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While Deep Learning (DL) is often considered the state-of-the art for Artificial Intelligence-based medical decision support, it remains sparsely implemented in clinical practice and poorly trusted by clinicians due to insufficient…

Machine Learning · Computer Science 2020-12-23 Valentin Gabeff , Tomas Teijeiro , Marina Zapater , Leila Cammoun , Sylvain Rheims , Philippe Ryvlin , David Atienza

Hyperdimensional computing is a promising novel paradigm for low-power embedded machine learning. It has been applied on different biomedical applications, and particularly on epileptic seizure detection. Unfortunately, due to differences…

Signal Processing · Electrical Eng. & Systems 2021-12-20 Una Pale , Tomas Teijeiro , David Atienza

Forecasting a typical object's future motion is a critical task for interpreting and interacting with dynamic environments in computer vision. Event-based sensors, which could capture changes in the scene with exceptional temporal…

Computer Vision and Pattern Recognition · Computer Science 2024-10-14 Song Wu , Zhiyu Zhu , Junhui Hou , Guangming Shi , Jinjian Wu

Epilepsy is a disorder of the nervous system that can affect people of any age group. With roughly 50 million people worldwide diagnosed with the disorder, it is one of the most common neurological disorders. The EEG is an indispensable…

Populations and Evolution · Quantitative Biology 2022-02-21 Niamh McCallan , Scot Davidson , Kok Yew Ng , Pardis Biglarbeigi , Dewar Finlay , Boon Leong Lan , James McLaughlin

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

A variety of screening approaches have been proposed to diagnose epileptic seizures, using electroencephalography (EEG) and magnetic resonance imaging (MRI) modalities. Artificial intelligence encompasses a variety of areas, and one of its…

Seizure detection algorithms must discriminate abnormal neuronal activity associated with a seizure from normal neural activity in a variety of conditions. Our approach is to seek spatiotemporal waveforms with distinct morphology in…

Machine Learning · Computer Science 2021-08-16 Carlos H. Mendoza-Cardenas , Austin J. Brockmeier

In this era, big data applications including biomedical are becoming attractive as the data generation and storage is increased in the last years. The big data processing to extract knowledge becomes challenging since the data mining…

Distributed, Parallel, and Cluster Computing · Computer Science 2017-12-19 Samed Jukic , Abdulhamit Subasi

Understanding the seizure initiation process and its propagation pattern(s) is a critical task in epilepsy research. Characteristics of the pre-seizure electroencephalograms (EEGs) such as oscillating powers and high-frequency activities…

Applications · Statistics 2009-01-27 Li Qin , Yuedong Wang

Epilepsy is a common neurological disorder characterized by abrupt seizures. Although seizures may appear random, they are often preceded by early warning signs in neural signals, notably, critical slowing down, a phenomenon in which the…

Systems and Control · Electrical Eng. & Systems 2024-11-12 Yuzhen Qin , Marcel van Gerven

Neonates are highly susceptible to seizures, often leading to short or long-term neurological impairments. However, clinical manifestations of neonatal seizures are subtle and often lead to misdiagnoses. This increases the risk of…

Accurate epileptic seizure prediction from electroencephalography (EEG) remains challenging because pre-ictal dynamics may span long time horizons while clinically relevant signatures can be subtle and transient. Many deep learning models…

Machine Learning · Computer Science 2026-01-21 Tien-Dat Pham , Xuan-The Tran

Data-driven machine-learning for predicting instantaneous and future fault-slip in laboratory experiments has recently progressed markedly due to large training data sets. In Earth however, earthquake interevent times range from 10's-100's…

Geophysics · Physics 2022-01-19 Kun Wang , Christopher W. Johnson , Kane C. Bennett , Paul A. Johnson

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

Understanding how the brain switches from normal activity to an epileptic seizure is essential for improving seizure therapy, yet the underlying mechanisms remain largely unknown. In particular, seizure onset can be described as a critical…

Epilepsy is one of the most common brain diseases that affect more than 1\% of the world's population. It is characterized by recurrent seizures, which come in different types and are treated differently. Electroencephalography (EEG) is…

Signal Processing · Electrical Eng. & Systems 2022-06-09 Hezam Albaqami , Ghulam Mubashar Hassan , Amitava Datta

Epilepsy is a chronic neurological disorder affecting more than 65 million people worldwide and manifested by recurrent unprovoked seizures. The unpredictability of seizures not only degrades the quality of life of the patients, but it can…

Signal Processing · Electrical Eng. & Systems 2019-11-13 Damian Pascual , Amir Aminifar , David Atienza , Philippe Ryvlin , Roger Wattenhofer

Epilepsy is a chronic neurological disorder that affects a significant portion of the human population and imposes serious risks in the daily life of patients. Despite advances in machine learning and IoT, small, nonstigmatizing wearable…

Machine Learning · Computer Science 2023-02-22 Una Pale , Tomas Teijeiro , David Atienza

An ability to map seizure-generating brain tissue, i.e., the seizure onset zone (SOZ), without recording actual seizures could reduce the duration of invasive EEG monitoring for patients with drug-resistant epilepsy. A widely-adopted…

Over the past decade, high-frequency oscillations (HFOs) have been studied as a promising biomarker for localizing epileptogenic areas in drug-resistant patients requiring pre-surgical intervention, while exploiting intracranial…

Signal Processing · Electrical Eng. & Systems 2024-12-24 Zayneb Sadek , Abir Hadriche , Rahma Maalej , Nawel Jmail