3 citations · 3 across the 1 of their papers we have counts for
5 papers
Machine-Learning-Based Diagnostics of EEG Pathology
Lukas Alexander Wilhelm Gemein, Robin Tibor Schirrmeister, Patryk Chrabąszcz +5
Machine learning (ML) methods have the potential to automate clinical EEG analysis. They can be categorized into feature-based (with handcrafted features), and end-to-end approache…
Cortical Mirror-System Activation During Real-Life Game Playing: An Intracranial Electroencephalography (EEG) Study
Markus Kern, Johanna Ruescher, Andreas Schulze-Bonhage +1
Analogous to the mirror neuron system repeatedly described in monkeys as a possible substrate for imitation learning and/or action understanding, a neuronal execution/observation m…
Cross-paradigm pretraining of convolutional networks improves intracranial EEG decoding
Joos Behncke, Robin Tibor Schirrmeister, Martin Völker +5
When it comes to the classification of brain signals in real-life applications, the training and the prediction data are often described by different distributions. Furthermore, di…
Early Seizure Detection with an Energy-Efficient Convolutional Neural Network on an Implantable Microcontroller
Maria Hügle, Simon Heller, Manuel Watter +6
Implantable, closed-loop devices for automated early detection and stimulation of epileptic seizures are promising treatment options for patients with severe epilepsy that cannot b…
Intracranial Error Detection via Deep Learning
Martin Völker, Jiří Hammer, Robin T. Schirrmeister +6
Deep learning techniques have revolutionized the field of machine learning and were recently successfully applied to various classification problems in noninvasive electroencephalo…