Boualem Boashash

Boualem Boashash
Qatar University · Department of Electrical Engineering

About

526
Publications
101,506
Reads
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15,898
Citations
Introduction
Boualem Boashash was an early pioneer of the field of Time-Frequency Signal Processing and he is currently working on further development of time-frequency theory and medical applications covering mental health and neurosciences with focus on newborn EEG analysis as well as ECG, HRV and fetal movements for improving health outcomes. He developed the first software package for time-frequency signal analysis and processing-TFSAP (time-frequency.net) and his work has been cited over 10,000 times.
Skills and Expertise

Publications

Publications (526)
Article
Background and Objective : In newborns, it is often difficult to accurately differentiate between seizure and non-seizure based solely on clinical manifestations. This highlights the importance of electroencephalogram (EEG) in the recognition and management of neonatal seizures. This paper proposes an effective algorithm for the detection of neonat...
Article
Background and Objective Significant health care resources are allocated to monitoring high risk pregnancies to minimize growth compromise, reduce morbidity and prevent stillbirth. Fetal movement has been recognized as an important indicator of fetal health. Studies have shown that 25% of pregnancies with decreased fetal movement in the third trime...
Article
Full-text available
This paper proposes a new performance evaluation process for time-frequency distributions (TFD) by designing a reference optimal TFD and novel accuracy and resolution measures. The motivation comes from the need for a TFD performance evaluation method that is objective, capable of quantifying the TFD accuracy and resolution, can determine the perfo...
Article
Phase synchrony assessment across non-stationary multivariate signals is a useful way to characterize the dynamical behavior of their underlying systems. Traditionally, phase synchrony of a multivariate signal has been quantified by first assessing all pair-wise phase relationships between different channels and then, averaging their phase coupling...
Article
This paper aims at providing a more accurate description of the ambiguity domain characteristics of a piecewise multicomponent non-stationary signals with focus on piece-wise linear frequency modulated (LFM) (PW-LFM) signal and a mixed LFM and hyperbolic FM (HFM). The main motivation comes from the observed PW-LFM nature of several real life signal...
Article
This paper addresses the problem of noise reduction in non-stationary signals. The paper first describes a human physiology based time–frequency (TF) representation (TFHP) using Mel filterbanks. It is then used to improve a noise reduction algorithm that does not require any a priori information about the signal of interest and the noise. This algo...
Article
The Multisensor Time-FrequencySignal Processing (MTFSP) Matlab package is an analysis tool for multichannel non-stationary signals collected from an array of sensors. By combining array signal processing for non-stationary signals and multichannel high resolution time-frequency methods, MTFSP enables applications such as cross-channel causality rel...
Article
This paper presents high-resolution multisensor time-frequency distributions (MTFDs) and their applications to the analysis of multichannel non-stationary signals. The approach combines high-resolution time-frequency analysis and array signal processing methods. The improved performance of MTFDs is demonstrated using several applications including...
Article
Full-text available
This article describes the source code used in the TFSAP toolbox (Boashash, 2016). It is extended with additional functions to allow reproducible research as presented in Boashash and Ouelha (in press). These codes can be used for analysis and classification to (1) generate Time-Frequencydistributions (TFDs) or Time-Scale distributions (TSDs), (2)...
Article
The Locally Optimized Spectrogram (LOS) defines a novel method for obtaining a high-resolution time-frequency representation based on the short-time fractional Fourier transform (STFrFT). The key novelty of the LOS is that it automatically determines the locally optimal window parameters and fractional order (angle) for all signal components, leadi...
Article
This paper deals with the problem of extracting information from non-stationary signals in the form of features that can be used for effective decision-making in both data analysis and machine learning for automatic classification systems. Suitable time–frequency (TF) and time–scale (TS) representations of such signals are reviewed for these purpos...
Article
This paper uses the surrogate data method to investigate the presence of nonlinearity in neonatal electroencephalogram (EEG) burst suppression (B/S) patterns in order to rationalize the use of nonlinear methods for automated detection of such patterns. To generate surrogate data, the statically transformed autoregressive process (STAP) algorithm is...
