PCA and ICA and has the main advantage that, with respect to aPCA/PCA and aICA/ICA, it performs more robustly. This advantage renders it favorable for employment in automated, real-time fetal monitoring applications.
引用
收藏
页码:935 / 951
页数:17
相关论文
共 23 条
  • [1] SPECTRAL-ANALYSIS OF THE FETAL ELECTROCARDIOGRAM
    ABBOUD, S
    SADEH, D
    [J]. COMPUTERS IN BIOLOGY AND MEDICINE, 1989, 19 (06) : 409 - 415
  • [2] Continuous cardiotocography (CTG) as a form of electronic fetal monitoring (EFM) for fetal assessment during labour
    Alfirevic, Z.
    Devane, D.
    Gyte, G. M. L.
    [J]. COCHRANE DATABASE OF SYSTEMATIC REVIEWS, 2006, (03):
  • [3] [Anonymous], 2006, Pattern recognition and machine learning
  • [4] BURGER HC, 1946, BRIT HEART J, V8, P157
  • [5] VARIABILITY ANALYSIS OF FETAL HEART-RATE SIGNALS AS OBTAINED FROM ABDOMINAL ELECTROCARDIOGRAPHIC RECORDINGS
    CERUTTI, S
    BASELLI, G
    CIVARDI, S
    FERRAZZI, E
    MARCONI, AM
    PAGANI, M
    PARDI, G
    [J]. JOURNAL OF PERINATAL MEDICINE, 1986, 14 (06) : 445 - 452
  • [6] Fetal electrocardiogram extraction by blind source subspace separation
    De Lathauwer, L
    De Moor, B
    Vandewalle, O
    [J]. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2000, 47 (05) : 567 - 572
  • [7] DOWER G E, 1980, Clinical Cardiology, V3, P87
  • [8] AN ACCURATE, CLINICALLY PRACTICAL SYSTEM FOR SPATIAL VECTORCARDIOGRAPHY
    FRANK, E
    [J]. CIRCULATION, 1956, 13 (05) : 737 - 749
  • [9] Harmeling S., 2003, 4 INT S IND COMP AN, P149
  • [10] Fast and robust fixed-point algorithms for independent component analysis
    Hyvärinen, A
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS, 1999, 10 (03): : 626 - 634