TY - CHAP
T1 - ONLINE DETECTION OF SCALP-INVISIBLE MESIAL-TEMPORAL BRAIN INTERICTAL EPILEPTIFORM DISCHARGES FROM EEG
AU - Abdi-Sargezeh, Bahman
AU - Valentin, Antonio
AU - Alarcon, Gonzalo
AU - Sanei, Saeid
N1 - Publisher Copyright:
© 2022 IEEE
PY - 2022
Y1 - 2022
N2 - Brain interictal epileptiform discharges (IEDs) are transient events occurring between two or before seizure onsets. The IEDs are captured mainly by the intracranial EEG (iEEG) and only 4.7% of them are visible in our scalp EEG (sEEG) dataset. Here, we propose a method namely temporal components analysis (TCA) to detect the IEDs from ongoing sEEG and iEEG signals recorded simultaneously. In addition, spatial components analysis (SCA) previously proposed by ourselves is employed to detect the IEDs. Finally, both TCA and SCA are combined to boost the IED detection system performance. This method is referred as to TCA-SCA. The proposed TCA-SCA method detects the IEDs from the iEEG and sEEG by 81.2% and 37.4% sensitivity, respectively. The findings show that our proposed method enables the detection of scalp-invisible IEDs from ongoing sEEG recordings.
AB - Brain interictal epileptiform discharges (IEDs) are transient events occurring between two or before seizure onsets. The IEDs are captured mainly by the intracranial EEG (iEEG) and only 4.7% of them are visible in our scalp EEG (sEEG) dataset. Here, we propose a method namely temporal components analysis (TCA) to detect the IEDs from ongoing sEEG and iEEG signals recorded simultaneously. In addition, spatial components analysis (SCA) previously proposed by ourselves is employed to detect the IEDs. Finally, both TCA and SCA are combined to boost the IED detection system performance. This method is referred as to TCA-SCA. The proposed TCA-SCA method detects the IEDs from the iEEG and sEEG by 81.2% and 37.4% sensitivity, respectively. The findings show that our proposed method enables the detection of scalp-invisible IEDs from ongoing sEEG recordings.
KW - EEG
KW - IED detection
KW - interictal epileptiform discharges
KW - tensor decomposition
UR - http://www.scopus.com/inward/record.url?scp=85131254120&partnerID=8YFLogxK
U2 - 10.1109/ICASSP43922.2022.9746807
DO - 10.1109/ICASSP43922.2022.9746807
M3 - Conference paper
AN - SCOPUS:85131254120
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 1416
EP - 1420
BT - 2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022
Y2 - 23 May 2022 through 27 May 2022
ER -