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Identifying seizure activities in non-stationary electroencephalography (EEG) is a challenging task, since it is time-consuming, burdensome, and dependent on expensive human resources and subject to error and bias. A computerized seizure…

Signal Processing · Electrical Eng. & Systems 2020-04-29 S. Sheykhivand , T. Yousefi Rezaii , Z. Mousavi , A. Delpak , A. Farzamnia

Epilepsy is a chronic, noncommunicable brain disorder, and sudden seizure onsets can significantly impact patients' quality of life and health. However, wearable seizure-predicting devices are still limited, partly due to the bulky size of…

Signal Processing · Electrical Eng. & Systems 2025-07-22 Ruifeng Zheng , Cong Chen , Shuang Wang , Yiming Liu , Lin You , Jindong Lu , Ruizhe Zhu , Guodao Zhang , Kejie Huang

Epilepsy is a disease in which frequent seizures occur due to abnormal activity of neurons. Patients affected by this disease can be treated with the help of medicines or surgical procedures. However, both of these methods are not quite…

Neurons and Cognition · Quantitative Biology 2020-04-20 Syed Muhammad Usman , Shahzad Latif , Arshad Beg

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

Epilepsy is one of the most common neurological disorders affecting up to 1% of the world's population and approximately 2.5 million people in the United States. Seizures in more than 30% of epilepsy patients are refractory to…

Signal Processing · Electrical Eng. & Systems 2019-08-23 Md Abu Sayeed , Saraju P. Mohanty , Elias Kougianos

Objective. Deep neural networks (DNNs) have shown unprecedented success in various brain-machine interface applications such as epileptic seizure prediction. However, existing approaches typically train models in a patient-specific fashion…

Machine Learning · Computer Science 2022-06-14 Di Wu , Jie Yang , Mohamad Sawan

Information transmission in the human brain is a fundamentally dynamic network process. In partial epilepsy, this process is perturbed and highly synchronous seizures originate in a local network, the so-called epileptogenic zone (EZ),…

Neurons and Cognition · Quantitative Biology 2019-06-19 Simona Olmi , Spase Petkoski , Maxime Guye , Fabrice Bartolomei , Viktor Jirsa

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

Epilepsy is a neurological condition such that it affects the brain and the nervous system. It is characterized by recurrent seizures, which are physical reactions to sudden, usually brief, excessive electrical discharges in a group of…

Signal Processing · Electrical Eng. & Systems 2018-07-30 Asmaa Hamad , Aboul Ella Hassanien , Aly A. Fahmy , Essam H. Houssein

Epilepsy which is characterized by seizures is studied using EEG signals by recording the electrical activity of the brain. Different types of communication between different parts of the brain are characterized by many state of the art…

Machine Learning · Computer Science 2020-09-29 Mohammad Mansour , Fouad Khnaisser , Hmayag Partamian

Epilepsy is a neurological brain disorder which life threatening and gives rise to recurrent seizures that are unprovoked. It occurs due to the abnormal chemical changes in our brain. Over the course of many years, studies have been…

Signal Processing · Electrical Eng. & Systems 2022-10-13 Muhammad Shoaib Farooq , Aimen Zulfiqar , Shamyla Riaz

Approximately, 50 million people in the world are affected by epilepsy. For patients, the anti-epileptic drugs are not always useful and these drugs may have undesired side effects on a patient's health. If the seizure is predicted the…

Machine Learning · Computer Science 2019-12-16 Hazrat Ali , Feroz Karim , Junaid Javed Qureshi , Adnan Omer Abuassba , Mohammad Farhad Bulbul

Epilepsy or the occurrence of epileptic seizures, is one of the world's most well-known neurological disorders affecting millions of people. Seizures mostly occur due to non-coordinated electrical discharges in the human brain and may cause…

Machine Learning · Computer Science 2023-03-14 Hitesh Raju , Ankit Sharma , Aoife Smeaton , Alan F. Smeaton

Approximately over 50 million people worldwide suffer from epilepsy. Traditional diagnosis of epilepsy relies on tedious visual screening by highly trained clinicians from lengthy EEG recording that contains the presence of seizure (ictal)…

Artificial Intelligence · Computer Science 2009-04-27 Forrest Sheng Bao , Jue-Ming Gao , Jing Hu , Donald Y. -C. Lie , Yuanlin Zhang , K. J. Oommen

The electroencephalogram (EEG) is one of the most precious technologies to understand the happenings inside our brain and further understand our body's happenings. Automatic prediction of oncoming seizures using the EEG signals helps the…

Signal Processing · Electrical Eng. & Systems 2022-11-08 Abhijeet Bhattacharya

Epilepsy is one of the most prevalent brain disorders that disrupts the lives of millions worldwide. For patients with drug-resistant seizures, there exist implantable devices capable of monitoring neural activity, promptly triggering…

Signal Processing · Electrical Eng. & Systems 2023-10-31 Arman Zarei , Bingzhao Zhu , Mahsa Shoaran

Epilepsy is one of the most common neurological disorders, typically observed via seizure episodes. Epileptic seizures are commonly monitored through electroencephalogram (EEG) recordings due to their routine and low expense collection. The…

Signal Processing · Electrical Eng. & Systems 2023-01-10 İlkay Yıldız Potter , George Zerveas , Carsten Eickhoff , Dominique Duncan

Repeated epileptic seizures impair around 65 million people worldwide and a successful prediction of seizures could significantly help patients suffering from refractory epilepsy. For two dogs with yearlong intracranial…

Neurons and Cognition · Quantitative Biology 2022-01-13 Hongliu Yang , Matthias Eberlein , Jens Müller , Ronald Tetzlaff

Early management and better clinical outcomes for epileptic patients depend on seizure prediction. The accuracy and false alarm rates of existing systems are often compromised by their dependence on static thresholds and basic…

Signal Processing · Electrical Eng. & Systems 2025-01-29 Mathan Kumar Mounagurusamy , Thiyagarajan V S , Abdur Rahman , Shravan Chandak , D. Balaji , Venkateswara Rao Jallepalli

Implantable, closed-loop devices for automated early detection and stimulation of epileptic seizures are promising treatment options for patients with severe epilepsy that cannot be treated with traditional means. Most approaches for early…