Power spectrum analysis of fetal heart rate variability using the abdominal maternal electrocardiogram |
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| Affiliation: | 1. Patient Care and Monitoring Department, Philips Research, Eindhoven, the Netherlands;2. AI Data Science & Digital Twin Department, Philips Research, Eindhoven, the Netherlands;3. Eindhoven University of Technology, Electrical Engineering Department, Eindhoven, the Netherlands;1. AI Data Science & Digital Twin Department, Philips Research, Eindhoven, the Netherlands;2. Patient Care and Monitoring Department, Philips Research, Eindhoven, the Netherlands;3. Eindhoven University of Technology, Electrical Engineering Department, Eindhoven, the Netherlands;1. Department of Electrical Engineering, Institute of Infrastructure, Technology, Research and Management (IITRAM), Ahmedabad, 380026, India;2. Nagee Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Singapore, 599489, Singapore;3. Department of Biomedical Engineering, School of Science and Technology, SUSS University, Singapore;4. Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Malaysia;1. Electrical and Electronics Engineering, Aksaray University, Aksaray, Turkey;2. Computer Engineering Department, Ankara University, Ankara, Turkey;3. Computer Engineering Department, Baskent University, Ankara, Turkey;4. Computer Engineering Department, AYBU, Ankara, Turkey |
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| Abstract: | A signal analysis procedure is described for obtaining the power spectrum of the fetal and maternal heart rates as recorded from the abdomen. This technique, which includes the subtraction of an averaged maternal ECG waveform using a cross-correlation function and the fast Fourier transform algorithm, enables the detection of all the fetal QRS complexes in spite of their coincidence with the maternal ECGs. The power spectrum of the fetal heart rates (FHR) obtained from 15 women at 32–41 weeks gestation were studied and two indices were measured which are related to the long term and short term variabilities in the FHR signal. It was found that quantitative evaluation of the FHR variability can be obtained using power spectrum analysis. |
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