Noise reduction by perfect-translation-invariant complex discrete wavelet transforms for fetal electrocardiography and magnetocardiography

作者：Ishikawa Yasuhiro^*; Horigome Hitoshi; Kandori Akihiko; Toda Hiroshi; Zhang Zhong

来源：International Journal of Wavelets, Multiresolution and Information Processing, 2014, 12(4): 1460008.

DOI：10.1142/S021969131460008X

• Perfect translation invariance
• noise reduction by wavelet thresholding
• fetal electrocardiography
• fetal magnetocardiography

Echocardiography is widely used for the diagnosis of fetal cardiac arrhythmias. However, this method does not detect configurational changes in the electrocardiogram (ECG) such as life-threatening changes in QRS and the prolongation of the QT interval. Fetal magnetocardiography (fMCG) and fetal electrocardiography (fECG) are valuable tools for the detection of electrophysiological cardiac signals although both have certain limitations. Such techniques must deal with excess internal noise such as maternal respiratory movements, fetal movements, muscle contraction and fetal body movement and external noise (e.g., electromagnetic waves). Heart rate variability (HRV) is a well-known phenomenon with fluctuation in the time interval between heartbeats. The lack of translation invariance is a serious defect in the conventional wavelet transforms (discrete wavelet transform (DWT)). Fluctuation of the impulse response at each energy level is observed in the multi-resolution analysis (MRA). Configurational changes in the ECG waveforms are frequently observed after noise reduction by the conventional wavelet transforms. Both the lack of translation invariance of conventional wavelet transforms and HRV cause deformation of the ECG waveforms. We describe here the CDWTs with perfect translation invariance (PTI). Compared with conventional wavelets, PTI of the fECG and fMCG resulted in only minor configurational changes in the ECG waveforms. This technique yields persistently stable ECG waveforms, including P wave and QRS complex. First, an independent component analysis (ICA) was applied to fECG or fMCG data to remove noise. We provide an example to show that the morphological change in QRS complex is barely affected when PTI is applied to normal fECG. Examples of fetal arrhythmias, such as ventricular trigeminy, ventricular bigeminy and premature atrial contraction are demonstrated using this technique. The results lead us to the conclusion that ICA and noise reduction in fECG and fMCG by PTI are promising methods for the diagnosis of fetal arrhythmia.

• 出版日期2014-7