Browsing by Author "n 90698394"
Now showing items 21-40 of 121
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Calibration of time features and frequency features in the time-frequency domain for improved detection and classification of seizure in newborn EEG signals
Bahnasy Y.; Saad N.; Boubchir L.; Boashash B. ( IEEE Computer Society , 2012 , Conference Paper)This paper presents new time-frequency features for seizure detection in newborn EEG signals. These features are obtained by calibrating relevant time features and frequency features in the joint time-frequency domain. The ... -
Classification of fetal movement accelerometry through time-frequency features
Layeghy, Siamak; Azemi, Ghasem; Colditz, Paul; Boashash, Boualem ( IEEE , 2014 , Conference Paper)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 ... -
A comparison of quadratic TFDs for entropy based detection of components time supports in multicomponent nonstationary signal mixtures
Saulig, N.; Sucic, V.; Boashash, B.; Sersic, D. ( IEEE , 2013 , Conference Paper)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, ... -
Design and implementation of a multi-sensor newborn EEG seizure and background model with inter-channel field characterization
Al-Sa'd, Mohammad F.; Boashash, B. ( Elsevier Inc. , 2019 , Article)This paper presents a novel multi-sensor non-stationary EEG model; it is obtained by combining state of the art mono-sensor newborn EEG simulators, a multilayer newborn head model comprised of four homogeneous concentric ... -
Design of a high-resolution separable-kernel quadratic TFD for improving newborn health outcomes using fetal movement detection
Boashash B.; Ben-Jabeur T. (2012 , Conference Paper)Prior to birth, fetus health can be monitored by the variety and scale of its movements. In addition, at birth, EEG signals are recorded from at-risk newborns. Studies have shown that both fetal movements and newborn EEGs ... -
Design of a Simulator for Neonatal Multichannel EEG: Application to Time-Frequency Approaches for Automatic Artifact Removal and Seizure Detection
Al-Sa'd, Mohamed Fathi (2016 , Master Thesis)The electroencephalogram (EEG) is used to noninvasively monitor brain activities; it is the most utilized tool to detect abnormalities such as seizures. In recent studies, detection of neonatal EEG seizures has been ... -
Design of a Time-Frequency Algorithm for Automatic Eeg Artifact Removal
Boashash, Boualem; Ouelha, Samir; Maqsood, Sadiq Ali ( Hamad bin Khalifa University Press (HBKU Press) , 2016 , Conference Paper)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 ... -
Designing high-resolution time–frequency and time–scale distributions for the analysis and classification of non-stationary signals: a tutorial review with a comparison of features performance
Boashash B.; Ouelha S. ( Elsevier Inc. , 2018 , 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 ... -
Detecting Fetal Movements Using Non-Invasive Accelerometers: A Preliminary Analysis
Girier, T.; O'Toole, J.; Mesbah, M.; Boashash, B.; Clough, I.; Wilson, S.; Fuentes, M.; Callan, S.; East, C.; Colditz, P.... more authors ... less authors ( IEEE , 2010 , Article)Monitoring fetal movement is important to assess fetal health. Standard clinical fetal monitoring technologies include ultrasound imaging and cardiotocography. Both have limited prognostic value and require significant ... -
Detection of neonatal EEG burst-suppression using a time-frequency approach
Awal, Md. Abdul; Colditz, Paul B.; Boashash, Boualem; Azemi, Ghasem ( IEEE , 2014 , Conference Paper)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 ... -
Detection of neonatal seizure using multiple filters
Khlif, M.S.; Mesbah, M.; Boashash, Boualem; Colditz, P. ( IEEE , 2010 , Conference Paper)It is often impossible to accurately differentiate between seizure and non-seizure related activities in irifants based on clinical manifestations alone. The electroencephalogram (EEG) is therefore the best tool available ... -
Detection of perinatal hypoxia using time-frequency analysis of heart rate variability signals
Dong S.; Boashash B.; Azemi G.; Lingwood B.E.; Colditz P.B. (2013 , Conference Paper)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 ... -
Detection of seizure signals in newborns
Boashash, Boualem; Barklem, P; Keir, M ( IEEE , 1999 , Conference Paper)This paper considers a system design for processing a multidimensional biomedical signal formed by EEG, ECG, EOG and motion recorded from a newborn, for the purpose of detection of epileptic seizures in newborns as an ... -
Detection, classification, and estimation in the (t, f ) domain
Sayeed, A.M.; Papandreou-Suppappola, A.; Suppappola, S.B.; Xia, X.-G.; Hlawatsch, F.; Matz, G.; Boashash, B.; Azemi, G.; Khan, N.A.... more authors ... less authors ( Elsevier Inc. , 2016 , Book chapter)Several studies involving real-life applications have shown that methods for the detection, estimation, and classification of nonstationary signals can be enhanced by utilizing the time-frequency ((t,f)) characteristics ... -
Editorial: Time frequency and array processing of non-stationary signals
Belouchrani, Adel; Abed-Meraim, Karim; Boashash, Boualem ( Springer , 2012 , Article)Conventional time-frequency analysis methods were extended to data arrays in many applications, and there is the potential for more synergistic development of new advanced tools by exploiting the joint properties of ... -
Editorial: Time-Frequency Approach to Radar Detection, Imaging, and Classification
Thayaparan, Thayananthan; Stankovic, Ljubisa; Amin, Moeness; Chen, Victor; Cohen, Leon; Boashash, B.... more authors ... less authors ( Institution of Engineering and Technology , 2010 , Article)One of the central problems in exploiting the radar data is the analysis of atime series. The problem at hand is how to extract the information present in the data and use it to its full potential. Traditionally, radar ... -
EEG amplitude and correlation spatial decay analysis for neonatal head modelling
Odabaee M.; Layeghy S.; Mesbah M.; Azemi G.; Boashash B.; Colditz P.; Vanhatalo S.... more authors ... less authors (2012 , Conference Paper)There is an increased need to better understand the relation between brain structures and functions in newborns by using EEG source localization techniques. This requires a realistic head model that would take into account ... -
EEG background features that predict outcome in term neonates with hypoxic ischaemic encephalopathy: A structured review
Awal, Md Abdul; Lai, Melissa M.; Azemi, Ghasem; Boashash, B.; Colditz, Paul B. ( Elsevier Ireland Ltd , 2016 , Article)Objectives 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 ... -
EEG-based automatic epilepsy diagnosis using the instantaneous frequency with sub-band energies
Fani, Mohammad; Azemi, Ghasem; Boashash, Boualem ( IEEE , 2011 , Conference Paper)This paper presents a novel approach for classifying the electroencephalogram (EEG) signals as normal or abnormal. This method uses features derived from the instantaneous frequency (IF) and energies of EEG signals in ... -
Effective implementation of time–frequency matched filter with adapted pre and postprocessing for data-dependent detection of newborn seizures
Khlif, M; Colditz, P; Boashash, B ( Elsevier , 2013 , 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 ...