Design Methodology of a New Wavelet Basis Function for Fetal Phonocardiographic Signals

Chourasia, Vijay S.; Tiwari, Anil Kumar

doi:10.1155/2013/505840

Cited by 28 publications

(30 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The duality problem is observed, which is solved through the Lagrange's theorem [5] in (10). The Lagrange's theorem is employed to limit the number of used features.…”

Section: Soft Margin Support Vector Machine (Ssvm)mentioning

confidence: 99%

“…The optimized values for (8) are obtained in (9). θ is the utilized Lagrange's coefficient for high dimension feature space for the i th trial (10).…”

Section: Soft Margin Support Vector Machine (Ssvm)mentioning

confidence: 99%

“…Since now, many patterns are generated as a mother wavelet such as Daubechies [14] and Mexican Hat [34]. One method to improve the DWT functionality is to optimize the mother wavelets [10]. For instance, to diagnose fetal phonocardiography waves for higher accuracy, beside a mother wavelet a daughter wavelet is designed to add a property of finding the wavelet location to the mother wavelet [10].…”

mentioning

confidence: 99%

“…One method to improve the DWT functionality is to optimize the mother wavelets [10]. For instance, to diagnose fetal phonocardiography waves for higher accuracy, beside a mother wavelet a daughter wavelet is designed to add a property of finding the wavelet location to the mother wavelet [10]. In another study, the evolutionary algorithm is exploited to generate a mother wavelet pattern based on the predefined mother wavelet such as genetic algorithm for finding epilepsy seizure patterns [17].…”

mentioning

confidence: 99%

See 3 more Smart Citations

Combination of discrete wavelet packet transform with detrended fluctuation analysis using customized mother wavelet with the aim of an imagery-motor control interface for an exoskeleton

Hekmatmanesh

Nasrabadi

et al. 2019

Multimed Tools Appl

View full text Add to dashboard Cite

One critical issue in brain computer interface (BCI) studies is to extract imaginary movement patterns from electroencephalograph (EEG). In this study, two different techniques -detrended fluctuation analysis (DFA) and discrete wavelet packet transform-are combined (DWPT-DFA) for feature extraction. Both approaches are known as self-similarity quantifier techniques. In wavelet technique, mother wavelets play an important role. Herein, A customized mother wavelet utilizing event related desynchronization (ERD) potential patterns are extracted and updated automatically for individual subjects. Also, three predefined mother wavelets are used, and the results are compared with the customized mother wavelet. The predefined mother wavelets are db4, db8 and coiflet 4. The soft margin support vector machine with the generalized radial basis function (SSVM-GRBF) is employed to classify the DWPT-DFA features. For the efficiency of the method, nine subjects have participated to record EEG based on the imaginary hand movements. The ERDs and features are extracted from FC1 and CP6 channels. Results show that the combination of the DWPT and DFA with the personalize ERD mother wavelet gives the best accuracy of 85.33% with p < 0.001. Based on the results, we conclude that the DWPT-DFA method using the ERD mother wavelets improves significantly the efficiency of the SSVM-GRBF classifier.Keywords Brain computer interface (BCI) · Detrended fluctuation analysis (DFA) · Discrete wavelet packet transform (DWPT) · Event related desynchronization (ERD) · Soft margin support vector machine with generalized radial basis function (SSVM-GRBF)

show abstract

“…The duality problem is observed, which is solved through the Lagrange's theorem [5] in (10). The Lagrange's theorem is employed to limit the number of used features.…”

Section: Soft Margin Support Vector Machine (Ssvm)mentioning

confidence: 99%

“…The optimized values for (8) are obtained in (9). θ is the utilized Lagrange's coefficient for high dimension feature space for the i th trial (10).…”

Section: Soft Margin Support Vector Machine (Ssvm)mentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Combination of discrete wavelet packet transform with detrended fluctuation analysis using customized mother wavelet with the aim of an imagery-motor control interface for an exoskeleton

Hekmatmanesh

Nasrabadi

et al. 2019

Multimed Tools Appl

View full text Add to dashboard Cite

show abstract

“…As to fetal movement tracing, a band-pass filter is used to reject the background noises further. Then a de-noising algorithm described in [16] is used to de-noise the fetal movement signals.…”

Section: Acquisition and Preprocessingmentioning

confidence: 99%

Fetal heart rate baseline estimation with analysis of fetal movement signal

Wei

2014

Bio-Medical Materials and Engineering

View full text Add to dashboard Cite

In order to assign appropriate baseline estimation algorithms to different fetal heart rate tracing, a method to evaluate the fetal heart rate (FHR) baseline combining with the fetal movement information was proposed. Fetal actography and tocography were used to extract the fetal movement information. The results showed that the combined method, where the fetal movement detection result was the union of results of actography and tocography, achieved a better performance with the highest sensitivity and an acceptable positive predictive value (PPV). Furthermore, the mean absolute errors (MAEs) of basal FHR values between the two algorithms and the expert were calculated with respect to the duration coefficient of fetal movement. The results showed that the algorithm using empirical mode decomposition (EMD) and Kohonen neural network (KNN) had lower MAEs than a traditional linear baseline estimation algorithm as the duration coefficient increased. However, if the duration coefficient is below 0.2, the errors may be tolerant for the FHR baseline estimation by a linear baseline estimation algorithm, which indicates that different algorithms may be selected for FHR baseline estimation based on different duration coefficients of fetal movement.

show abstract

Concept Design and Dynamic Modelling of a Fibre-Based Continuum Robot for Early Cancer Detection Using DT-TMM

Bærenholdt

Wang

Zhang

2018

Mechanisms and Machine Science

View full text Add to dashboard Cite

Medical and service robotic are getting a growing market and an increasing interest from research and applications viewpoints. The aging of population and shortage of resources is increasing the demand of novel robotic solutions and devices, as for example in assistance in medical treatments and rehabilitation. Human-Robot interactions and performance evaluations are attracting significant interest to validate the effectiveness and acceptability of the proposed solutions. This proceedings book systematizes the contributions in the approached field that have been accepted for presentation at MESROB 2018, the 6-th International Workshop on New Trends in Medical and Service Robotic. MESROB 2018 has been held at the School of Engineering of the University of Cassino and South Latium in Cassino, Italy. This conference event continues a successful series of workshops that have been started

show abstract

Design Methodology of a New Wavelet Basis Function for Fetal Phonocardiographic Signals

Cited by 28 publications

References 35 publications

Combination of discrete wavelet packet transform with detrended fluctuation analysis using customized mother wavelet with the aim of an imagery-motor control interface for an exoskeleton

Combination of discrete wavelet packet transform with detrended fluctuation analysis using customized mother wavelet with the aim of an imagery-motor control interface for an exoskeleton

Fetal heart rate baseline estimation with analysis of fetal movement signal

Concept Design and Dynamic Modelling of a Fibre-Based Continuum Robot for Early Cancer Detection Using DT-TMM

Contact Info

Product

Resources

About