Overcomplete discrete wavelet transform based respiratory sound discrimination with feature and decision level fusion

[1]  David G. Stork,et al.  Pattern Classification , 1973 .

[2]  Stan Davis,et al.  Comparison of Parametric Representations for Monosyllabic Word Recognition in Continuously Spoken Se , 1980 .

[3]  R. Baughman,et al.  Lung sound analysis for continuous evaluation of airflow obstruction in asthma. , 1985, Chest.

[4]  Lars Kai Hansen,et al.  Neural Network Ensembles , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  H Hermansky,et al.  Perceptual linear predictive (PLP) analysis of speech. , 1990, The Journal of the Acoustical Society of America.

[6]  Geoffrey E. Hinton,et al.  Adaptive Mixtures of Local Experts , 1991, Neural Computation.

[7]  John G. Proakis,et al.  Digital Signal Processing: Principles, Algorithms, and Applications , 1992 .

[8]  Harris Drucker,et al.  Boosting and Other Ensemble Methods , 1994, Neural Computation.

[9]  P. Piirilä,et al.  Crackles: recording, analysis and clinical significance. , 1995, The European respiratory journal.

[10]  Noam Gavriely,et al.  Breath Sounds Methodology , 1995 .

[11]  Lalu Mansinha,et al.  Localization of the complex spectrum: the S transform , 1996, IEEE Trans. Signal Process..

[12]  B Sankur,et al.  Multiresolution biological transient extraction applied to respiratory crackles. , 1996, Computers in biology and medicine.

[13]  Kevin W. Bowyer,et al.  Combination of Multiple Classifiers Using Local Accuracy Estimates , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  H. Pasterkamp,et al.  Respiratory sounds. Advances beyond the stethoscope. , 1997, American journal of respiratory and critical care medicine.

[15]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[16]  A. Dittmar,et al.  The relationship between normal lung sounds, age, and gender. , 2000, American journal of respiratory and critical care medicine.

[17]  C. Chui,et al.  Compactly supported tight frames associated with refinable functions , 2000 .

[18]  James C. Bezdek,et al.  Decision templates for multiple classifier fusion: an experimental comparison , 2001, Pattern Recognit..

[19]  I. Selesnick The Double Density DWT , 2001 .

[20]  Ethem Alpaydin,et al.  Introduction to machine learning , 2004, Adaptive computation and machine learning.

[21]  N. Malmurugan,et al.  Neural classification of lung sounds using wavelet coefficients , 2004, Comput. Biol. Medicine.

[22]  Y.P. Kahya,et al.  A Multi-Channel Device for Respiratory Sound Data Acquisition and Transient Detection , 2005, 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference.

[23]  Hüseyin Polat,et al.  Combining Neural Network and Genetic Algorithm for Prediction of Lung Sounds , 2005, Journal of Medical Systems.

[24]  Richard Baraniuk,et al.  The Dual-tree Complex Wavelet Transform , 2007 .

[25]  R. Polikar,et al.  Ensemble based systems in decision making , 2006, IEEE Circuits and Systems Magazine.

[26]  Chee Kheong Siew,et al.  Extreme learning machine: Theory and applications , 2006, Neurocomputing.

[27]  Philip S. Yu,et al.  Top 10 algorithms in data mining , 2007, Knowledge and Information Systems.

[28]  E. Andrès,et al.  Analysis of Respiratory Sounds: State of the Art , 2008, Clinical medicine. Circulatory, respiratory and pulmonary medicine.

[29]  Stephen R. Marsland,et al.  Machine Learning - An Algorithmic Perspective , 2009, Chapman and Hall / CRC machine learning and pattern recognition series.

[30]  Ivan W. Selesnick,et al.  Frequency-Domain Design of Overcomplete Rational-Dilation Wavelet Transforms , 2009, IEEE Transactions on Signal Processing.

[31]  Ali Abbas,et al.  An Automated Computerized Auscultation and Diagnostic System for Pulmonary Diseases , 2010, Journal of Medical Systems.

[32]  Katsuya Yamauchi,et al.  Classification between normal and abnormal respiratory sounds based on maximum likelihood approach , 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

[33]  Ivan W. Selesnick,et al.  Oscillatory plus transient signal decomposition using overcomplete rational-dilation wavelet transforms , 2009, Optical Engineering + Applications.

[34]  Leontios J. Hadjileontiadis,et al.  Analysis of Wheezes Using Wavelet Higher Order Spectral Features , 2010, IEEE Transactions on Biomedical Engineering.

[35]  P. Mayorga,et al.  Acoustics based assessment of respiratory diseases using GMM classification , 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

[36]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[37]  Nizamettin Aydin,et al.  Pulmonary crackle detection using time-frequency and time-scale analysis , 2013, Digit. Signal Process..

[38]  Rajkumar Palaniappan,et al.  Machine learning in lung sound analysis: a systematic review , 2013 .

[39]  A. Bohadana,et al.  Fundamentals of lung auscultation. , 2014, The New England journal of medicine.

[40]  Yasemin P. Kahya,et al.  Respiratory sound classification using perceptual linear prediction features for healthy - Pathological diagnosis , 2014, 2014 18th National Biomedical Engineering Meeting.

[41]  Kenneth Sundaraj,et al.  A telemedicine tool to detect pulmonary pathology using computerized pulmonary acoustic signal analysis , 2015, Appl. Soft Comput..

[42]  Goutam Saha,et al.  Lung sound classification using cepstral-based statistical features , 2016, Comput. Biol. Medicine.

[43]  J. Geoffrey Chase,et al.  A proof of concept study of acoustic sensing of lung recruitment during mechanical ventilation , 2017, Biomed. Signal Process. Control..