A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf
.
Automatic seizure detection based on imaged-EEG signals through fully convolutional networks
2020
Scientific Reports
AbstractSeizure detection is a routine process in epilepsy units requiring manual intervention of well-trained specialists. This process could be extensive, inefficient and time-consuming, especially for long term recordings. We proposed an automatic method to detect epileptic seizures using an imaged-EEG representation of brain signals. To accomplish this, we analyzed EEG signals from two different datasets: the CHB-MIT Scalp EEG database and the EPILEPSIAE project that includes scalp and
doi:10.1038/s41598-020-78784-3
pmid:33311533
fatcat:tgigm3ldybfs7k4akigcow6zge