Title
Adaptive SVR Denoising Algorithm for Fetal Monitoring System
Abstract
This paper proposes a new fetal monitoring system, including the acquisition and the processing of fetal heart sounds (FHS). Based on the foundation of the stethoscope principle, a single-channel, non-invasive sensor is designed to acquire the fetal heart sounds, in which polyvinylidene fluoride (PVDF) membrane material is used as the core transducer. In the fetal heart sounds processing part, we propose a new method for denoising based on adaptive support vector regression (SVR) which has a good performance on curve fitting and effectively weakens the interference of additive noise. Thus, the clean fetal heart signals extracted from the interfered source can be further utilized to draw the fetal phonocardiogram (FPCG) and calculate the fetal heart rate (FHR).
Year
DOI
Venue
2018
10.1109/WCSP.2018.8555621
2018 10th International Conference on Wireless Communications and Signal Processing (WCSP)
Keywords
Field
DocType
fetal heart rate,fetal heart sounds,adaptive support vector regression,PVDF
Noise reduction,Transducer,Phonocardiogram,Stethoscope,Curve fitting,Pattern recognition,Computer science,Support vector machine,Real-time computing,Interference (wave propagation),Artificial intelligence,Fetal monitoring
Conference
ISSN
ISBN
Citations 
2325-3746
978-1-5386-6120-8
0
PageRank 
References 
Authors
0.34
1
5
Name
Order
Citations
PageRank
Zhenyuan Wang168490.22
Jianjun Wei200.34
Xiaohui Li328.19
Zelin Liu400.34
Fan Su500.34