Time-Frequency Processing of Nonstationary Signals: Advanced TFD Design to Aid Diagnosis with Highlights from Medical Applications

This article presents a methodical approach for improving quadratic time-frequency distribution (QTFD) methods by designing adapted time-frequency (T-F) kernels for diagnosis applications with illustrations on three selected medical applications using the electroencephalogram (EEG), heart rate variability (HRV), and pathological speech signals. Manual and visual inspection of such nonstationary multicomponent signals is laborious especially for long recordings, requiring skilled interpreters with possible subjective judgments and errors. Automated assessment is therefore preferred for objective diagnosis by using T-F distributions (TFDs) to extract more information. This requires designing advanced high-resolution TFDs for automating classification and interpretation. As QTFD methods are general and their coverage is very broad, this article concentrates on methodologies using only a few selected medical problems studied by the authors.

[1]  Boualem Boashash,et al.  Fast and memory-efficient algorithms for computing quadratic time–frequency distributions , 2013 .

[2]  Miroslav Zivanovic,et al.  Nonstationary Harmonic Modeling for ECG Removal in Surface EMG Signals , 2012, IEEE Transactions on Biomedical Engineering.

[3]  Po-Lei Lee,et al.  Reorganization of functional connectivity during the motor task using EEG time–frequency cross mutual information analysis , 2011, Clinical Neurophysiology.

[4]  Dimitrios I. Fotiadis,et al.  Epileptic Seizure Detection in EEGs Using Time–Frequency Analysis , 2009, IEEE Transactions on Information Technology in Biomedicine.

[5]  Pablo Laguna,et al.  Characterization of Dynamic Interactions Between Cardiovascular Signals by Time-Frequency Coherence , 2012, IEEE Transactions on Biomedical Engineering.

[6]  R. E. Greenblatt,et al.  Connectivity measures applied to human brain electrophysiological data , 2012, Journal of Neuroscience Methods.

[7]  Boualem Boashash,et al.  Kernel design for time-frequency signal analysis using the Radon transform , 1993, IEEE Trans. Signal Process..

[8]  Ian Vince McLoughlin,et al.  Reconstruction of Normal Sounding Speech for Laryngectomy Patients Through a Modified CELP Codec , 2010, IEEE Transactions on Biomedical Engineering.

[9]  Sridhar Krishnan,et al.  A Joint Time-Frequency and Matrix Decomposition Feature Extraction Methodology for Pathological Voice Classification , 2009, EURASIP J. Adv. Signal Process..

[10]  Mj Martin Bastiaans.  Time-frequency signal analysis , 2008 .

[11]  Boualem Boashash,et al.  Detection of perinatal hypoxia using time-frequency analysis of heart rate variability signals , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

[12]  Juan Ignacio Godino-Llorente,et al.  Selection of Dynamic Features Based on Time–Frequency Representations for Heart Murmur Detection from Phonocardiographic Signals , 2009, Annals of Biomedical Engineering.

[13]  Boualem Boashash,et al.  A time-frequency based approach for generalized phase synchrony assessment in nonstationary multivariate signals , 2013, Digit. Signal Process..

[14]  John M. O'Toole,et al.  Time-Frequency Detection of Slowly Varying Periodic Signals with Harmonics: Methods and Performance Evaluation , 2011, EURASIP J. Adv. Signal Process..

[15]  T. Thayaparan.  Time-Frequency Signal Analysis , 2014 .

[16]  John M. O'Toole,et al.  Estimating the time-varying periodicity of epileptiform discharges in the electroencephalogram , 2012, 2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA).

[17]  Boualem Boashash,et al.  Resolution measure criteria for the objective assessment of the performance of quadratic time-frequency distributions , 2003, IEEE Trans. Signal Process..

[18]  Ali Yener Mutlu,et al.  A Time-Frequency-Based Approach to Phase and Phase Synchrony Estimation , 2011, IEEE Transactions on Signal Processing.

[19]  Boualem Boashash,et al.  Time-Frequency Signal Analysis and Processing: A Comprehensive Reference , 2015 .

[20]  Jin Jiang,et al.  Time-frequency feature representation using energy concentration: An overview of recent advances , 2009, Digit. Signal Process..

[21]  Leontios J. Hadjileontiadis,et al.  Adaptive Emotional Information Retrieval From EEG Signals in the Time-Frequency Domain , 2012, IEEE Transactions on Signal Processing.

[22]  Carlos Guerrero-Mosquera,et al.  New feature extraction approach for epileptic EEG signal detection using time-frequency distributions , 2010, Medical & Biological Engineering & Computing.

[23]  Luca T Mainardi,et al.  On the quantification of heart rate variability spectral parameters using time–frequency and time-varying methods , 2009, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[24]  Boualem Boashash,et al.  Design of a high-resolution separable-kernel quadratic TFD for improving newborn health outcomes using fetal movement detection , 2012, 2012 11th International Conference on Information Science, Signal Processing and their Applications (ISSPA).

[25]  Douglas L. Jones,et al.  An adaptive optimal-kernel time-frequency representation , 1995, IEEE Trans. Signal Process..

[26]  Boualem Boashash,et al.  Time-Frequency Distributions Based on Compact Support Kernels: Properties and Performance Evaluation , 2012, IEEE Transactions on Signal Processing.

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

[28]  Boualem Boashash,et al.  A methodology for time-frequency image processing applied to the classification of non-stationary multichannel signals using instantaneous frequency descriptors with application to newborn EEG signals , 2012, EURASIP J. Adv. Signal Process..

[29]  Touradj Ebrahimi,et al.  Joint Time-Frequency-Space Classification of EEG in a Brain-Computer Interface Application , 2003, EURASIP J. Adv. Signal Process..