Localization and classification of heart beats in phonocardiography signals —a comprehensive review

[1]  Carlos Abreu Ferreira,et al.  Classifying Heart Sounds Using Images of MFCC and Temporal Features , 2017, EPIA.

[2]  Nima Amjady,et al.  Short Term Wind Power Prediction Based on Improved Kriging Interpolation, Empirical Mode Decomposition, and Closed-Loop Forecasting Engine , 2017 .

[3]  Wenjie Zhang,et al.  Heart sound classification based on scaled spectrogram and tensor decomposition , 2017, Expert Syst. Appl..

[4]  Mohammed Nabih-Ali,et al.  A review of intelligent systems for heart sound signal analysis , 2017, Journal of medical engineering & technology.

[5]  Leontios J. Hadjileontiadis,et al.  Fetal Heart Sounds Detection Using Wavelet Transform and Fractal Dimension , 2017, Front. Bioeng. Biotechnol..

[6]  Anil Kumar Tiwari,et al.  An adaptive thresholding method for the wavelet based denoising of phonocardiogram signal , 2017, Biomed. Signal Process. Control..

[7]  Anurag Agarwal,et al.  DropConnected neural networks trained on time-frequency and inter-beat features for classifying heart sounds , 2017, Physiological measurement.

[8]  El-Sayed A. El-Dahshan,et al.  Heart Diseases Diagnosis Using Intelligent Algorithm Based on PCG Signal Analysis , 2017 .

[9]  Farshad Almasganj,et al.  Imaging of heart acoustic based on the sub-space methods using a microphone array , 2017, Comput. Methods Programs Biomed..

[10]  Anushikha Singh,et al.  Analysis of Heart Sound for Automated Diagnosis of Cardiac Disorders. , 2017, 2017 International Conference and Workshop on Bioinspired Intelligence (IWOBI).

[11]  El-Sayed A. El-Dahshan,et al.  Denoising of Heart Sound Signals Using Discrete Wavelet Transform , 2017, Circuits Syst. Signal Process..

[12]  Yu Tsao,et al.  S1 and S2 Heart Sound Recognition Using Deep Neural Networks , 2017, IEEE Trans. Biomed. Eng..

[13]  Wenjie Zhang,et al.  Heart sound classification based on scaled spectrogram and partial least squares regression , 2017, Biomed. Signal Process. Control..

[14]  Jasmin Kevric,et al.  Wavelet and Teager Energy Operator (TEO) for Heart Sound Processing and Identification , 2017 .

[15]  M. Picheny,et al.  Comparison of Parametric Representation for Monosyllabic Word Recognition in Continuously Spoken Sentences , 2017 .

[16]  Anirban Mukherjee,et al.  Segmentation and detection of first and second heart sounds (Si and S2) using variational mode decomposition , 2016, 2016 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES).

[17]  Richard Mengko,et al.  Empirical Mode Decomposition (EMD) Based Denoising Method for Heart Sound Signal and Its Performance Analysis , 2016 .

[18]  Mohamed Atibi,et al.  Comparison of MFCC and DWT features extractors applied to PCG classification , 2016, 2016 11th International Conference on Intelligent Systems: Theories and Applications (SITA).

[19]  Ali Ghaffari,et al.  Cycle selection and neuro-voting system for classifying heart sound recordings , 2016, 2016 Computing in Cardiology Conference (CinC).

[20]  Bryan R. Conroy,et al.  Ensemble of feature-based and deep learning-based classifiers for detection of abnormal heart sounds , 2016, 2016 Computing in Cardiology Conference (CinC).

[21]  Hong Tang,et al.  Classification of normal/abnormal heart sound recordings based on multi-domain features and back propagation neural network , 2016, 2016 Computing in Cardiology Conference (CinC).

[22]  Márton Áron Goda,et al.  Morphological determination of pathological PCG signals by time and frequency domain analysis , 2016, 2016 Computing in Cardiology Conference (CinC).

[23]  Jhing-Fa Wang,et al.  Detection of the Third Heart Sound Based on Nonlinear Signal Decomposition and Time–Frequency Localization , 2016, IEEE Transactions on Biomedical Engineering.

