Items where Author is "Mumtaz, W."

Qayyum, A. and Ahmad, I. and Mumtaz, W. and Alassafi, M.O. and Alghamdi, R. and Mazher, M. (2020) Automatic segmentation using a hybrid dense network integrated with an 3D-atrous spatial pyramid pooling module for computed tomography (CT) imaging. IEEE Access, 8. pp. 169794-169803.

Babiker, A. and Faye, I. and Mumtaz, W. and Malik, A.S. and Sato, H. (2019) EEG in classroom: EMD features to detect situational interest of students during learning. Multimedia Tools and Applications, 78 (12). pp. 16261-16281.

Hafeez, Y. and Ali, S.S.A. and Mumtaz, W. and Moinuddin, M. and Adil, S.H. and Al-Saggaf, U.M. and Yasin, M.A.B.M. and Malik, A.S. (2019) Investigating Neurofeedback Protocols for Stress Mitigation: A Comparative Analysis of Different Stimulus Contents. IEEE Access, 7. pp. 141021-141035.

Hafeez, Y. and Ali, S.S.A. and Mumtaz, W. and Moinuddin, M. and Adil, S.H. and Al-Saggaf, U.M. and Yasin, M.A.B.M. and Malik, A.S. (2019) Investigating Neurofeedback Protocols for Stress Mitigation: A Comparative Analysis of Different Stimulus Contents. IEEE Access, 7. pp. 141021-141035.

Mumtaz, W. and Saad, M.N.B.M. and Kamel, N. and Ali, S.S.A. and Malik, A.S. (2018) An EEG-based functional connectivity measure for automatic detection of alcohol use disorder. Artificial Intelligence in Medicine, 84. pp. 79-89.

Mumtaz, W. and Saad, M.N.B.M. and Kamel, N. and Ali, S.S.A. and Malik, A.S. (2018) An EEG-based functional connectivity measure for automatic detection of alcohol use disorder. Artificial Intelligence in Medicine, 84. pp. 79-89.

Subhani, A.R. and Mumtaz, W. and Kamil, N. and Saad, N.M. and Nandagopal, N. and Malik, A.S. (2018) MRMR based feature selection for the classification of stress using EEG. Proceedings of the International Conference on Sensing Technology, ICST, 2017-D. pp. 1-4.

Mumtaz, W. and Ali, S.S.A. and Yasin, M.A.M. and Malik, A.S. (2018) A machine learning framework involving EEG-based functional connectivity to diagnose major depressive disorder (MDD). Medical and Biological Engineering and Computing, 56 (2). pp. 233-246.

Mumtaz, W. and Vuong, P.L. and Malik, A.S. and Rashid, R.B.A. (2018) A review on EEG-based methods for screening and diagnosing alcohol use disorder. Cognitive Neurodynamics, 12 (2). pp. 141-156.

Mumtaz, W. and Vuong, P.L. and Xia, L. and Malik, A.S. and Rashid, R.B.A. (2017) An EEG-based machine learning method to screen alcohol use disorder. Cognitive Neurodynamics, 11 (2). pp. 161-171.

Mumtaz, W. and Xia, L. and Ali, S.S.A. and Yasin, M.A.M. and Hussain, M. and Malik, A.S. (2017) Electroencephalogram (EEG)-based computer-aided technique to diagnose major depressive disorder (MDD). Biomedical Signal Processing and Control, 31. pp. 108-115.

Subhani, A.R. and Mumtaz, W. and Saad, M.N.B.M. and Kamel, N. and Malik, A.S. (2017) Machine learning framework for the detection of mental stress at multiple levels. IEEE Access, 5. pp. 13545-13556.

Mumtaz, W. and Xia, L. and Yasin, M.A.M. and Ali, S.S.A. and Malik, A.S. (2017) A wavelet-based technique to predict treatment outcome for Major Depressive Disorder. PLoS ONE, 12 (2).

Bashiri, M. and Mumtaz, W. and Malik, A.S. and Waqar, K. (2016) EEG-based brain connectivity analysis of working memory and attention. In: UNSPECIFIED.

Mumtaz, W. and Malik, A.S. and Ali, S.S.A. and Yasin, M.A.M. and Amin, H. (2015) Detrended fluctuation analysis for major depressive disorder. In: UNSPECIFIED.

Amin, H.U. and Malik, A.S. and Mumtaz, W. and Badruddin, N. and Kamel, N. (2015) Evaluation of passive polarized stereoscopic 3D display for visual & mental fatigues. In: UNSPECIFIED.

Mumtaz, W. and Malik, A.S. and Yasin, M.A.M. and Xia, L. (2015) Review on EEG and ERP predictive biomarkers for major depressive disorder. Biomedical Signal Processing and Control, 22. pp. 85-98.

Khairuddin, H.R. and Malik, A.S. and Mumtaz, W. and Kamel, N. and Xia, L. (2013) Analysis of EEG signals regularity in adults during video game play in 2D and 3D. In: UNSPECIFIED.

Mumtaz, W. and Xia, L. and Malik, A.S. and Mohd Yasin, M.A. (2013) EEG classification of physiological conditions in 2D/3D environments using neural network. In: UNSPECIFIED.