Integrated EEG Signal Fusion for Advanced Epileptic Seizure Analysis

B. Karthik Raja, K. Nirmal Richard, A. Balachandar, D. Raghu Raman, A. Usharani, P. Manju Bala

2025

Abstract

Epileptic seizures can result in substantial harm to the brain, which can lead to cognitive decline and memory loss. Reducing the severity of seizures is largely dependent on early identification. Currently, the doctors visually inspect EEG signals in order to diagnose seizure activity, which can be time-consuming and difficult. In order to automatically monitor and detect seizures through the brain's bio-signals, we propose a new method: simplistic convolutional neural network-long short-term memory model (1DCNN-LSTM). First, the unprocessed EEG dataset is pre-treatment and normalized, and we extract the sequence of features by a 1D CNN, and pass them to the LSTM layer. The temporal features are supplied to a few fully connected layers for final seizure recognition. Using data from UCI epileptic seizure detection dataset, the suggested model was assessed. In terms of recognition accuracy, the results are excellent: 82.00% for five-class seizure recognition and 99.39% for binary seizure recognition. The attribution of accuracy is considerably above that of classical machine learning methods and outshines other deep learning models widely recognized as competitors.

Paper Citation

in Harvard Style

Karthik Raja B., Nirmal Richard K., Balachandar A., Raghu Raman D., Usharani A. and Manju Bala P. (2025). Integrated EEG Signal Fusion for Advanced Epileptic Seizure Analysis. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 449-456. DOI: 10.5220/0013594500004664

in Bibtex Style

@conference{incoft25,
author={B. Karthik Raja and K. Nirmal Richard and A. Balachandar and D. Raghu Raman and A. Usharani and P. Manju Bala},
title={Integrated EEG Signal Fusion for Advanced Epileptic Seizure Analysis},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT},
year={2025},
pages={449-456},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013594500004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT
TI - Integrated EEG Signal Fusion for Advanced Epileptic Seizure Analysis
SN - 978-989-758-763-4
AU - Karthik Raja B.
AU - Nirmal Richard K.
AU - Balachandar A.
AU - Raghu Raman D.
AU - Usharani A.
AU - Manju Bala P.
PY - 2025
SP - 449
EP - 456
DO - 10.5220/0013594500004664
PB - SciTePress