Neural synergy in compact biomedical IoT devices: spintronic pathways for MEG-EEG integration and portability
dc.contributor.advisor | Fadlullah, Zubair | |
dc.contributor.advisor | Fouda, Mostafa | |
dc.contributor.author | Elshafei, Mohamed | |
dc.date.accessioned | 2023-10-11T18:40:37Z | |
dc.date.available | 2023-10-11T18:40:37Z | |
dc.date.created | 2023 | |
dc.date.issued | 2023 | |
dc.identifier.uri | https://knowledgecommons.lakeheadu.ca/handle/2453/5255 | |
dc.description.abstract | The human brain, a marvel of nature, consists of intricate neural networks that have fascinated and perplexed the scientific community for generations. As scientists and researchers globally endeavour to unravel the mysteries of bioelectrical activities that form the basis of our cognitive functions and experiences, our research emerges at the nexus of biology and cutting-edge technology. Specifically, we spotlight the remarkable capabilities of magnetoencephalography (MEG) and electroencephalography (EEG). These potent neuroimaging tools, celebrated for their unparalleled spatial and temporal precision, are synergistically combined in our study. We aim to map MEG innovatively signals onto their EEG replicas, employing avant-garde spintronic devices, with a particular emphasis on Magnetic Tunnel Junctions (MTJ). [...] | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Magnetoencephalography | en_US |
dc.subject | Electroencephalography | en_US |
dc.subject | Magnetic tunnel junctions | en_US |
dc.subject | BiLSTM model | en_US |
dc.subject | Neuroimaging devices | en_US |
dc.subject | Artificial intelligence (MEG/EEG mapping) | en_US |
dc.title | Neural synergy in compact biomedical IoT devices: spintronic pathways for MEG-EEG integration and portability | en_US |
dc.type | Thesis | en_US |
etd.degree.name | Master of Science | en_US |
etd.degree.level | Master | en_US |
etd.degree.discipline | Computer Science | en_US |
etd.degree.grantor | Lakehead University | en_US |