MULTIMODAL DATA MINING INFRASTRUCTURE
in Support of
PERSONAL HEALTHCARE SOLUTIONS at HOME
Objective Entropy-based approaches to understanding the temporal dynamics of complexity have revealed novel insights into various brain activities. Herein, electroencephalogram complexity before migraine attacks was examined using an inherent fuzzy entropy approach, allowing the development of an electroencephalogram-based classification model to recognize the difference between interictal and preictal phases.
Cephalalgia 2017 [full article]
Forehead EEG in support of future feasible personal healthcare solutions at home
It is evident that frontal EEG activity is critically involved in sleep management, headache prevention, and depression treatment. The use of dry electrodes on the forehead allows for easy and rapid monitoring on an everyday basis. The advances in EEG recording and analysis ensure a promising future in support of personal healthcare solutions.
IEEE 2017 [full article]
Resting-state EEG power and coherence vary between migraine phases
Migraine is characterized by a series of phases (inter-ictal, pre-ictal, ictal, and post-ictal). It is of great interest whether resting-state electroencephalography (EEG) is differentiable between these phases. We compared resting-state EEG energy intensity and effective connectivity in different migraine phases using EEG power and coherence analyses in patients with migraine without aura as compared with healthy controls (HCs). Inter-ictal and ictal patients had decreased EEG power and coherence relative to HCs, which were “normalized” in the pre-ictal or post-ictal groups.
Journal of Headache and Pain 2016 [full article]