Publication Details
Modular Framework for Detection of Inter-ictal Spikes in iEEG
Sekanina Lukáš, prof. Ing., Ph.D. (DCSY FIT BUT)
Brázdil Milan, MUDr., Ph.D. (NK-LF MUNI)
Detectors, Electroencephalography, Epilepsy, Feature extraction, Indexes, Sensitivity, Standards
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.
@INPROCEEDINGS{FITPUB11333,
author = "Filip Ke\v{s}ner and Luk\'{a}\v{s} Sekanina and Milan Br\'{a}zdil",
title = "Modular Framework for Detection of Inter-ictal Spikes in iEEG",
pages = "418--421",
booktitle = "The 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'17)",
year = 2017,
location = "Los Alamos, US",
publisher = "Institute of Electrical and Electronics Engineers",
ISBN = "978-1-5090-2809-2",
doi = "10.1109/EMBC.2017.8036851",
language = "english",
url = "https://www.fit.vut.cz/research/publication/11333"
}