Back to Search
Start Over
Recovery of the fetal electrocardiogram for morphological analysis from two trans-abdominal channels via optimal shrinkage
- Source :
- Physiological measurement. 40(11)
- Publication Year :
- 2019
-
Abstract
- We propose a novel algorithm to recover fetal electrocardiogram (ECG) for both the fetal heart rate analysis and morphological analysis of its waveform from two or three trans-abdominal maternal ECG channels. We design an algorithm based on the optimal-shrinkage and the nonlocal Euclidean median under the wave-shape manifold model. For the fetal heart rate analysis, the algorithm is evaluated on publicly available database, 2013 PhyioNet/Computing in Cardiology Challenge, set A. For the morphological analysis, we propose to simulate semi-real databases by mixing the MIT-BIH Normal Sinus Rhythm Database and MITDB Arrhythmia Database. For the fetal R peak detection, the proposed algorithm outperforms all algorithms under comparison. For the morphological analysis, the algorithm provides an encouraging result in recovery of the fetal ECG waveform, including PR, QT and ST intervals, even when the fetus has arrhythmia. To the best of our knowledge, this is the first work focusing on recovering the fetal ECG for morphological analysis from two or three channels with an algorithm potentially applicable for continuous fetal electrocardiographic monitoring, which creates the potential for long term monitoring purpose.<br />Comment: 25 pages, 6 figures
- Subjects :
- Signal Processing (eess.SP)
FOS: Computer and information sciences
Physiology
Computer science
0206 medical engineering
Biomedical Engineering
Biophysics
02 engineering and technology
Statistics - Applications
03 medical and health sciences
Electrocardiography
0302 clinical medicine
Fetus
Pregnancy
Physiology (medical)
Abdomen
medicine
FOS: Electrical engineering, electronic engineering, information engineering
Waveform
Humans
Applications (stat.AP)
cardiovascular diseases
Electrical Engineering and Systems Science - Signal Processing
Normal Sinus Rhythm
medicine.diagnostic_test
business.industry
Pattern recognition
Heart
Fetal electrocardiogram
020601 biomedical engineering
Peak detection
Fetal ecg
Long term monitoring
Morphological analysis
Female
Artificial intelligence
business
030217 neurology & neurosurgery
Algorithms
Subjects
Details
- ISSN :
- 13616579
- Volume :
- 40
- Issue :
- 11
- Database :
- OpenAIRE
- Journal :
- Physiological measurement
- Accession number :
- edsair.doi.dedup.....d6d4e9dac936e71e4a1f2cb40d063166