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In this study, we developed and tested machine learning models to predict epilepsy surgical outcome using noninvasive clinical and demographic data from patients. Methods: Seven dif-ferent categorization algorithms were used to analyze the…

We present the implementation of seizure detection algorithms based on a minimal number of EEG channels on a parallel ultra-low-power embedded platform. The analyses are based on the CHB-MIT dataset, and include explorations of different…

Controlling the surrounding world and predicting future events has always seemed like a dream, but that could become a reality using a Brain-Computer/Machine Interface (BCI/BMI). Epilepsy is a group of neurological diseases characterized by…

Signal Processing · Electrical Eng. & Systems 2019-06-10 Zaghloul Saad Zaghloul , Magdy Bayoumi

The Epilepsies are a common, chronic neurological disorder affecting more than 50 million individuals across the globe. It is characterized by unprovoked, recurring (similar or different type) seizures which are commonly diagnosed through…

Signal Processing · Electrical Eng. & Systems 2021-08-03 Palak Handa , Monika Mathur , Nidhi Goel

Epilepsy is a well-known neuronal disorder that can be identified by interpretation of the electroencephalogram (EEG) signal. Usually, the length of an EEG signal is quite long which is challenging to interpret manually. In this work, we…

Machine Learning · Computer Science 2019-03-07 Md Mursalin , Syed Shamsul Islam , Md Kislu Noman , Adel Ali Al-Jumaily

This paper introduces an innovative framework designed for progressive (granular in time to onset) prediction of seizures through the utilization of a Deep Learning (DL) methodology based on non-invasive multi-modal sensor networks.…

Signal Processing · Electrical Eng. & Systems 2024-11-05 Ali Saeizadeh , Douglas Schonholtz , Joseph S. Neimat , Pedram Johari , Tommaso Melodia

Reliable seizure detection is critical for diagnosing and managing epilepsy, yet clinical workflows remain dependent on time-consuming manual EEG interpretation. While machine learning has shown promise, existing approaches often rely on…

Machine Learning · Computer Science 2025-08-12 Bartlomiej Chybowski , Shima Abdullateef , Hollan Haule , Alfredo Gonzalez-Sulser , Javier Escudero

Epilepsy is a highly prevalent brain condition with many serious complications arising from it. The majority of patients which present to a clinic and undergo electroencephalogram (EEG) monitoring would be unlikely to experience seizures…

Signal Processing · Electrical Eng. & Systems 2023-12-14 Matthew McDougall , Hezam Albaqami , Ghulam Mubashar Hassan , Amitava Datta

Epilepsy is one of the most occurring neurological disease globally emerged back in 4000 BC. It is affecting around 50 million people of all ages these days. The trait of this disease is recurrent seizures. In the past few decades, the…

Machine Learning · Computer Science 2021-11-08 Virender Ranga , Shivam Gupta , Jyoti Meena , Priyansh Agrawal

Epilepsy is a prevalent neurological disorder globally, impacting around 50 million people \cite{WHO_epilepsy_50million}. Epileptic seizures result from sudden abnormal electrical activity in the brain, which can be read as sudden and…

Machine Learning · Computer Science 2025-08-15 Mohammed Guhdar , Ramadhan J. Mstafa , Abdulhakeem O. Mohammed

The diagnosis of epilepsy generally includes a visual inspection of EEG recorded data by the Neurologist, with the purpose of checking the occurrence of transient waveforms called interictal epileptiform discharges. These waveforms have…

Computer Vision and Pattern Recognition · Computer Science 2016-06-08 Andre Rosado , Agostinho C Rosa

Wearable and unobtrusive monitoring and prediction of epileptic seizures has the potential to significantly increase the life quality of patients, but is still an unreached goal due to challenges of real-time detection and wearable devices…

Neural and Evolutionary Computing · Computer Science 2022-01-25 Una Pale , Tomas Teijeiro , David Atienza

Developing a Brain-Computer Interface~(BCI) for seizure prediction can help epileptic patients have a better quality of life. However, there are many difficulties and challenges in developing such a system as a real-life support for…

Machine Learning · Computer Science 2017-02-20 Mohammad-Parsa Hosseini , Hamid Soltanian-Zadeh , Kost Elisevich , Dario Pompili

In clinical practice, electroencephalography (EEG) plays an important role in the diagnosis of epilepsy. EEG-based computer-aided diagnosis of epilepsy can greatly improve the ac-curacy of epilepsy detection while reducing the workload of…

Signal Processing · Electrical Eng. & Systems 2026-03-24 Andong Li , Zhaohong Deng , Qiongdan Lou

Identifying epileptic seizures through analysis of the electroencephalography (EEG) signal becomes a standard method for the diagnosis of epilepsy. Manual seizure identification on EEG by trained neurologists is time-consuming,…

Machine Learning · Computer Science 2019-06-07 X. Yao , X. Li , Q. Ye , Y. Huang , Q. Cheng , G. -Q. Zhang

Epilepsy is one of the most common neurological disorders, affecting about 1% of the population at all ages. Detecting the development of epilepsy, i.e., epileptogenesis (EPG), before any seizures occur could allow for early interventions…

Machine Learning · Computer Science 2020-06-18 Diyuan Lu , Sebastian Bauer , Valentin Neubert , Lara Sophie Costard , Felix Rosenow , Jochen Triesch

Epilepsy and psychogenic non-epileptic seizures often present with similar seizure-like manifestations but require fundamentally different management strategies. Misdiagnosis is common and can lead to prolonged diagnostic delays,…

Computation and Language · Computer Science 2026-03-31 Shuang Zhou , Kai Yu , Zaifu Zhan , Huixue Zhou , Min Zeng , Feng Xie , Zhiyi Sha , Rui Zhang

Epilepsy is a disorder of the brain denoted by frequent seizures. The symptoms of seizure include confusion, abnormal staring, and rapid, sudden, and uncontrollable hand movements. Epileptic seizure detection methods involve neurological…

Epilepsy is one of the common neurological disorders characterized by recurrent and uncontrollable seizures, which seriously affect the life of patients. In many cases, electroencephalograms signal can provide important physiological…

Neurons and Cognition · Quantitative Biology 2023-08-15 Mohammad Reza Yousefi , Saina Golnejad , Melika Mohammad Hosseini , Amin Dehghani

We investigate the suitability of selected measures of complexity based on recurrence quantification analysis and recurrence networks for an identification of pre-seizure states in multi-day, multi-channel, invasive electroencephalographic…