Article
This paper addresses the problem of direction of arrival (DOA) estimation and blind source separation (BSS) for non-stationary signals in the underdetermined case. These two problems are strongly related to the mixing matrix estimation problem. To deal with the non-stationary characteristics of signals,} this study uses high-resolution quadratic ti...
Research
Full-text available
NPRP 4 - 1303 - 2 – 517- Progress Report Number 6- Automated Neonatal EEG quality assessment and improvement using artefact filtering and signal segmentation
Research
Full-text available
NPRP 4 - 1303 - 2 – 517- Progress Report Number 5- Automated Neonatal EEG quality assessment and improvement using artefact filtering and signal segmentation
Research
Full-text available
NPRP 6 - 885 - 2 – 364 - Progress Report Number 5- Localization of EEG Abnormalities for Improving Brain Monitoring of Newborn Babies at Risk of Brain Injury using a multichannel time-frequency signal processing
Research
Full-text available
NPRP 6 - 885 - 2 – 364 Progress Report 4- Localization of EEG Abnormalities for Improving Brain Monitoring of Newborn Babies at Risk of Brain Injury using a multichannel time-frequency signal processing approach.
Article
This study demonstrates that a time-frequency (TF) image pattern recognition approach offers significant advantages over standard signal classification methods that use t-domain only or f-domain only features. Two approaches are considered and compared. The paper describes the significance of the standard TF approach for non-stationary signals; TF...
Article
This paper presents an improved signal reconstruction method based on a new inverse short-time Fourier transform (ISTFT) estimator. The main challenge addressed in this study is to design a more computationally efficient algorithm called exact formal approach (EFA) which overcomes the drawbacks of the popular overlap and add (OLA) and least squares...
Article
This paper presents a new advanced methodology for designing high resolution Time-Frequency Distributions (TFDs) of multicomponent non-stationary signals that can be approximated using Piece-Wise Linear Frequency Modulated (PW-LFM) signals. Most previous kernel design methods assumed that signals auto-terms are mostly centered around the origin of...
Article
Contrast enhancement, in a broad sense, is a process whereby some characteristics of an image signal are highlighted. Techniques for image contrast enhancement improve the visibility of image details but may generate some undesirable artifacts such as noise amplification, ringing and overshooting. As a consequence, developing distortion-free method...
Article
This paper presents a novel framework for a fully automatic optimization of Quadratic Time-frequency Distributions (QTFDs). This ‘black box’ approach automatically adjusts the QTFD kernel parameters by using a hybrid genetic algorithm (HGA). This results in an optimal use of QTFDs suitable for non-specialist users without requiring any additional i...
Conference Paper
Full-text available
Falls are a major cause of fatal and nonfatal injuries in people aged 65 years and older. Radar has the potential to become one of the leading technologies for fall detection, thereby enabling the elderly to live independently. Existing techniques for fall detection using radar are based on manual feature extraction and require significant paramete...
Conference Paper
Full-text available
Falls are a major cause of accidents in elderly people. Even simple falls can lead to severe injuries, and sometimes result in death. Doppler fall detection has drawn much attention in recent years. Micro-Doppler signatures play an important role for the Doppler-based radar systems. Numerous studies have demonstrated the offerings of micro-Doppler...
Article
This paper presents a locally adaptive time-frequency (t,f) method for estimating the instantaneous frequency (IF) of multi-component signals. A high-resolution adaptive directional time-frequency distribution (ADTFD) is defined by locally adapting the direction of its smoothing kernel at each (t,f) point based on the direction of the energy distri...
Conference Paper
Full-text available
1) The method The injuries suffered by newborns during birth are a major health issue. To improve the health outcomes of sick newborns using EEG measurements, a number of recent studies focused on the use of high-resolution Time-Frequency Distributions to extract critical information from the collected signals [1]. Several algorithms have been prop...
