2,895 research outputs found
EEG-based brain source localization of mental stress using the SAFFIRE method
No full textA Master of Science thesis in Electrical Engineering by Nada Zahour entitled, “EEG-based brain source localization of mental stress using the SAFFIRE method”, submitted in April 2024. Thesis advisor is Dr. Hasan Al-Nashash and thesis co-advisor is Dr. Hasan Mir. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
LCMV-Based EEG & FNIRS-Based Brain Source Localization of Mental Stress
No full textA Master of Science thesis in Biomedical Engineering by Ismat Feras Ismat Almadani entitled, “LCMV-Based EEG & FNIRS-Based Brain Source Localization of Mental Stress”, submitted in May 2024. Thesis advisor is Dr. Hasan Mir and thesis co-advisor is Dr. Hasan Al-Nashash. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).College of EngineeringMultidisciplinary ProgramsMaster of Science in Biomedical Engineering (MSBME
Transmit Beamforming Methods for the Frequency Diverse Array
No full textA Master of Science thesis in Electrical Engineering by Mobeen Mahmood entitled, “Transmit Beamforming Methods for the Frequency Diverse Array”, submitted in May 2019. Thesis advisor is Dr. Hasan Mir. Soft and hard copy available.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
Functional microRNA high throughput screening reveals miR-9 as a central regulator of liver oncogenesis by affecting the PPARA-CDH1 pathway
No full textBackground: Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related deaths, reflecting the aggressiveness of this type of cancer and the absence of effective therapeutic regimens. MicroRNAs have been involved in the pathogenesis of different types of cancers, including liver cancer. Our aim was to identify microRNAs that have both functional and clinical relevance in HCC and examine their downstream signaling effectors. Methods: MicroRNA and gene expression levels were measured by quantitative real-time PCR in HCC tumors and controls. A TargetScan algorithm was used to identify miR-9 downstream direct targets. Results: A high-throughput screen of the human microRNAome revealed 28 microRNAs as regulators of liver cancer cell invasiveness. MiR-9, miR-21 and miR-224 were the top inducers of HCC invasiveness and also their expression was increased in HCC relative to control liver tissues. Integration of the microRNA screen and expression data revealed miR-9 as the top microRNA, having both functional and clinical significance. MiR-9 levels correlated with HCC tumor stage and miR-9 overexpression induced SNU-449 and HepG2 cell growth, invasiveness and their ability to form colonies in soft agar. Bioinformatics and 3’UTR luciferase analyses identified E-cadherin (CDH1) and peroxisome proliferator-activated receptor alpha (PPARA) as direct downstream effectors of miR-9 activity. Inhibition of PPARA suppressed CDH1 mRNA levels, suggesting that miR-9 regulates CDH1 expression directly through binding in its 3’UTR and indirectly through PPARA. On the other hand, miR-9 inhibition of overexpression suppressed HCC tumorigenicity and invasiveness. PPARA and CDH1 mRNA levels were decreased in HCC relative to controls and were inversely correlated with miR-9 levels. Conclusions: Taken together, this study revealed the involvement of the miR-9/PPARA/CDH1 signaling pathway in HCC oncogenesis
An Intraoral Camera for Supporting Assistive Devices
No full textA Master of Science thesis in Mechatronics Engineering by Muhammad Amin Tily entitled, “An Intraoral Camera for Supporting Assistive Devices”, submitted in December 2018. Thesis advisor is Dr. Hasan Al-Nashash and thesis co-advisor is Dr. Hasan Mir. Soft and hard copy available.Thousands of patients around the globe are affected by paralysis which hinders the fulfilment of their basic needs such as mobility and speech. Several research topics have been dedicated to improve the livelihood of paralytic patients and a small subset of the topics has focused on capturing inputs from the tongue. The tongue is a muscular organ directly connected to the brain through a cranial nerve known as the hypoglossal nerve which is responsible for the motor functions of the tongue. Hence, tongue movements are not affected during spinal cord injuries, which is one of the major causes of paralysis. Given the importance of capturing inputs from the tongue, this research proposes a novel method of using an intraoral camera for this purpose. It discusses the methods used for capturing the images with the help of an Endoscope camera. It explains how the features were extracted in real-time using image processing techniques on each captured frame and how the orientation and position of the tongue was then accurately classified into one of the 11 possible categories to produce specific outputs which could be used by paralytic patients as inputs to any external system. After testing the system with a data entry application, an average of 19.34 correct entries per minute was calculated from 5 different experiments, and an average error rate of 3.96% was obtained, which outperforms systems such as the Resistopalatography and the MouthPad in terms of accuracy.College of EngineeringMultidisciplinary ProgramsMaster of Science in Mechatronics Engineering (MSMTR
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Ali Husain Mir Interview
