@inbook{1fc3de7182764f8693bbcc12c9a5135d,
title = "On sound-based interpretation of neonatal EEG",
abstract = "Significant training is required to visually interpret neonatal EEG signals. This study explores alternative sound-based methods for EEG interpretation which are designed to allow for intuitive and quick differentiation between healthy background activity and abnormal activity such as seizures. A novel method based on frequency and amplitude modulation (FM/AM) is presented. The algorithm is tuned to facilitate the audio domain perception of rhythmic activity which is specific to neonatal seizures. The method is compared with the previously developed phase vocoder algorithm for different time compressing factors. A survey is conducted amongst a cohort of non-EEG experts to quantitatively and qualitatively examine the performance of sound-based methods in comparison with the visual interpretation. It is shown that both sonification methods perform similarly well, with a smaller inter-observer variability in comparison with visual. A post-survey analysis of results is performed by examining the sensitivity of the ear to frequency evolution in audio.",
keywords = "amplitude modulation, EEG sonification, frequency modulation, neonatal seizure detection, phase vocoder",
author = "S. Gomez and M. Orsullivan and E. Popovici and S. Mathieson and G. Boylan and A. Temko",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 29th Irish Signals and Systems Conference, ISSC 2018 ; Conference date: 21-06-2018 Through 22-06-2018",
year = "2018",
month = dec,
day = "20",
doi = "10.1109/ISSC.2018.8585349",
language = "English",
series = "29th Irish Signals and Systems Conference, ISSC 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "29th Irish Signals and Systems Conference, ISSC 2018",
address = "United States",
}