Application of Higuchi's fractal dimension from basic to clinical neurophysiology: a review
S Kesić, SZ Spasić - Computer methods and programs in biomedicine, 2016 - Elsevier
Background and objective For more than 20 years, Higuchi's fractal dimension (HFD), as a
nonlinear method, has occupied an important place in the analysis of biological signals. The …
nonlinear method, has occupied an important place in the analysis of biological signals. The …
[HTML][HTML] Computer-assisted analysis of routine EEG to identify hidden biomarkers of epilepsy: A systematic review
Background Computational analysis of routine electroencephalogram (rEEG) could improve
the accuracy of epilepsy diagnosis. We aim to systematically assess the diagnostic …
the accuracy of epilepsy diagnosis. We aim to systematically assess the diagnostic …
PyEEG: an open source python module for EEG/MEG feature extraction
FS Bao, X Liu, C Zhang - Computational intelligence and …, 2011 - Wiley Online Library
Computer‐aided diagnosis of neural diseases from EEG signals (or other physiological
signals that can be treated as time series, eg, MEG) is an emerging field that has gained …
signals that can be treated as time series, eg, MEG) is an emerging field that has gained …
Two-stream attention 3-D deep network-based childhood epilepsy syndrome classification
Epilepsy syndromes are typical childhood nervous system diseases, usually containing
several different seizure types commonly seen. There exist around 20 known childhood …
several different seizure types commonly seen. There exist around 20 known childhood …
A dynamic filtering DF-RNN deep-learning-based approach for EEG-based neurological disorders diagnosis
Filtering of unwanted signals has a great impact on the performance of EEG signal
processing applied to neurological disorders diagnosis. It is so difficult to remove …
processing applied to neurological disorders diagnosis. It is so difficult to remove …
[LIVRE][B] Epilepsy: the intersection of neurosciences, biology, mathematics, engineering, and physics
I Osorio, HP Zaveri, MG Frei, S Arthurs - 2016 - books.google.com
Integrating the studies of epilepsy, neurosciences, computational neurosciences,
mathematics, physics, engineering, and medicine, this volume provides the first means to a …
mathematics, physics, engineering, and medicine, this volume provides the first means to a …
Classification of the epileptic seizure onset zone based on partial annotation
Epilepsy is a chronic disorder caused by excessive electrical discharges. Currently, clinical
experts identify the seizure onset zone (SOZ) channel through visual judgment based on …
experts identify the seizure onset zone (SOZ) channel through visual judgment based on …
3D residual-attention-deep-network-based childhood epilepsy syndrome classification
Interictal electroencephalograms (EEGs) usually contain important information for epilepsy
analysis and diagnosis. However, the focus of existing research has mainly been on …
analysis and diagnosis. However, the focus of existing research has mainly been on …
Transfer learning for the identification of paediatric EEGs with interictal epileptiform abnormalities
EEG is a test that helps in the clinical diagnosis of epilepsy. Epilepsy diagnosis is facilitated
by establishing the presence of interictal epileptiform abnormalities on EEG, which predict …
by establishing the presence of interictal epileptiform abnormalities on EEG, which predict …
Interval analysis of interictal EEG: pathology of the alpha rhythm in focal epilepsy
J Pyrzowski, M Siemiński, A Sarnowska… - Scientific reports, 2015 - nature.com
The contemporary use of interictal scalp electroencephalography (EEG) in the context of
focal epilepsy workup relies on the visual identification of interictal epileptiform discharges …
focal epilepsy workup relies on the visual identification of interictal epileptiform discharges …