Evidence map›Paper›PMID 41717633›Full record

ArticleAnnals of neurosciences2026

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

Arundhati Kumari, Kamlesh Jha, Tribhuwan Kumar, Lokesh Tiwari, Rakesh Ranjan, Purushottam Kumar

Abstract read
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Article in Annals of neurosciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Arundhati KumariDepartment of Physiology, AIIMS Patna, Bihar, India.
Kamlesh JhaDepartment of Physiology, AIIMS Patna, Bihar, India.ORCID https://orcid.org/0000-0003-0525-9444
Tribhuwan KumarDepartment of Physiology, AIIMS Patna, Bihar, India.
Lokesh TiwariDepartment of Pediatrics, AIIMS Patna, Bihar, India.ORCID https://orcid.org/0000-0002-2231-0152
Rakesh RanjanDepartment of Electronics and Communication Engineering, National Institute of Technology Patna, Bihar, India.
Purushottam KumarDepartment of Community and Family Medicine, AIIMS Patna, Bihar, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 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.

Indexed as

asymmetry indexepilepsypaediatric seizure disorderpower spectral density (PSD)qEEG

Identifiers

PMID41717633
PMCPMC12913032

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