Nidal S. Kamel

Nidal S. Kamel
Universiti Teknologi Petronas | UTP · Department of Electrical and Electronics Engineering

PhD (Statistical Signal Processing)

About

226
Publications
55,798
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
3,384
Citations

Publications

Publications (226)
Article
Full-text available
Introduction Social anxiety disorder (SAD) is a prevalent psychiatric condition characterized by an intense fear of and avoidance of social situations. Traditional assessment methods for SAD primarily rely on subjective self-report questionnaires and clinical interviews, which can be prone to biases and inaccuracies. This study aims to explore the...
Chapter
Background initialization is an essential step for both hand-crafted and deep learning foreground segmentation approaches. In this paper, we propose a low-rank approximation algorithm that effectively handles the challenge caused by Stationary Foreground Objects (SFOs) on both offline and online bases. The proposed algorithm employs different incre...
Article
Full-text available
Introduction The early diagnosis and classification of social anxiety disorder (SAD) are crucial clinical support tasks for medical practitioners in designing patient treatment programs to better supervise the progression and development of SAD. This paper proposes an effective method to classify the severity of SAD into different grading (severe,...
Article
Background and Objective: Brain connectivity plays a pivotal role in understanding the brain’s information processing functions by providing various details including magnitude, direction, and temporal dynamics of inter-neuron connections. While the connectivity may be classified as structural, functional and causal, a complete in-vivo directional...
Article
Foreground segmentation is an essential processing phase in several change detection-based applications. Classical foreground segmentation is highly dependent on the accuracy of the estimated background model and the procedures followed to subtract such model from the original frame. Obtaining good foreground masks via background subtraction remain...
Conference Paper
Electroencephalogram (EEG) plays an essential part in identifying brain function and behaviors for different mental states. Nevertheless, the captured electrical activity is always found to be contaminated with various artifacts that negatively influence the accuracy of EEG analysis. Therefore, it is crucial to build a model to constructively ident...
Article
Full-text available
Brain neuroimaging studies have found that social anxiety disorder (SAD) is correlated with aberration in regional or network-level brain function. In this study, SAD-related alternation in brain connections within the default mode network (DMN) was investigated. Partial directed coherence (PDC) was used to assess the causal influences of DMN regio...
Article
This study aims to evaluate the effect of workstation type on the neural and vascular networks of the prefrontal cortex (PFC) underlying the cognitive activity involved during mental stress. Workstation design has been reported to affect the physical and mental health of employees. However, while the functional effects of ergonomic workstations hav...
Article
Full-text available
Motor imagery (MI)-based brain-computer interfaces have gained much attention in the last few years. They provide the ability to control external devices, such as prosthetic arms and wheelchairs, by using brain activities. Several researchers have reported the inter-communication of multiple brain regions during motor tasks, thus making it difficul...
Article
Full-text available
Stress is a complex response that begins when people are exposed to various stressors, including psychological and environmental factors, which are associated with negative cognitive effects. However, little is known about their interactions within the brain. This research aimed to examine the influence of low and high noise levels in the workplace...
Article
Full-text available
Recent brain imaging findings by using different methods (e.g., fMRI and PET) have suggested that social anxiety disorder (SAD) is correlated with alterations in regional or network-level brain function. However, due to many limitations associated with these methods, such as poor temporal resolution and limited number of samples per second, neurosc...
Article
Full-text available
Neuroimaging investigations have proven that social anxiety disorder (SAD) is associated with aberrations in the connectivity of human brain functions.The assessment of the effective connectivity (EC) of the brain and its impact on the detection and medication of neurodegenerative pathophysiology is hence a crucial concern that needs to be addresse...
Article
Full-text available
Alcohol Use Disorder (AUD) is a chronic relapsing brain disease characterized by excessive alcohol use, loss of control over alcohol intake, and negative emotional states under no alcohol consumption. The key factor in successful treatment of AUD is the accurate diagnosis for better medical and therapy management. Conventionally, for individuals to...
Conference Paper
Social Anxiety Disorder (SAD) is a prevalent, debilitating, and psychiatric condition marked by intense anxiety of being evaluated of negative appraisal or criticism in social events, which results in greater functional impairment in the brain. The main objective of this study is to quantify the severity of SAD by using effective connectivity (EC)....
Article
Full-text available
This study aims to investigate the effects of workplace noise on neural activity and alpha asymmetries of the prefrontal cortex (PFC) during mental stress conditions. Workplace noise exposure is a pervasive environmental pollutant and is negatively linked to cognitive effects and selective attention. Generally, the stress theory is assumed to under...
