Detail výsledku
Modular Framework for Detection of Inter-ictal Spikes in iEEG
In this paper, we present a new modular approach for detection of inter-ictal spikes in intracranial iEEG recordings from patients that are suffering from pharmaco-resistant form of epilepsy. This new approach is presented in the form of a detection framework consisting of three primary modules: first level detector, second level feature extractor, and third level detection classifier, where each module is responsible for a specific functionality. This detection framework can be perceived as a three slot system, where modules can be easily plugged in their slots and replaced by a different module or implementation on demand, in order to adapt the quality of detection (measured in terms of sensitivity, precision or inter-recording adaptability) and computational cost. Using complex real-world data sets it was confirmed that the proposed framework provides highly sensitive and precise detection, while it also significantly reduces the computation time.
Detectors, Electroencephalography, Epilepsy, Feature extraction, Indexes, Sensitivity, Standards
@inproceedings{BUT144409,
author="Filip {Kešner} and Lukáš {Sekanina} and {}",
title="Modular Framework for Detection of Inter-ictal Spikes in iEEG",
booktitle="The 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'17)",
year="2017",
pages="418--421",
publisher="Institute of Electrical and Electronics Engineers",
address="Los Alamos",
doi="10.1109/EMBC.2017.8036851",
isbn="978-1-5090-2809-2",
url="https://www.fit.vut.cz/research/publication/11333/"
}