Chapter
This chapter presents time-frequency (t,f) methods suitable for multichannel signal processing using multisensor and time-space processing methods. The topic is covered in seven sections with relevant cross-referencing. A brief tutorial review of the topic of multichannel/multisensor (t,f) signal processing describes the extension of (t,f) methods...
Book
Time-Frequency Signal Analysis and Processing (TFSAP) is a collection of theory, techniques and algorithms used for the analysis and processing of non-stationary signals, as found in a wide range of applications including telecommunications, radar, and biomedical engineering. This book gives the university researcher and R&D engineer insights into...
Conference Paper
Electroencephalography (EEG) is the electrical activity of the brain recorded on the scalp. The analysis of EEG is an important tool for detecting different brain dysfunctions in newborns. A normal EEG is highly predictive of a normal outcome, whereas various abnormal EEG features have been consistently associated with neurological abnormalities or...
Article
Full-text available
In this study, the authors consider the problem of human gait recognition in the presence of a walking cane using radars. Quadratic time-frequency distributions are used to provide the local signal behaviour over frequency and to detail the changes in the Doppler and micro-Doppler signatures over time. New features that capture the intrinsic differ...
Conference Paper
Full-text available
In this paper, we analyze the micro-Doppler signatures of elderly gait patterns in the presence of walking aids using radars. The signatures are based on real data experiments conducted in a laboratory environment using human subjects walking with a walking cane and a walker. Short-time Fourier transform is used to provide the local signal behavior...
Conference Paper
Full-text available
In this paper, we examine the role of high-resolution time-frequency distributions (TFDs) of radar micro-Doppler signatures for fall detection. The work supports the recent and rising interest in using emerging radar technology for elderly care and assisted living. Spectrograms have been the de facto joint-variable signal representation, depicting...
Article
Hypoxic ischaemic encephalopathy is a significant cause of mortality and morbidity in the term infant. Electroencephalography (EEG) is a useful tool in the assessment of newborns with HIE. This systematic review of published literature identifies those background features of EEG in term neonates with HIE that best predict neurodevelopmental outcome...
Article
Full-text available
In newborn EEG, the presence of burst suppression carries with it a high probability of poor neurodevelopmental outcome. This paper presents a novel method to detect neonatal bust suppression from multichannel EEG using a time-frequency (T-F) based approach. In this approach, features are extracted from T-F representations of EEG signals obtained u...
Article
Full-text available
This paper presents a time-frequency approach for fetal movement monitoring which is based on classification of accelerometry signals collected from pregnant women's abdomen. Features extracted from time-frequency distribution of these signals were supplied into statistical analysis to generate feature-measure mixtures. Four various classes subject...
Article
This paper presents a tutorial review of recent advances in the field of time–frequency signal processing with focus on exploiting image feature information using pattern recognition techniques for detection and classification applications. This is achieved by (1) revisiting and streamlining the design of high-resolution quadratic time frequency di...
Article
This paper presents a novel design of a time–frequency (t-f) matched filter as a solution to the problem of detecting a non–stationary signal in the presence of additive noise, for application to the detection of newborn seizure using multichannel EEG signals. The solution reduces to two possible t-f approaches that use a general formulation of t-f...
Article
Full-text available
This study proposes an adaptive method for components instantaneous frequency (IF) estimation of noisy non-stationary multicomponent signals, combined with the components time-support estimation method based on the short-time Rényi entropy (STRE). Components localisation and separation are done using a double-direction component tracking and extrac...
Article
This paper describes a multi-sensor fetal movement (FetMov) detection system based on a time–frequency (TF) signal processing approach. Fetal motor activity is clinically useful as a core aspect of fetal screening for well-being to reduce the current high incidence of fetal deaths in the world. FetMov are present in early gestation but become more...
Data
This package implements a time-frequency phase synchrony assessment approach for multivariate non-stationary signals (such as multichannel EEG signals) represented in [1]. The package uses the following external toolboxes/scripts: 1. Time-Frequency Signal Analysis (TFSA) toolbox, available at: http://espace.library.uq.edu.au/view/uq:211321, 2. Ec...