Preprint
Full-text available
Several neuroimaging findings by using different modalities (e.g., fMRI and PET) have suggested that social anxiety disorder (SAD) is correlated with alterations in regional or network-level brain function. However, these modalities do not quantify the fast dynamic connectivity of causal information networks due to their poor temporal resolution. I...
Article
Full-text available
Major depressive disorder (MDD), which is also known as unipolar depression, is one of the leading sources of functional frailty. MDD is mostly a chronic disorder that requires a long duration of treatment and clinical management. One of the critical issues in MDD treatment is the need for it’s early diagnosis. Conventional tools in MDD diagnosis a...
Article
Full-text available
Videos are full of dynamic changes along both the spatial and temporal dimensions. Large, jerky short-term motions make it difficult to extract significant changes from videos such as subtle color changes and long-term motions occurring in time-lapse sequences. In this paper, we introduce two singular value decomposition (SVD)-based video decomposi...
Article
The complexity of a scene in addition to the need for real-time processing are the main challenges that face any background/foreground separation approach for maritime environment. Recent studies on Low-rank and Sparse Separation (LSS) achieved good performance when compared to traditional background subtraction techniques in segregating the fore...
Article
Objective The purpose of this study is to examine the effect of the workstation type on the severity of mental stress by means of measuring prefrontal cortex (PFC) activation using functional near-infrared spectroscopy. Background Workstation type is known to influence worker’s health and performance. Despite the practical implications of ergonomi...
Article
Workplace noises, such as realistic environmental and occupational noises, routinely take place in the work environment and have been linked with negative cognitive effects. Little is known about their impact on brain activity during mental stress. The current study aimed to investigate the effects of workplace environments, quiet and noisy, on bra...
Article
The background Initialization (BI) problem has attracted the attention of researchers in different image/video processing fields. Recently, a tensor-based technique called spatiotemporal slice-based singular value decomposition (SS-SVD) has been proposed for background initialization. SS-SVD applies the SVD on the tensor slices and estimates the ba...
Article
Full-text available
Localizing brain neural activity using electroencephalography (EEG) neuroimaging technique is getting increasing response from neuroscience researchers and medical community. It is due to the fact that brain source localization has a variety of applications for diagnoses of various brain disorders. This problem is ill‐posed in nature because an inf...
Article
Full-text available
The periodicity of an object is one of its most important visual characteristics. Recently, several low-rank/sparse matrix decomposition techniques have indicated that a relationship exists between the frequency components of the motion matrix and its decomposition components. This relationship was mostly identified based on empirical evidence with...
Article
Full-text available
Brain source activation is caused due to certain mental or physical task, and such activation is localized by using various optimization techniques. This localization has vital application for diagnoses of various brain disorders such as epilepsy, schizophrenia, Alzheimer, depression, Parkinson and stress. Various neuroimaging techniques (such as E...
Article
Neuroscientists have investigated the functionality of the brain in detail and achieved remarkable results but this area still need further research. Functional magnetic resonance imaging (fMRI) is considered as the most reliable and accurate technique to decode the human brain activity, on the other hand electroencephalography (EEG) is a portable...
Article
In tasks such as abandoned luggage detection and stopped car detection, Stationary Foreground Objects (SFOs) need to be detected and properly classified in real time. Different methods have been proposed to detect SFOs, but they are mainly focused on certain types of objects. In this paper, an incremental singular value decomposition-based method i...
Article
Full-text available
This research studies the impact of the imagination of movements and associated feedbacks on the modulation of sensorimotor electroencephalographic (EEG) rhythms, for the online controls of a brain-computer interface (BCI). Nine subjects with no physical or mental impairments were selected. The number of sessions was five: one calibration and four...
Article
Full-text available
The monitoring of vegetation near high-voltage transmission power lines and poles is tedious. Blackouts present a huge challenge to power distribution companies and often occur due to tree growth in hilly and rural areas. There are numerous methods of monitoring hazardous overgrowth that are expensive and time-consuming. Accurate estimation of tree...
Article
Full-text available
Accurate segregation of pectoral muscles is very crucial in breast cancer detection. Pectoral segmentation is a challenging task due to heterogeneous tissues densities, neighborhood complexities and breast shape variabilities. This paper presents an adaptive gamma correction method for pectoral suppression in mammograms. The proposed algorithm is a...
Article
Full-text available
This paper presents a new approach for breast cancer classification using time series analysis. In particular, the region of interest (ROI) in mammogram images is classified as normal or abnormal using dynamic time warping (DTW) as a similarity measure. According to the analogous case in time series analysis, the DTW subsumes Euclidean distance (ED...
Article
Full-text available
Complaints of stress are common in modern life. Psychological stress is a major cause of lifestyle-related issues, contributing to poor quality of life. Chronic stress impedes brain function, causing impairment of many executive functions, including working memory, decision making and attentional control. The current study sought to describe newly...
