2 citations · 4 across the 6 of their papers we have counts for
5 papers · 1 filter
SeizeIT2: Wearable Dataset Of Patients With Focal Epilepsy
Miguel Bhagubai, Christos Chatzichristos, Lauren Swinnen +10
The increasing technological advancements towards miniaturized physiological measuring devices have enabled continuous monitoring of epileptic patients outside of specialized envir…
Multimodal wearable EEG, EMG and accelerometry measurements improve the accuracy of tonic-clonic seizure detection in-hospital
Jingwei Zhang, Lauren Swinnen, Christos Chatzichristos +23
Objective: Most current wearable tonic-clonic seizure (TCS) detection systems are based on extra-cerebral signals, such as electromyography (EMG) or accelerometry (ACC). Although m…
U-PASS: an Uncertainty-guided deep learning Pipeline for Automated Sleep Staging
Elisabeth R. M. Heremans, Nabeel Seedat, Bertien Buyse +3
As machine learning becomes increasingly prevalent in critical fields such as healthcare, ensuring the safety and reliability of machine learning systems becomes paramount. A key c…
CoRe-Sleep: A Multimodal Fusion Framework for Time Series Robust to Imperfect Modalities
Konstantinos Kontras, Christos Chatzichristos, Huy Phan +2
Sleep abnormalities can have severe health consequences. Automated sleep staging, i.e. labelling the sequence of sleep stages from the patient's physiological recordings, could sim…
Feature matching as improved transfer learning technique for wearable EEG
Elisabeth R. M. Heremans, Huy Phan, Amir H. Ansari +4
Objective: With the rapid rise of wearable sleep monitoring devices with non-conventional electrode configurations, there is a need for automated algorithms that can perform sleep…