What question did this study set out to answer?

The study aims to explore EEG biomarkers associated with generalised seizures in paediatric populations.

February 19, 2026Annals of Neurosciences1 citationsOpen Access

Quantitative Electroencephalographic (qEEG) Characterisation and Biomarker Identification of Generalised Paediatric Seizure Using Spectral Features

AKAnnu KumariIndian Institute of Technology Roorkee KJKamlesh JhaAll India Institute of Medical Sciences Raipur TKTribhuwan KumarAll India Institute of Medical Sciences Raipur

Key Points

The study aims to explore EEG biomarkers associated with generalised seizures in paediatric populations.
Recruitment of 66 subjects aged 2–15 years with generalised seizures and matched healthy controls.
Recording of EEG readings using a 32-channel setup alongside demographic data.
Extraction of quantitative spectral features using Fast Fourier Transform (FFT) in MATLAB.
Higher alpha power in seizure subjects compared to controls in both hemispheres.
Lower beta power noted in the left hemisphere of seizure subjects.
Significant asymmetries in theta and delta across cortical regions, particularly in the temporal region.

Abstract

Background Epilepsy possesses significant long-term health sequelae and potential morbidity among children globally. A diagnosis of seizures can often be challenging in the paediatric population owing to seizure mimics and absence of classical features in clinical as well as electroencephalographic (EEG) presentations. Purpose The objective of the study is to explore potential EEG biomarkers using quantitative analysis of conventional EEG records of subjects with seizure in paediatric populations. Method 66 subjects with generalised seizures in the age group of 2–15 years had been recruited along with an equal number of age-matched healthy control subjects. Readings obtained from a 32-channel EEG were recorded along with the demographic details of the subjects. Using the Fast Fourier Transform (FFT) in the MATLAB environment, quantitative spectral features were extracted and compared between the groups and within the group to explore EEG markers related to the generalised seizures in the study population. Results The case group showed significantly higher alpha power in both left (17.86 vs 15.06 µV 2 /Hz) and right (20.76 vs 16.12 µV 2 /Hz) hemispheres compared to the controls. The case group had lower beta power in the left hemisphere (33.34 vs 35.52 µV 2 /Hz) but no difference in the right hemisphere. Significant asymmetries were observed across all cortical regions, including the temporal region showing the highest theta and delta asymmetry (asymmetry indices of −0.142 for both), whereas alpha asymmetry was highest in the occipitotemporal regions (asymmetry indices −0.125 and −0.141, respectively). Conclusion The study reveals a complex pattern of characteristic quantitative electroencephalographic (qEEG) alterations in the paediatric seizure population suggestive of significant neurophysiological implications, including alterations in arousal, attention and inhibitory control mechanisms and the features may be of some value in objective seizure assessment using EEG.

اسأل الذكاء الاصطناعي

Bookmark

View Full Paper