Behrad Soleimani, Isabella Dallasta, Proloy Das, Pranjeevan Kulasingham, Sophia Girgenti, Jonathan Z Simon, Behtash Babadi, Elisabeth B Marsh
Journal
Brain Communications , vol. 5(3) , pp. fcad149 · 2023 · Cited by 25
Biosignal ProcessingPhysiological Monitoring and Digital Health
Abstract
Cortical ischaemic strokes result in cognitive deficits depending on the area of the affected brain. However, we have demonstrated that difficulties with attention and processing speed can occur even with small subcortical infarcts. Symptoms appear independent of lesion location, suggesting they arise from generalized disruption of cognitive networks. Longitudinal studies evaluating directional measures of functional connectivity in this population are lacking. We evaluated six patients with minor stroke exhibiting cognitive impairment 6–8 weeks post-infarct and four age-similar controls. Resting-state magnetoencephalography data were collected. Clinical and imaging evaluations of both groups were repeated 6- and 12 months later. Network Localized Granger Causality was used to determine differences in directional connectivity between groups and across visits, which were correlated with clinical …
Mithunjha Anandakumar, Jathurshan Pradeepkumar, Simon L Kappel, Chamira U. S. Edussooriya, Anjula C. De Silva
Conference
SMC 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC) , pp. 514-519 · 2023 · Cited by 9
Machine Learning and Pattern RecognitionBiosignal ProcessingPhysiological Monitoring and Digital Health
Abstract
Sleep plays a crucial role in the well-being of human lives. Traditional sleep studies using Polysomnography are associated with discomfort and often lower sleep quality caused by the acquisition setup. Previous works have focused on developing less obtrusive methods to conduct high-quality sleep studies, and ear- EEG is among popular alternatives. However, the performance of sleep staging based on ear-EEG is still inferior to scalp- EEG based sleep staging. In order to address the performance gap between scalp-EEG and ear- EEG based sleep staging, we propose a cross-modal knowledge distillation strategy 1 † https://github.com/Mithunjha/EarEEG_KnowledgeDistillation, which is a domain adaptation approach. We employ model architectures from the transformer and convolutional neural network families to demonstrate the model-agnostic nature of the method. Our experiments and analysis validate the …