No full textAli Husain Mir is a Bollywood lyricist and script writer and a professor of Management at William Paterson University. Mir visited the Hindi Urdu Flagship at the University of Texas at Austin to speak to Flagship students about his career in Urdu literature and Bollywood production. For this interview, Mir sat down with HUF directors, Syed Akbar Hyder and Herman van Olphen, to discuss his background in Urdu and the state of the language in modern India. Mir is the author of Anthems of Resistance, the definitive book on the All India Progressive Writers’ Movement; he is also an acclaimed lyricist and script-writer for Hindi and Urdu films (Iqbal, Dor). Mir’s oeuvre engages issues of religious minorities and secularism in South Asia.Asian Studie
Adaptive Time-Varying Brain Source Localization
No full textA Master of Science thesis in Biomedical Engineering by Sajedah A. Al-Momani entitled, “Adaptive Time-Varying Brain Source Localization”, submitted in November 2019. Thesis advisor is Dr. Hasan Mir and thesis co-advisor is Dr. Hasan Al-Nashash. Soft copy is available (Thesis, Approval Signatures, Completion Certificate, and AUS Archives Consent Form).According to the most recent statistics provided by the World Health Organization, 50 million individuals around the world are diagnosed with epilepsy with 2.5 million new cases diagnosed annually. One-third of this large population are refractory epileptic patients who resist the antiepileptic drugs. Accordingly, the recommended solution is to surgically resect the seizure onset zone (SOZ). To ensure favourable surgical outcomes in terms of being seizure free and avoiding undesirable consequences, a precise identification of the SOZ is a critical factor. Electroencephalograph (EEG) is usually used along with advanced imaging techniques to localize and identify the SOZ. The high temporal resolution of EEG makes it a convenient tool to study the dynamic and rapid propagating nature of epileptic spikes. Incorporating the spatiotemporal propagating characteristic of epileptic spikes in the formulation of the EEG source localization problem enhances the identification of SOZs corresponding to both fixed and moving sources. Therefore, the main objective of this thesis is to localize and track, with acceptable computational time and localization error, the spatiotemporal dynamics of epileptic sources. To do so, the time-varying source localization problem is solved using two methods, namely the Source Affine Image Reconstruction (SAFFIRE) algorithm and a proposed Steepest Descent algorithm. The derivation of these methods is based on finding filter weights that minimize the mean squared error cost function. The main reason behind proposing the Steepest Descent method is to obtain a new estimation of the source vector with each newly received data sample. The performance of these methods is investigated on simulated data mimicking two scenarios: a spatially fixed source and a spatially moving source. For the moving source scenario, the results showed that the SAFFIRE algorithm had a 0.9±0.05 localization error compared to a 1.69±0.06 for the Steepest Descent. The execution time of the SAFFIRE algorithm was 9-folds higher compared to Steepest Descent. Finally, the two algorithms are applied on a high-density simulated epileptic spike originated from a fixed source. Results showed that both algorithms provided similar localization error. This suggests that both algorithms may perform similar to each other at higher number of electrodes.College of EngineeringMultidisciplinary ProgramsMaster of Science in Biomedical Engineering (MSBME
Brain Source Localization in the Presence of Leadfield Perturbations
No full textA Master of Science thesis in Electrical Engineering by Rabiya Nakhat Momin entitled, "Brain Source Localization in the Presence of Leadfield Perturbations," submitted in May 2015. Thesis advisors are Dr. Hasan Mir and Dr. Hasan Al-Nashash. Soft and hard copy available.Brain source localization enables us to localize different areas of the brain that are activated during any mental activity. This thesis makes use of Electroencephalography (EEG) recordings which is an important noninvasive tool for studying the temporal dynamics of the human brain. EEG source localization finds its applications in cognitive neuroscience in order to develop a Brain Computer Interface (BCI), and in psychopharmacology and psychiatry, to localize sources in certain frequency bands. Unfortunately, EEG readings cannot directly indicate the location of the source of brain activity using the signals measured on the scalp, which contributes to the ambiguity of the inverse problem. In order to solve the ill-posed inverse problem, array processing methods are implemented, in conjunction with various techniques that are applied, to improve the localization in the presence of calibration errors. In this thesis, a recently developed G-MUSIC algorithm is applied to the problem of brain source localization. G-MUSIC is a form of weighted MUSIC that performs better in scenarios where only limited sample support is available. Two transfer function based calibration algorithms are also developed to estimate the accurate location of neural activity in the brain when the measured leadfield is perturbed. The localization performance of G-MUSIC is compared to the traditional MUSIC algorithm and quantified in terms of the localization error. This thesis also addresses the problem of localization when exact knowledge of the leadfield matrix, for an individual head anatomy, is not available, by developing an iterative algorithm. This algorithm includes a high resolution localization technique, recently used in radar field, called Source Affine Image Reconstruction Algorithm (SAFFIRE) that can determine the model order (number of sources) and their locations. A beamformer is then designed in order to estimate the dipole source amplitudes. Finally, the EEG signal is reconstructed and related to the actual EEG signal via a calibration matrix. This procedure is repeated until a convergence criteria is met. The performance of this algorithm is quantified in terms of the localization error and accuracy and further validated by applying it to experimental data. In conclusion, the algorithm is also tested on non-stationary EEG signal, where a variant of the conventional adaptive beamformer is applied in order to estimate the source signal amplitudes.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
