BRAIN EPILEPTIC SEIZURE DETECTION USING DEEP LEARNING

Registration ID: IJNRD_218475

Published ID: IJNRD2404403

DOI: Click Here to Get

Mekala M , Mrs. Anitha V , Asma Begam M , Dharshini G

Convolutional Neural Networks(CNNs),Artificial Neural Networks(ANNs),Recurrent Neural Networks(RNNs)

Epilepsy is a chronic condition characterized by recurring, spontaneous seizures. If a person has two or more unprovoked seizures, they are diagnosed with epilepsy. Epilepsy seizures can be caused by a brain damage or a genetic predisposition, although the reason is often unknown. Overcoming the difficulty of accurately describing seizure occurrences in a broad and heterogeneous population of patients is thus a critical step toward clinical applicability. As a result of significant patient inter-variability in epileptic diseases, present technologies have difficulty generalizing to unseen patients, and they frequently need to be fine-tuned to each patient. Several approaches have been developed to detect and forecast seizure events from EEG of epileptic patients collected mostly during short in- hospital monitoring with standard scalp-EEG or intracerebral electrodes, thanks to the rise of Deep Learning (DL) in the biomedical sector. Though some methods reported outstanding results, the majority used offline analysis with extensive pre- processing and manipulation of the EEG data, which is incompatible with the goal of online, long-term, low-power ambulatory operations. The difficulties in accurately detecting automated epileptic seizures with DL and EEG modalities are explored. The benefits and drawbacks of using DL-based approaches to diagnose epileptic seizures are discussed. Finally, the most promising DL models are proposed, as well as potential future research on automated epileptic seizure detection.

Published Paper   E-Certificate

Mekala M, Mrs. Anitha V, Asma Begam M, & Dharshini G (April-2024). BRAIN EPILEPTIC SEIZURE DETECTION USING DEEP LEARNING. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), e10-e15. https://ijnrd.org/papers/IJNRD2404403.pdf

Volume 9 Issue 4, April-2024

Pages : e10-e15

Paper Reg. ID: IJNRD_218475

Published Paper Id: IJNRD2404403

Downloads: 000121975

Research Area: Computer Engineering 

Country: Salem, Tamil Nadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404403.pdf

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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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