Automated EEG analysis of epilepsy: A review

By Usha R. Acharya, Subbhuraam Vinitha Sree, G. Swapna, Roshan Joy Martis, Jasjit S. Suri. Knowledge-Based Systems, 2013

816 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Signal Processing

View Paper: https://www.semanticscholar.org/paper/947d36d93d8f9c9a466d9e30d76126e2ae1452b2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. Fathi E. Abd El-Samie
2. Saleh A. Alshebeili
3. Adeel Razi
4. Alexandre Gramfort
5. Ishtiaq Ahmad
6. Tiago H. Falk
7. Turky Nayef Alotaiby

In Signal Processing

1. Junaid Qadir
2. Alexandre Gramfort
3. Tiago H. Falk

Citations in the corpus

• EEG seizure detection and prediction algorithms: a survey (2014, background): “Several studies have been conducted on EEG seizure detection [3,4].”
• Machine Learning for Predicting Epileptic Seizures Using EEG Signals: A Review (2020, background): “[6] 2013 EEG signals for epilepsy √ √ √ × × √”
• Deep learning-based electroencephalography analysis: a systematic review (2019, background): “For example, in clinical settings, EEG is often used to study sleep patterns [1] or epilepsy [3].”
• Review on Fundamental of Electroencephalography and Detection Techniques in Substance and Behavioral Addiction (2025, unknown): “Substance abuse occurs when the substance used affects the central and peripheral nervous systems, causing abnormalities in their functioning, which can be noticed in their behavior and brain-related biosignals, such as EEG (15).”