Measurement of Vigilance Using EEG Source Localization
No full textA Master of Science thesis in Electrical Engineering by Salma Khaled Mohamad Zeid entitled, "Measurement of Vigilance Using EEG Source Localization," submitted in November 2017. Thesis advisor is Dr. Hasan Al-Nashash and thesis co-advisor is Dr. Hasan Mir. Soft and hard copy available.Vigilance, or sustained attention, is crucial for jobs where attentiveness for prolonged times is required. These jobs include air traffic control, luggage inspection, and surveillance jobs. Vigilance decrement can cause catastrophic consequences. Therefore, vigilance level assessment is a widely-researched topic. Several methods have been used to assess vigilance levels such as eye tracking techniques which include monitoring saccadic eye movements and pupil size variation. Other methods used are heart rate variability, and physiological data such as electrocardiogram (ECG), electro-oculogram (EoG) and electroencephalogram (EEG). EEG data has been found to have strong correlations with human's vigilance level. This thesis report presents a novel method for the assessment of vigilance decrement using EEG data that embarks upon the brain's temporal behavior. An experiment based on a 20 to 30-minute Psychomotor Vigilance Task (PVT), that simulates real applications where vigilance decrement is observed, was carried out on 33 subjects and their EEG recordings and reaction times were collected. In the PVT task, subjects were required to respond to target events while refraining from non-target events. Vigilance reinforcement by challenge integration was tested where 22 out of the 33 subjects had an additional task where they had to respond to noisy target events. The spectral power density characteristics namely the delta, theta, alpha and beta waves of the EEG data are compared for low and high vigilance states. Furthermore, EEG source localization is utilized to monitor source dynamics of the brain in transition from vigilance states. Results from both methods are analyzed using Student's t-test with the significance threshold set at 0.1. Power spectral density analysis showed that power in AF8 electrode in delta, theta and alpha bands increased with vigilance decrement with p-values .023, .079 and .020 respectively. The source localization approach showed an increase in prefrontal source distribution with vigilance decrement with p-value of .015. The joint probability function of the prefrontal delta, theta and alpha bands as well as the source dynamics of prefrontal activity showed promise in constructing a vigilance assessment model to identify vigilance state from labeled data by yielding an 84.85% accurate detection.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
Cortical EEG Source Localization of Focal Epilepsy
No full textA Master of Science thesis in Electrical Engineering by Wisal Elfatih Mohamed Siyam entitled, “Cortical EEG Source Localization of Focal Epilepsy”, submitted in November 2017. Thesis advisor is Dr. Hasan Mir and thesis co-advisor is Dr. Hasan Al-Nashash. Soft and hard copy available.Brain source localization allows us to localize different brain regions that are activated during neural activity. Several imaging modalities can be used for recording neural activity and are essential in clinical applications. One of these clinical applications is epilepsy diagnosis and localization. Structural or/and functional imaging techniques are used for patients to investigate epilepsy, classify seizures, and in pre-surgical evaluation. This report summarizes the most common imaging techniques for epilepsy diagnosis. It will then make use of electroencephalography (EEG) readings to localize epileptogenic regions in the brain, as it is a noninvasive technique with high temporal resolution. In addition, EEG requires low-cost hardware when compared with the other modalities such as functional Magnetic Resonance Imaging (fMRI), Positron Emission Tomography (PET), and Single Photon Emission Computed Tomography (SPECT). Moreover, the most common source models are discussed along with the used signal processing based techniques for source localization. In this work, distributed sources dipole model algorithms including the SAFFIRE and sLORETA are discussed and applied to simulated epileptic spikes. Upon examination of these algorithms, their potential in epilepsy source localization was proven with relatively low localization errors of 6.25 cm and 3.55 cm for sLORETA and SAFFIRE algorithms respectively. The SAFFIRE algorithm performance is investigated on epilepsy real data where the localized epileptogenic foci were consistent to the suggested locations by neurologists. Furthermore, the effect of reducing the number of electrodes on the source localization error was investigated on simulated epileptic spikes. The source localization error increased by 2.18 cm when reducing the number of electrodes from 256 down to 128. Then it increased by 3.7 mm when going from 128 electrodes to 64 electrodes. In conclusion, the localization error is inversely proportional to the number of electrodes used for recording brain potentials.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
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