[24]  Christine William Shaker,et al.  Improving the Recognition of Heart Murmur , 2016 .

[25]  Sherif N. Abbas,et al.  A comparative approach between cepstral features for human authentication using heart sounds , 2016, Signal Image Video Process..

[26]  Lionel Tarassenko,et al.  Logistic Regression-HSMM-Based Heart Sound Segmentation , 2016, IEEE Transactions on Biomedical Engineering.

[27]  Jenna Wiens,et al.  Heart sound classification based on temporal alignment techniques , 2016, 2016 Computing in Cardiology Conference (CinC).

[28]  Puneet Kumar Jain,et al.  An adaptive method for shrinking of wavelet coefficients for phonocardiogram denoising , 2016, 2016 IEEE International Conference on Digital Signal Processing (DSP).

[29]  Jusak Jusak,et al.  Heart murmurs extraction using the complete Ensemble Empirical Mode Decomposition and the Pearson distance metric , 2016, 2016 International Conference on Information & Communication Technology and Systems (ICTS).

[30]  Christian Brandt,et al.  Time-Scale-Based Segmentation for Degraded PCG Signals Using NMF , 2016 .

[31]  Wilhelm Burger,et al.  Digital Image Processing - An Algorithmic Introduction using Java , 2008, Texts in Computer Science.

[32]  Armein Z. R. Langi,et al.  Automatic segmentation and detection of heart sound components S1, S2, S3 and S4 , 2015, 2015 4th International Conference on Instrumentation, Communications, Information Technology, and Biomedical Engineering (ICICI-BME).

[33]  Richard Mengko,et al.  Performance comparison of denoising methods for heart sound signal , 2015, 2015 International Symposium on Intelligent Signal Processing and Communication Systems (ISPACS).

[34]  Shengdong Nie,et al.  [An Improved Empirical Mode Decomposition Algorithm for Phonocardiogram Signal De-noising and Its Application in S1/S2 Extraction]. , 2015, Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi.

[35]  Sourav Saha,et al.  Phonocardiogram signal analysis - practices, trends and challenges: A critical review , 2015, 2015 International Conference and Workshop on Computing and Communication (IEMCON).

[36]  Grzegorz Redlarski,et al.  A System for Heart Sounds Classification , 2014, PloS one.

[37]  K. I. Ramachandran,et al.  A novel heart sound activity detection framework for automated heart sound analysis , 2014, Biomed. Signal Process. Control..

[38]  Miguel A. Becerra,et al.  Heart murmur detection using Ensemble Empirical Mode Decomposition and derivations of the Mel-Frequency Cepstral Coefficients on 4-area phonocardiographic signals , 2014, Computing in Cardiology 2014.

[39]  Leontios J. Hadjileontiadis,et al.  Efficient Heart Sound Segmentation and Extraction Using Ensemble Empirical Mode Decomposition and Kurtosis Features , 2014, IEEE Journal of Biomedical and Health Informatics.

[40]  Dominique Zosso,et al.  Variational Mode Decomposition , 2014, IEEE Transactions on Signal Processing.

[41]  Irini Reljin,et al.  Automatic heart sound detection in pediatric patients without electrocardiogram reference via pseudo-affine Wigner-Ville distribution and Haar wavelet lifting , 2014, Comput. Methods Programs Biomed..

[42]  Ana Castro,et al.  Automatic heart sound segmentation and murmur detection in pediatric phonocardiograms , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[43]  Wei Chen,et al.  An improved empirical mode decomposition-wavelet algorithm for phonocardiogram signal denoising and its application in the first and second heart sound extraction , 2013, 2013 6th International Conference on Biomedical Engineering and Informatics.

[44]  Mandeep Singh,et al.  Heart Sounds Classification using Feature Extraction of Phonocardiography Signal , 2013 .

[45]  Mohammad R. Homaeinezhad,et al.  Noise/spike detection in phonocardiogram signal as a cyclic random process with non-stationary period interval , 2013, Comput. Biol. Medicine.

[46]  Miguel Tavares Coimbra,et al.  Exploring the Stationary Wavelet Transform detail coefficients for detection and identification of the S1 and S2 heart sounds , 2013, Computing in Cardiology 2013.

