Physical Sciences and Mathematics | Open Access Articles

Smartfunction: An Immersive Vr System To Assess Attention Using Embodied Cognition, Ashish Jaiswal, Aref Hebri, Pavel Hamza Reza, Zadeh Mohammad Zaki, Fillia Makedon

Computer Science and Engineering Faculty Publications

In traditional neuropsychological tests, executive functions (EFs) are typically evaluated using paper and pencil or computer-based sit-down tasks. However, a new assessment framework, the Automated Test of Embodied Cognition (ATEC), has been developed to measure EFs and embodied cognition through physical tasks. This paper proposes integrating the ATEC system with virtual reality (VR) to evaluate and diagnose attention-deficit disorders using embodied cognition (EC) principles. The VR system will utilize Meta Quest 2 VR headsets and controllers with motion sensors to accurately capture users’ physical movements. The collected motion data will be transmitted to a remote server for evaluation through machine …

Go to article

Detecting Cognitive Fatigue In Subjects With Traumatic Brain Injury From Fmri Scans Using Self-Supervised Learning, Ashish Jaiswal, Ramesh Babu Ashwin, Zadeh Mohammad Zaki, Glenn Wylie, Fillia Makedon

Computer Science and Engineering Faculty Publications

Understanding cognitive states from fMRI data have yet to be investigated to its full extent due to its complex nature. In this work, the problem of understanding cognitive fatigue among TBI patients has been formulated as a multi-class classification problem. We built a Spatio-temporal encoder model using convolutions and LSTMs as the building blocks to extract spatial features and to model the 4D nature of fMRI scans. To learn a better representation of the data and the condition, we used a self-supervised learning technique called "Contrastive Learning" to pretrain our encoder with a public dataset BOLD5000 and further fine-tuned our …

Go to article

Application Of A Gene Modular Approach For Clinical Phenotype Genotype Association And Sepsis Prediction Using Machine Learning In Meningococcal Sepsis, Asrar Rashid, Arif R. Anwary, Feras Al-Obeidat, Joe Brierley, Mohammed Uddin, Hoda Alkhzaimi, Amrita Sarpal, Mohammed Toufiq, Zainab A. Malik, Raziya Kadwa, Praveen Khilnani, M. Guftar Shaikh, Govind Benakatti, Javed Sharief, Syed Ahmed Zaki, Abdulrahman Zeyada, Ahmed Al-Dubai, Wael Hafez, Amir Hussain

All Works

Sepsis is a major global health concern causing high morbidity and mortality rates. Our study utilized a Meningococcal Septic Shock (MSS) temporal dataset to investigate the correlation between gene expression (GE) changes and clinical features. The research used Weighted Gene Co-expression Network Analysis (WGCNA) to establish links between gene expression and clinical parameters in infants admitted to the Pediatric Critical Care Unit with MSS. Additionally, various machine learning (ML) algorithms, including Support Vector Machine (SVM), Naive Bayes, K-Nearest Neighbors (KNN), Decision Tree, Random Forest, and Artificial Neural Network (ANN) were implemented to predict sepsis survival. The findings revealed a transition …

Go to article

Physical Sciences and Mathematics Commons^™

Full-Text Articles in Physical Sciences and Mathematics

Smartfunction: An Immersive Vr System To Assess Attention Using Embodied Cognition, Ashish Jaiswal, Aref Hebri, Pavel Hamza Reza, Zadeh Mohammad Zaki, Fillia Makedon

Computer Science and Engineering Faculty Publications

Detecting Cognitive Fatigue In Subjects With Traumatic Brain Injury From Fmri Scans Using Self-Supervised Learning, Ashish Jaiswal, Ramesh Babu Ashwin, Zadeh Mohammad Zaki, Glenn Wylie, Fillia Makedon

Computer Science and Engineering Faculty Publications

All Works