Halima Boutouil presented a poster co-authored by L. Wei, R. Gerbatin, O. Mamad, H. Boutouil, C. Reschke, M. Lowery, D. Henshall, G. Morris and C. Mooney, titled “ XGboost-based Method for Seizure Detection in Mouse Models of Epilepsy ” at the 2020 IEEE Signal Processing in Medicine and Biology Symposium (IEEE-SPMB 2020), the conference of IEEE SPMB held virtually on December 5, 2020.
[pdf-embedder url=”https://lisda.ucd.ie/wp-content/uploads/2020/12/SPMB_poster.pdf”]
Epilepsy is a chronic neurological disease which affects over 50 million people worldwide. EEG monitoring in rodent disease models of epilepsy is critical in the understanding of disease mechanisms and drug development. However, the visual annotation of EEG traces is time-consuming, typically requires experienced experts and is subject to low inter-observer reproducibility. Therefore, automated seizure detection has been proposed recently to help to reduce the time required to annotate EEGs and improve reproducibility. Research on the automatic detection of seizures in mouse EEGs has been limited to date. In this study, we present a TKEO-based and an XGBoost-based method to detect seizures in EEGs from intra-amygdala kainic acid (IAKA) and Dravet syndrome (DS) mouse models of epilepsy. The TKEO-based method mimics how experts typically detect seizures in this type of mouse model of epilepsy and demonstrated 74.4% sensitivity and 97.5% specificity in the IAKA test set; and 25.0% sensitivity and 98.0% specificity in the DS test set. For the XGBoost-based method, one IAKA mouse and one DS mouse were used to train the method. 19 features were selected as the input and Synthetic Minority Over-sampling Technique (SMOTE) was used to balance the dataset. The sensitivity and specificity of the XGBoost-based method were 86.6% and 93.3% in the IAKA test set, and 98.5% and 98.8% in the DS test set. The proposed XGBoost-based method generalized well on two mouse models of epilepsy, and has the potential to assist researchers in the automated analysis of seizures in single-channel mouse EEG.
— Lan