[47]  Irini Reljin,et al.  Application of wavelet and EMD-based denoising to phonocardiograms , 2013, International Symposium on Signals, Circuits and Systems ISSCS2013.

[48]  Sh-Hussain Salleh,et al.  Multimodal Biometrics Based on Identification and Verification System , 2013 .

[49]  Qinqin Shen,et al.  Heart Sound Biometric System Based on Marginal Spectrum Analysis , 2013, Sensors.

[50]  Braham Barkat,et al.  Segmentation of Pathological Heart Sound Signal Using Empirical Mode Decomposition , 2013 .

[51]  Cheolsoo Park,et al.  Classification of Motor Imagery BCI Using Multivariate Empirical Mode Decomposition , 2013, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[52]  Christian Brandt,et al.  Study of Two Feature Extraction Methods to Distinguish between the First and the Second Heart Sounds , 2012, BIOSIGNALS.

[53]  H. Naseri,et al.  Detection and Boundary Identification of Phonocardiogram Sounds Using an Expert Frequency-Energy Based Metric , 2012, Annals of Biomedical Engineering.

[54]  Germán Castellanos-Domínguez,et al.  Time–frequency based feature selection for discrimination of non-stationary biosignals , 2012, EURASIP J. Adv. Signal Process..

[55]  A Atbi,et al.  Analysis of phonocardiogram signals using wavelet transform , 2012, Journal of medical engineering & technology.

[56]  Yao Lu,et al.  Heart sounds monitor and analysis in noisy environments , 2012, 2012 International Conference on Systems and Informatics (ICSAI2012).

[57]  Yiqi Deng,et al.  A Robust Heart Sound Segmentation and Classification Algorithm using Wavelet Decomposition and Spectrogram , 2012 .

[58]  Rachid Harba,et al.  On the separation of heart sound components using a translated empirical mode decomposition , 2011, ISABEL '11.

[59]  Braham Barkat,et al.  Segmentation and identification of some pathological phonocardiogram signals using time-frequency analysis , 2011 .

[60]  PP Yupapin,et al.  Heart detection and diagnosis based on ECG and EPCG relationships , 2011, Medical devices.

[61]  Eduardo Gil,et al.  Selection of Nonstationary Dynamic Features for Obstructive Sleep Apnoea Detection in Children , 2011, EURASIP J. Adv. Signal Process..

[62]  Goutam Saha,et al.  Detection of cardiac abnormality from PCG signal using LMS based least square SVM classifier , 2010, Expert Syst. Appl..

[63]  Qiao Li,et al.  Improved methods for detecting main components of heart sounds , 2010, 2010 Sixth International Conference on Natural Computation.

[64]  Elmar Wolfgang Lang,et al.  Empirical Mode Decomposition - an introduction , 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

[65]  Thierry Dutoit,et al.  A novel method for pediatric heart sound segmentation without using the ECG , 2010, Comput. Methods Programs Biomed..

[66]  J J Struijk,et al.  Segmentation of heart sound recordings by a duration-dependent hidden Markov model , 2010, Physiological measurement.

[67]  Shamim Nemati,et al.  Data Fusion for Improved Respiration Rate Estimation , 2010, EURASIP J. Adv. Signal Process..

[68]  Irena Orovic,et al.  Time-Frequency-Based Speech Regions Characterization and Eigenvalue Decomposition Applied to Speech Watermarking , 2010, EURASIP J. Adv. Signal Process..

[69]  D. P. Mandic,et al.  Multivariate empirical mode decomposition , 2010, Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[70]  Euripidis Loukis,et al.  Support Vectors Machine-based identification of heart valve diseases using heart sounds , 2009, Comput. Methods Programs Biomed..

[71]  Sepideh Babaei,et al.  Heart sound reproduction based on neural network classification of cardiac valve disorders using wavelet transforms of PCG signals , 2009, Comput. Biol. Medicine.

[72]  Ping Wang,et al.  A computer-aided MFCC-based HMM system for automatic auscultation , 2008, Comput. Biol. Medicine.

[73]  S. M. Debbal,et al.  Computerized heart sounds analysis , 2008, Comput. Biol. Medicine.

