Quantifying Intra- and Inter-subject Variability for EEG-based Sensorimotor Brain Computer Interface (Open)
Brain Computer Interface (BCI), as an unorthodox communication pathway between the brain and the computer, offers an extended degree of freedom that can potentially rehabilitate impaired motor functionality. Sensorimotor rhythm (SMR)-based BCI systems are being investigated for restoring impaired motor functions. As a noninvasive signal acquisition modality, electroencephalography (EEG) records the electrical activity of the brain with a set of electrodes placed on the scalp. Understanding the underlying neurophysiology associated with SMR-related brain activities plays a critical role in the design of a BCI system. In particular, the SMR-related neurophysiology manifested in EEG varies across subjects and over time. Subject- and session-specific training is usually required for BCI to perform efficiently while compensating inherent inter-subject and inter-session variabilities. This project aims at scrutinizing the SMR-related EEG dynamics to understand the role of inter-subject and inter-session variabilities on BCI performance.
Collaborators
1. Associate Professor Mathias Baumert (The University of Adelaide, Australia)
2. Professor Leontios J. Hadjileontiadis (Khalifa University, Abu Dhabi, UAE)
3. Associate Professor Ahsan Khandoker (Khalifa University, Abu Dhabi, UAE)
Selected Publications
1. S. Saha, K. A. Mamun, K. Ahmed, R. Mostafa, G. R. Naik, A. H. Khandoker, S. Darvishi, and M. Baumert, "Progress in brain computer interface: challenges and opportunities", Frontiers in Systems Neuroscience, vol. 15, 2021. (doi: 10.3389/fnsys.2021.578875)
2. S. Saha and M. Baumert, "Intra- and Inter-subject Variability in EEG-Based Sensorimotor Brain Computer Interface: A Review", Frontiers in Computational Neuroscience, vol. 13, 2020. (doi: 10.3389/fncom.2019.00087).
3. S. Saha, M.S. Hossain, K. Ahmed, R. Mostafa, L. Hadjileontiadis, A. Khandoker and M. Baumert, "Wavelet Entropy-Based Inter-subject Associative Cortical Source Localization for Sensorimotor BCI", Frontiers in Neuroinformatics, vol. 13, 2019. (doi: 10.3389/fninf.2019.00047).
4. S. Saha, K. Ahmed, R. Mostafa, L. Hadjileontiadis and A. Khandoker, "Evidence of Variabilities in EEG Dynamics During Motor Imagery-Based Multiclass Brain–Computer Interface," IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 26, no. 2, pp. 371-382, Feb. 2018. (doi: 10.1109/TNSRE.2017.2778178)
5. S. Saha, K. Ahmed, R. Mostafa, A. Khandoker and L. Hadjileontiadis, "Enhanced inter-subject brain computer interface with associative sensorimotor oscillations", Healthcare Technology Letters, vol. 4, no. 1, pp. 39-43, 2017. (doi: 10.1049/htl.2016.0073)
Computer-guided Ablation Techniques for Atrial Fibrillation (Closed)
Multiple variables including bipolar lead orientation as relative to the wave propagation vector, inter-electrode spacing, electrode size, and tissue contact, impact bipolar EGM and EGM-derived measures. Both inter-electrode spacing and electrode size are predefined during catheter design. Tissue contact relies on the accuracy of placing electrodes during signal acquisition although it is an onerous task to maintain stable electrode placement in the presence of continuous blood flow and contraction of the heart muscles. Once EGMs are already recorded using a catheter with certain specifications, the only variable that could be integrated into a mapping tool is the bipolar lead orientation. This project aims at quantifying the impact of bipolar lead orientation in intracardiac EGM from a signal processing perspective. As a secondary objective, the preprocessing (filtering) techniques are further to be investigated.
Collaborators
1. Associate Professor Mathias Baumert (The University of Adelaide, Australia)
2. Professor Prashanthan Sanders (The University of Adelaide, Australia)
3. Associate Professor Dominik Linz (The University of Adelaide, Australia)
Selected Publications
1. S. Saha, D. Linz, P. Sanders and M. Baumert, "Beamforming-inspired Spatial Filtering Technique for Intracardiac Electrograms," 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Berlin, Germany, 2019, pp. 4254-4257. (doi: 10.1109/EMBC.2019.8857194)
2. S. Saha, S. Hartmann, D. Linz, P. Sanders and M. Baumert, "A Ventricular Far-Field Artefact Filtering Technique for Atrial Electrograms," 2019 Computing in Cardiology (CinC), Singapore, Singapore, 2019, pp. Page 1-Page 4. (doi: 10.23919/CinC49843.2019.9005813)
3. D. Linz, S. Saha, R. Kutieleh, K. Kadhim, D. Lau, M. Baumert, and P. Sanders, “Impact of bipolar vector orientation and inter-electrode spacing on electrograms during human atrial fibrillation,” European Heart Journal, 2019, 40 (Supplement 1), pp.ehz748-1153. (doi: 10.1093/eurheartj/ehz748.1153)
ECG-PPG Based Health Monitoring for Depressed Patients with Suicidal Ideation (Closed)
Major Depressive Disorder (MDD) is a serious mental problem, often causes suicidal ideation in human subjects. The neurophysiological phenomena that foster depression in mass population are still ill-defined. However, recent research links depression as well as suicidal ideation with arterial stiffness, evident from electrocardiogram (ECG) and photo-plethysmogram (PPG) recordings.
Collaborators
1. Associate Professor Ahsan Khandoker (Khalifa University, UAE)
2. Dr. Veena Luthra (American Center for Psychiatry and Neurology, Abu Dhabi)
3. Dr. Yousef Abou Allaban (American Center for Psychiatry and Neurology, Abu Dhabi, UAE)
Selected Publications
1. Khandoker, V. Luthra, Y. Abouallaban, S. Saha, K. Ahmed, R. Mostafa, N. Chowdhury and H. Jelinek, "Suicidal Ideation Is Associated with Altered Variability of Fingertip Photo-Plethysmogram Signal in Depressed Patients", Frontiers in Physiology, vol. 8, p. 501, 2017. (doi: 10.3389/fphys.2017.00501)
2. Khandoker, V. Luthra, Y. Abouallaban, S. Saha, K. Ahmed, R. Mostafa, N. Chowdhury and H. Jelinek, "Predicting depressed patients with suicidal ideation from ECG recordings", Medical & Biological Engineering & Computing, vol. 55, no. 5, pp. 793-805, 2016. (doi: 10.1007/s11517-016-1557-y)