Conference Paper
The keynote talks discuss the following: Web 2.0; human centered information systems; query processing; time-frequency methods; and data processing.
Article
Full-text available
Perinatal hypoxia is a cause of cerebral injury in foetuses and neonates. Detection of foetal hypoxia during labour based on the pattern recognition of heart rate signals suffers from high observer variability and low specificity. We describe a new automated hypoxia detection method using time-frequency analysis of heart rate variability (HRV) sign...
Article
Full-text available
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. Man...
Conference Paper
Full-text available
This invited paper aims at reviewing the current status of Engineering education in the GCC countries and proposing a few guidelines for reform and improvement. The principles applied to this process have been developed by the author over the years and they arose from experience in several leading universities in France and Australia, as well as mo...
Conference Paper
Full-text available
This paper presents a time-frequency approach to detect perinatal hypoxia by characterizing the nonstationary nature of heart rate variability (HRV) signals. Quadratic time-frequency distributions (TFDs) are used to represent the HRV signals. Six features based on the instantaneous frequency (IF) of the lower frequency components of HRV signals are...
Article
Neonatal EEG seizures often manifest as nonstationary and multicomponent signals, necessitating analysis in the time-frequency (TF) domain. This paper presents a novel neonatal seizure detector based on effective implementation of the TF matched filter. In the detection process, the TF signatures of EEG seizure are extracted to construct the TF tem...
Conference Paper
Full-text available
Separation of different signal components, produced by one or more sources, is a problem encountered in many signal processing applications. This paper proposes a fully automatic undetermined blind source separation method, based on a peak detection and extraction technique from a signal time-frequency distribution (TFD). Information on the local n...
Conference Paper
Full-text available
This paper describes the advancements, updates and improvements made in the new Time Frequency Signal Analysis TFSAP toolbox as compared with the previous TFSA toolbox version. The updates and improvements done in TFSA toolbox are in-line with the latest research done in recent few years in the field of time-frequency based signal analysis. TFSA To...
Article
This paper proposes an approach for robust estimation of highly-varying nonlinear instantaneous frequency (IF) in monocomponent nonstationary signals. The proposed method is based on a lower order complex-time distribution (CTD), derived by using the idea of complex-time differentiation of the instantaneous phase. Unlike other existing TFDs in the...
Article
Full-text available
This paper presents a novel nonparametric Bayesian estimator for signal and image denoising in the wavelet domain. This approach uses a prior model of the wavelet coefficients designed to capture the sparseness of the wavelet expansion. A new family of Bessel K Form (BKF) densities are designed to fit the observed histograms, so as to provide a pro...
Article
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This letter presents a novel algorithm to compute the instantaneous frequency (IF) of a multicomponent nonstationary signal using a combination of fractional spectrograms (FS). A high resolution time frequency distribution (TFD) is defined by combining FS computed using windows of varying lengths and chirp rates. The IF of individual signal compone...
Article
Full-text available
Algorithms for computing time–frequency distributions (TFDs) limit computation time by reducing numerical operations. But these fast algorithms do not reduce the memory load. This article presents four TFD algorithms to minimise both the computation and memory loads. Each algorithm is optimised for a specific kernel category. Three algorithms reduc...
Article
The analysis of heart rate variability (HRV) provides a non-invasive tool for assessing the autonomic regulation of cardiovascular system. Quadratic time–frequency distributions (TFDs) have been used to account for the non-stationarity of HRV signals, but their performance is affected by cross-terms. This study presents an improved type of quadrati...
Article
Full-text available
This paper considers the problem of Phase synchrony and coherence analysis using a modified version of the S Transform, referred to here as the MST. This is a novel and important time-frequency approach to study the phase coupling between two or more different spatially recorded entities with non-stationary characteristics. The basic method include...
Article
Full-text available
This article proposes a new method for newborn seizure detection that uses information extracted from both multi-channel electroencephalogram (EEG) and a single channel electrocardiogram (ECG). The aim of the study is to assess whether additional information extracted from ECG can improve the performance of seizure detectors based solely on EEG. Tw...