@inproceedings{bae2a6a679ba49939ce40de56dae40cf,
title = "EEG-Based Methods to Characterize Memorised Visual Space",
abstract = "One second of memory maintenance was evaluated to determine EEG metrics ability to track memory load and its variations connected with the lateral presentation of objects in the visual hemi-field. An initial approach focused on features gathered from the N2pc time series to detect the memory load using ensemble learners. Conversely, the secondary approach employed a regularised support vector classifier to predict the area of N2pc event-related components, identifying 6 levels of memory load and stimulus location.",
keywords = "Memory load, Retention period, Visual working memory",
author = "Mauro Nascimben and {Zo{\"e}ga Rams{\o}y}, Thomas and Bruni, {Luis Emilio}",
note = "Funding Information: This project has received funding from the European Union{\textquoteright}s Horizon 2020 research and innovation programme under the Marie Sk lodowska-Curie Grant Agreement No 813234. Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG. ; 22nd International Conference on Human-Computer Interaction, HCII 2020 ; Conference date: 19-07-2020 Through 24-07-2020",
year = "2020",
doi = "10.1007/978-3-030-50726-8_72",
language = "English",
isbn = "978-3-030-50725-1",
series = "Communications in Computer and Information Science",
publisher = "Springer",
pages = "549--556",
editor = "Constantine Stephanidis and Margherita Antona",
booktitle = "HCI International 2020 - Posters",
address = "Germany",
}