[74]  Dimitrios Hatzinakos,et al.  Biometric Methods for Secure Communications in Body Sensor Networks: Resource-Efficient Key Management and Signal-Level Data Scrambling , 2008, EURASIP J. Adv. Signal Process..

[75]  Ronald W. Schafer,et al.  Introduction to Digital Speech Processing , 2007, Found. Trends Signal Process..

[76]  Toshihisa Tanaka,et al.  Complex Empirical Mode Decomposition , 2007, IEEE Signal Processing Letters.

[77]  Shoab A. Khan,et al.  Heart Sound Signal Modeling and Segmentation based on Improved Shannon Energy Envelogram using Adaptive Windows , 2007 .

[78]  Pablo Laguna,et al.  Principal Component Analysis in ECG Signal Processing , 2007, EURASIP J. Adv. Signal Process..

[79]  Shankar M. Krishnan,et al.  Neural network classification of homomorphic segmented heart sounds , 2007, Appl. Soft Comput..

[80]  Firdaus E. Udwadia,et al.  Use of the fast fourier transform for frequency analysis of the first heart sound in normal man , 2006, Medical and biological engineering.

[81]  S M Debbal,et al.  Time-frequency analysis of the second cardiac sound in phonocardiogram signals. , 2005, Medical physics.

[82]  C.N. Gupta,et al.  Segmentation and classification of heart sounds , 2005, Canadian Conference on Electrical and Computer Engineering, 2005..

[83]  M. Shen,et al.  Instantaneous Frequency Estimate of Nonstationary Phonocardiograph Signals Using Hilbert Spectrum , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[84]  Zhao Zhidong.  Noninvasive Diagnosis of Coronary Artery Disease Based on Instantaneous Frequency of Diastolic Murmurs and SVM , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[85]  S. Chien,et al.  National Institute of Biomedical Imaging and Bioengineering , 2020, Definitions.

[86]  Lisha Sun,et al.  A novel method of time-frequency representation and its application to biomedical signal processing , 2004, Proceedings 7th International Conference on Signal Processing, 2004. Proceedings. ICSP '04. 2004..

[87]  G.B. Moody,et al.  The impact of the MIT-BIH Arrhythmia Database , 2001, IEEE Engineering in Medicine and Biology Magazine.

[88]  I. Hartimo,et al.  A heart sound feature extraction algorithm based on wavelet decomposition and reconstruction , 1998, Proceedings of the 20th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. Vol.20 Biomedical Engineering Towards the Year 2000 and Beyond (Cat. No.98CH36286).

[89]  H. Liang,et al.  A feature extraction algorithm based on wavelet packet decomposition for heart sound signals , 1998, Proceedings of the IEEE-SP International Symposium on Time-Frequency and Time-Scale Analysis (Cat. No.98TH8380).

[90]  L. Senhadji,et al.  Time-frequency scaling transformation of the phonocardiogram based of the matching pursuit method , 1998, IEEE Transactions on Biomedical Engineering.

[91]  Richard G. Baraniuk,et al.  Pseudo affine Wigner distributions: definition and kernel formulation , 1998, IEEE Trans. Signal Process..

[92]  N. Huang,et al.  The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis , 1998, Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.

[93]  I. Hartimo,et al.  Heart sound segmentation algorithm based on heart sound envelogram , 1997, Computers in Cardiology 1997.

[94]  L. Durand,et al.  Digital signal processing of the phonocardiogram: review of the most recent advancements. , 1995, Critical reviews in biomedical engineering.

[95]  Y. S. Shin,et al.  Pseudo Wigner–Ville Time-Frequency Distribution and Its Application to Machinery Condition Monitoring , 1993 .

[96]  Alan F. Murray,et al.  International Joint Conference on Neural Networks , 1993 .

[97]  R M Rangayyan,et al.  Phonocardiogram signal analysis: a review. , 1987, Critical reviews in biomedical engineering.

[98]  Robert C. Wolpert,et al.  A Review of the , 1985 .

[99]  L. Stodieck,et al.  Relationships between the electrocardiogram and phonocardiogram: potential for improved heart monitoring. , 1984, ISA transactions.