Article
Full-text available
For crowd analytics and surveillance systems, motion estimation is an essential first step. Lots of crowd motion estimation algorithms have been presented in the last years comprising pedestrian motion. However, algorithms based on optical flow and background subtraction have numerous limitations such as the complexity of the computation in the pre...
Article
Acne vulgaris is a chronic skin abnormality that can afflict a person at any stage of life; however, it is more common in adolescent population. Due to the subjectivity and difficulty of the commonly used assessment methods such as photography and lesion counting, discrepancy is usually observed in the severity grading of acne vulgaris patients. In...
Article
Background: The abnormal alcohol consumption could cause toxicity and could alter the human brain's structure and function, termed as alcohol used disorder (AUD). Unfortunately, the conventional screening methods for AUD patients are subjective and manual. Hence, to perform automatic screening of AUD patients, objective methods are needed. The ele...
Article
Full-text available
Each mental or physical task gives rise to generate electromagnetic activity in the brain. These electrical signals are analyzed by using various neuroimaging techniques which include electroencephalography (EEG), magnetoencephalogy (MEG), positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). However, when the brain s...
Article
Abstract—Each mental or physical task gives rise to generate electromagnetic activity in the brain. These electrical signals are analyzed by using various neuroimaging techniques which include electroencephalography (EEG), magnetoencephalogy (MEG), positron emission tomography (PET) and functional magnetic resonance imaging (fMRI). However, when th...
Article
Full-text available
Mental stress has become a social issue and could become a cause of functional disability during routine work. In addition, chronic stress could implicate several psychophysiological disorders. For example, stress increases the likelihood of depression, stroke, heart attack and cardiac arrest. The latest neuroscience reveals that the human brain is...
Article
Background: Electrical signals are generated inside human brain due to any mental or physical task. This causes activation of several sources inside brain which are localized using various optimization algorithms. Methods: Such activity is recorded through various neuroimaging techniques like fMRI, EEG, MEG etc. EEG signals based localization is...
Article
Full-text available
Human behavior analysis has become a critical area of research in computer vision and artificial intelligence research community. In recent years, video surveillance systems of crowd scenes have witnessed an increased demand in different applications such as safety, security, entertainment and personal mental health. Although many methods have been...
Article
Full-text available
Human brain has a complex structure with billions of neurons, so it is a difficult and challenging task to predict the behavior of human brain. Different methods and classifiers are used to measure and classify the brain activities with higher accuracy and reliability. In this study, instead of using mostly used classifier (support vector machine),...
Article
Full-text available
Vehicular ad-hoc networks (VANETs) play an important role in intelligent transportation systems (ITS) for improving security and efficiency. However, due to the dynamic characteristics of the vehicular environment, routing remains a significant challenge in VANETs. While single-layer routing protocols based on the traditional layered open systems i...
Conference Paper
Subspace techniques are widely used for direction of arrival (DOA) problems in telecommunications and position location applications for estimating the location of sources from where the signal is originated. This source estimation problem is analogues to the source estimation problem in EEG signal processing commonly termed as EEG inverse problem....
Article
Decoding of human brain activity has always been a primary goal in neuroscience especially with functional magnetic resonance imaging (fMRI) data. In recent years, Convolutional neural network (CNN) has become a popular method for the extraction of features due to its higher accuracy, however it needs a lot of computation and training data. In thi...
Article
Full-text available
This paper presents a classification method for normal and abnormal region of interests (ROIs) in breast cancer using the chi-square distance on the texture features obtained from the local binary pattern (LBP) technique. The LBP features are calculated independently at different radii pixels in the varying neighborhood pixels using two different L...
Article
Background: Classification of the visual information from the brain activity data is a challenging task. Many studies reported in the literature are based on the brain activity patterns using either fMRI or EEG/MEG only. EEG and fMRI considered as two complementary neuroimaging modalities in terms of their temporal and spatial resolution to map th...
Conference Paper
This paper highlights the difference in brain dynamics in terms of activity and connectivity of the brain between stress and control conditions. In a cross-over experimental design, 22 subjects participated to perform arithmetic task under stress and control environments in which electroencephalogram (EEG) data were recorded. Prior to arithmetic ta...
Chapter
In this paper, four class motor imagery classification has been studied for brain com-puter interface. Feature investigations were conducted on the Enobio device, firstly with all 8 channels (F3, F4, T7, C3, C4, Cz, T8 and Pz) and subsequently with 3 selected channels (C4 left hand, C3 right hand, C3 and C4 both hand and Cz both feet) in alpha and...
