A new automated CNN deep learning approach for identification of ECG congestive heart failure and arrhythmia using constant-Q non-stationary Gabor transform
AS Eltrass, MB Tayel, AI Ammar - Biomedical signal processing and control, 2021 - Elsevier
Electrocardiogram (ECG) is an important noninvasive diagnostic method for interpretation
and identification of various kinds of heart diseases. In this work, a new Deep Learning (DL) …
and identification of various kinds of heart diseases. In this work, a new Deep Learning (DL) …
Automated ECG multi-class classification system based on combining deep learning features with HRV and ECG measures
AS Eltrass, MB Tayel, AI Ammar - Neural Computing and Applications, 2022 - Springer
Electrocardiogram (ECG) serves as the gold standard for noninvasive diagnosis of several
types of heart disorders. In this study, a novel hybrid approach of deep neural network …
types of heart disorders. In this study, a novel hybrid approach of deep neural network …
Automatic muscle artifacts identification and removal from single-channel eeg using wavelet transform with meta-heuristically optimized non-local means filter
Electroencephalogram (EEG) signals may get easily contaminated by muscle artifacts,
which may lead to wrong interpretation in the brain–computer interface (BCI) system as well …
which may lead to wrong interpretation in the brain–computer interface (BCI) system as well …
Deep convolutional neural network regularization for alcoholism detection using EEG signals
Alcoholism is attributed to regular or excessive drinking of alcohol and leads to the
disturbance of the neuronal system in the human brain. This results in certain malfunctioning …
disturbance of the neuronal system in the human brain. This results in certain malfunctioning …
Novel cascade filter design of improved sparse low-rank matrix estimation and kernel adaptive filtering for ECG denoising and artifacts cancellation
AS Eltrass - Biomedical Signal Processing and Control, 2022 - Elsevier
ElectroCardioGram (ECG) signals are highly vulnerable to disturbances caused by noise
and artifact sources which can degrade the ECG signal quality and increase the difficulty in …
and artifact sources which can degrade the ECG signal quality and increase the difficulty in …
Automatic epileptic seizure detection approach based on multi-stage Quantized Kernel Least Mean Square filters
AS Eltrass, MB Tayel, AF EL-qady - Biomedical Signal Processing and …, 2021 - Elsevier
Epilepsy is one of the most common neurological disorders of the brain all over the world.
For its detection, Electroencephalogram (EEG) is an important noninvasive diagnostic …
For its detection, Electroencephalogram (EEG) is an important noninvasive diagnostic …
A new automated multi-stage system of non-local means and multi-kernel adaptive filtering techniques for EEG noise and artifacts suppression
AS Eltrass, NH Ghanem - Journal of Neural Engineering, 2021 - iopscience.iop.org
Context. Electroencephalography (EEG) signals are contaminated with diverse types of
noises and artifacts, which greatly distort EEG recording and increase the difficulty in …
noises and artifacts, which greatly distort EEG recording and increase the difficulty in …
Identification and classification of epileptic EEG signals using invertible constant-Q transform-based deep convolutional neural network
AS Eltrass, MB Tayel, AF El-Qady - Journal of Neural Engineering, 2022 - iopscience.iop.org
Context. Epilepsy is the most widespread disorder of the nervous system, affecting humans
of all ages and races. The most common diagnostic test in epilepsy is the …
of all ages and races. The most common diagnostic test in epilepsy is the …
Trier: Template-guided neural networks for robust and interpretable sleep stage identification from eeg recordings
Neural networks often obtain sub-optimal representations during training, which degrade
robustness as well as classification performances. This is a severe problem in applying …
robustness as well as classification performances. This is a severe problem in applying …
Investigation of automatic spindle detection in sleep EEG signals contaminated with noise and artifact sources
AS Eltrass, NH Ghanem - Journal of Ambient Intelligence and Humanized …, 2023 - Springer
Electroencephalography (EEG) serves as the gold standard for noninvasive diagnosis of
different types of sleep disorders such as sleep apnea, insomnia, narcolepsy, restless leg …
different types of sleep disorders such as sleep apnea, insomnia, narcolepsy, restless leg …