AUTHOR=Xu Minghao , Li Xiaoxuan , Fu Yifan , Hu Dinghan , Zhang Yang , Wei Wang , Gao Yaotian , Lin Keyi , Yang Bin , Cao Jiuwen , Jiang Tao 

TITLE=Study on brain functional networks and wearable device monitoring in children with SeLECTs and high spike-wave index (SWI >50%)

JOURNAL=Frontiers in Neurology

VOLUME=Volume 16 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2025.1571330

DOI=10.3389/fneur.2025.1571330

ISSN=1664-2295

ABSTRACT=IntroductionSelf-limited epilepsy with centrotemporal spikes (SeLECTs) represents a common idiopathic focal epilepsy syndrome in childhood. Although most patients demonstrate a favorable prognosis, some patients develop ESES. ESES is associated with poorer neuropsychological prognosis. This association challenges the “benign” classification of SeLECTs. Currently, the diagnostic threshold for ESES remains controversial. Moreover, traditional long-term video-EEG monitoring presents certain limitations.MethodsThe research utilizes the “Biovital-P1” software integrated with Oppo smart bands to collect multimodal physiological signals. Simultaneously, a 21-channel digital EEG system acquires electroencephalographic data. The study constructs brain networks through DTF analysis. Additionally, it performs preprocessing and feature extraction on multimodal physiological signals (ACC, EDA, PPG).ResultsThe results demonstrate strong functional connectivity in the centrotemporal region in all frequency bands and the delta band. However, as SWI levels increase, the brain network's global and local efficiency significantly reduces. Analyzing multimodal physiological signals reveals statistically significant differences in ACC and PPG signal time-domain features (Maximum, Minimum, Peak) among different SWI groups. Multiple characteristic parameters of EDA signals also show significant intergroup differences. Notably, EDA signals exhibit excellent sensitivity in reflecting stress responses of the autonomic nervous system. The characteristic features of EDA signals demonstrate a significant negative correlation with SWI levels.