Conference Paper
Efficient Routing in Vehicular Ad Hoc Networks (VANETs) is one of the main challenges faced while providing reliable communication in the vehicular environment. Routing approaches that make routing decisions on the fly during data transmissions are much more suitable for the high mobility and variable density conditions present in the vehicular env...
Conference Paper
The segmentation of acne vulgaris lesions is a crucial step for the classification and developing a severity assessment system. In this paper, an unsupervised technique is proposed for the segmentation of acne vulgaris lesions. The effect of color feature normalization on segmentation results is examined. Two types of normalization is performed — i...
Conference Paper
The study investigates the effects of street light colors on driver alertness in aim to improve the traffic safety element. In order to achieve this objective, the human P100 visual evoked potentials (VEPs) responses are stimulated to different colors (red, green, blue, and yellow) with to levels of intensity, and twenty (20) healthy subjects with...
Conference Paper
Optical flow technique is one of the significant motion estimation techniques. Due to its importance, several optical flow technique have been used in order to estimate the velocity and the direction of the pedestrians in the crowded scenes. This paper presents an overview of the optical flow methods that used mainly for pedestrian and crowd motion...
Conference Paper
Cognitive state classification is a challenging task. Many studies were reported using different neuroimaging modalities for classification of the cognitive states of the human brain e.g., EEG, fMRI, MEG etc. However, functional MRI seems to be appropriate for these papers as due to its good spatial resolution and localizing the brain activated reg...
Conference Paper
Mental stress that is originated due to high task demands affects our life. Human brain is a target of stress. Neuronal variations take place in the brain and make many brain regions communicate with each other to process the information flow. Electroencephalographic (EEG) coherence is a mathematical representation of cross talk between two brain r...
Conference Paper
Human brain is considered as complex system having different mental states e.g., rest, active or cognitive states. It is well understood fact that brain activity increases with the cognitive load. This paper describes the cognitive and resting state classification based on EEG features. Previously, most of the studies used linear features. EEG sign...
Conference Paper
Functional magnetic resonance imaging (fMRI) is one of the most popular and reliable modality to measure brain activities. The quality of fMRI data is best among other modalities such as Electroencephalography (EEG) and Magnetoencephalography (MEG). In fMRI, normally number of features are more than the number of instances so it is necessary to sel...
Article
Memory plays an important role in human life. Memory can be divided into two categories, i.e., long term memory and short term memory (STM). STM or working memory (WM) stores information for a short span of time and it is used for information manipulations and fast response activities. WM is generally involved in the higher cognitive functions of t...
Article
Feature extraction and classification for electroencephalogram (EEG) in medical applications is a challenging task. The EEG signals produce a huge amount of redundant data or repeating information. This redundancy causes potential hurdles in EEG analysis. Hence, we propose to use this redundant information of EEG as a feature to discriminate and cl...
Article
Electroencephalography (EEG) is widely used in variety of research and clinical applications which includes the localization of active brain sources. Brain source localization provides useful information to understand the brain's behavior and cognitive analysis. Various source localization algorithms have been developed to determine the exact locat...
Conference Paper
Full-text available
In recent years, the need for an assistive device such as a wheelchair has increased, due to an increasing demand on rehabilitation for disabled people. Typical wheelchair controls based on body part movements include some measurements of muscle controls, head/eyeball positions and visual/auditory controls. However, the design of a robust method ha...
Article
Full-text available
Breast cancer is one of the leading causes of death among women worldwide. Early detection of breast cancer significantly reduces the mortality rate. Computer aided diagnosis (CAD) systems assist the clinicians for early detection, however they are still far from perfection due to morphological diversity of abnormalities in mammograms. In this stud...
Article
Full-text available
Consumer preference is rapidly changing from 2D to 3D movies due to the sensational effects of 3D scenes, like those in Avatar and The Hobbit. Two 3D viewing technologies are available: active shutter glasses and passive polarized glasses. However, there are consistent reports of discomfort while viewing in 3D mode where the discomfort may refer to...
Conference Paper
Velocity and direction estimation plays an important role in crowd analytic and behavior recognition. This paper presents an overview of the literature published for motion detection and estimation techniques. The work particularly focuses on optical flow techniques such as Lucas & Kanade and Horn & Schunck methods which describe the direction and...
Chapter
Full-text available
Cognitive task produces activation in the brain which are different from normal state. In order to study the brain behavior during cognitive state, different techniques are available. Wavelet energy and power spectral density (PSD) are well established methods for brain signal classification. In this paper, cognitive state of the brain is compared...
Conference Paper
The localization of active sources inside the brain is termed as brain source localization. However, when the neuroimaging technique is EEG, then it is specifically termed as EEG source localization. This problem is also referred to as EEG inverse problem. The source localization problem is defined by forward problem and inverse problem. For the fo...