A5077623317- EEG and Brain-Computer Interfaces
- Functional Brain Connectivity Studies
- Neural dynamics and brain function
- Image Processing Techniques and Applications
- Heart Rate Variability and Autonomic Control
- Blind Source Separation Techniques
- Advanced Vision and Imaging
- Video Surveillance and Tracking Methods
- Neural and Behavioral Psychology Studies
- Optical measurement and interference techniques
- Digital Holography and Microscopy
- Remote Sensing and LiDAR Applications
- Advanced MRI Techniques and Applications
- ECG Monitoring and Analysis
- Image Enhancement Techniques
- Image and Signal Denoising Methods
- Anomaly Detection Techniques and Applications
- Visual perception and processing mechanisms
- Neural Networks and Applications
- Virtual Reality Applications and Impacts
- Remote Sensing in Agriculture
- Advanced Image Fusion Techniques
- Gaze Tracking and Assistive Technology
- Advanced Optical Imaging Technologies
- Non-Invasive Vital Sign Monitoring
Houston Methodist Sugar Land Hospital
2023-2025
National University of Sciences and Technology
2024
Brno University of Technology
2022-2024
Korea Advanced Institute of Science and Technology
2024
Cardiff University
2024
Boston Medical Center
2022-2024
Boston University
2022-2024
Monash University
2023
Australian Regenerative Medicine Institute
2023
Petronas (Malaysia)
2011-2022
Mental stress has become a social issue and could cause of functional disability during routine work. In addition, chronic implicate several psychophysiological disorders. For example, increases the likelihood depression, stroke, heart attack, cardiac arrest. The latest neuroscience reveals that human brain is primary target mental stress, because perception determines situation threatening stressful. this context, an objective measure for identifying levels while considering considerably...
Feature extraction is an important step in the process of electroencephalogram (EEG) signal classification. The authors propose a "pattern recognition" approach that discriminates EEG signals recorded during different cognitive conditions. Wavelet based feature such as, multi-resolution decompositions into detailed and approximate coefficients as well relative wavelet energy were computed. Extracted features normalized to zero mean unit variance then optimized using Fisher's discriminant...
Treatment management for Major Depressive Disorder (MDD) has been challenging. However, electroencephalogram (EEG)-based predictions of antidepressant's treatment outcome may help during selection and ultimately improve the quality life MDD patients. In this study, a machine learning (ML) method involving pretreatment EEG data was proposed to perform such Selective Serotonin Reuptake Inhibitor (SSRIs). For purpose, acquisition experimental involved 34 patients 30 healthy controls....
Automatic identification of visual learning style in real time using raw electroencephalogram (EEG) is challenging. In this work, inspired by the powerful abilities deep techniques, learning-based models are proposed to learn high-level feature representation for EEG identification. Existing computer-aided systems that use electroencephalograms and machine can reasonably assess styles. Despite their potential, offline processing often necessary eliminate artifacts extract features, making...
ABSTRACT Wireless sensor networks comprise of a large number low cost nodes that have strictly restricted sensing, computation and communication capabilities. In addition to this, limited battery life which is not rechargeable in many applications. Due resource limitations for the nodes, it important use energy efficiently each node. This will result prolonged network lifetime functionality. Energy consumption balancing (ECB) property ensures average dissipation per equal all sensors...
Educational psychology research has linked fluid intelligence with learning and memory abilities neuroimaging studies have specifically associated event related potentials (ERPs). The objective of this study is to find the relationship ERPs recall predict score using P300 (P3) component. A sample thirty-four healthy subjects between twenty thirty years age was selected perform three tasks: (1) Raven's Advanced Progressive Matrices (RAPM) test assess intelligence; (2) task ability recall; (3)...
Assessing cognitive load during a learning phase is important, as it assists to understand the complexity of task. It can help in balancing postlearning and actual Here, we used electroencephalography (EEG) assess multimedia EEG data were collected from 34 human participants at baseline state. The analysis was based on feature extraction partial directed coherence (PDC). Results revealed that frequency bands activated brain regions contribute differed depending We concluded be assessed using...