Recent Advances in Doppler Signal Processing and Modelling Techniques for Fetal Monitoring

2018 ◽  
Keyword(s):  
Signal Processing ◽  
Fetal Monitoring ◽  
Doppler Signal ◽  
Recent Advances ◽  
Modelling Techniques

scholarly journals Non-Adaptive Methods for Fetal ECG Signal Processing: A Review and Appraisal

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3648 ◽  
Author(s):  
Rene Jaros ◽  
Radek Martinek ◽  
Radana Kahankova
Keyword(s):  
Signal Processing ◽  
Wavelet Transforms ◽  
Principal Component ◽  
Fetal Monitoring ◽  
Adaptive Methods ◽  
Component Analysis ◽  
Adaptive Signal Processing ◽  
Extensive Literature ◽  
Fetal Electrocardiogram ◽  
Fetal Ecg

Fetal electrocardiography is among the most promising methods of modern electronic fetal monitoring. However, before they can be fully deployed in the clinical practice as a gold standard, the challenges associated with the signal quality must be solved. During the last two decades, a great amount of articles dealing with improving the quality of the fetal electrocardiogram signal acquired from the abdominal recordings have been introduced. This article aims to present an extensive literature survey of different non-adaptive signal processing methods applied for fetal electrocardiogram extraction and enhancement. It is limiting that a different non-adaptive method works well for each type of signal, but independent component analysis, principal component analysis and wavelet transforms are the most commonly published methods of signal processing and have good accuracy and speed of algorithms.

Laser Doppler Velocimetry Signal Processing Based on Spectral Refinement and Correction

2011 ◽  
Vol 383-390 ◽  
pp. 6319-6323
Author(s):  
Nian Long Song ◽  
Da Zhang ◽  
Qi Li
Keyword(s):  
Signal Processing ◽  
Laser Doppler Velocimetry ◽  
Operation Time ◽  
Laser Doppler ◽  
Doppler Signal ◽  
Doppler Velocimetry ◽  
Basic Principles ◽  
Doppler Signals ◽  
Sinusoidal Signals ◽  
Ratio Correction

In order to improve the accuracy of signal processing in Laser Doppler Velocimetry, a method based on the association of spectral refinement and correction is presented. Zoom-FFT and ratio correction are adopted to realize this method. Basic principles of zoom-FFT and ratio correction are expounded. FFT and the method are adopted to process sinusoidal signals and simulated laser Doppler signals with different frequencies separately in circumstance of MATLAB 7.0. Comparisons between the results of FFT and the method are carried out. The comparisons show that this method has the capability to improve the accuracy of laser Doppler signal processing significantly and the operation time is acceptable for LDV system.

scholarly journals Gaussian Processes for Nonlinear Signal Processing: An Overview of Recent Advances

2013 ◽  
Vol 30 (4) ◽  
pp. 40-50 ◽  
Author(s):  
Fernando Perez-Cruz ◽  
Steven Van Vaerenbergh ◽  
Juan Jose Murillo-Fuentes ◽  
Miguel Lazaro-Gredilla ◽  
Ignacio Santamaria
Keyword(s):  
Signal Processing ◽  
Gaussian Processes ◽  
Nonlinear Signal Processing ◽  
Recent Advances ◽  
Nonlinear Signal

Laser Doppler signal processing based on trispectral interpolation of Nuttall window

Optik ◽  
2020 ◽  
Vol 205 ◽  
pp. 163364 ◽  
Author(s):  
Da Zhang ◽  
Shengjun Sun ◽  
Hongbo Zhao ◽  
Jiankun Yang
Keyword(s):  
Signal Processing ◽  
Laser Doppler ◽  
Doppler Signal

scholarly journals Recent Advances in Seismocardiography

Vibration ◽  
2019 ◽  
Vol 2 (1) ◽  
pp. 64-86 ◽  
Author(s):  
Amirtahà Taebi ◽  
Brian Solar ◽  
Andrew Bomar ◽  
Richard Sandler ◽  
Hansen Mansy
Keyword(s):  
Signal Processing ◽  
Low Cost ◽  
Cardiac Activity ◽  
Diagnostic Tools ◽  
Noninvasive Evaluation ◽  
Machine Learning Methods ◽  
Recent Advances ◽  
Signal Processing Algorithms ◽  
Potential Clinical Utility

Cardiovascular disease is a major cause of death worldwide. New diagnostic tools are needed to provide early detection and intervention to reduce mortality and increase both the duration and quality of life for patients with heart disease. Seismocardiography (SCG) is a technique for noninvasive evaluation of cardiac activity. However, the complexity of SCG signals introduced challenges in SCG studies. Renewed interest in investigating the utility of SCG accelerated in recent years and benefited from new advances in low-cost lightweight sensors, and signal processing and machine learning methods. Recent studies demonstrated the potential clinical utility of SCG signals for the detection and monitoring of certain cardiovascular conditions. While some studies focused on investigating the genesis of SCG signals and their clinical applications, others focused on developing proper signal processing algorithms for noise reduction, and SCG signal feature extraction and classification. This paper reviews the recent advances in the field of SCG.

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