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Related papers: Automated Video-EEG Analysis in Epilepsy Studies: …

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Epilepsy is one of the most common neurological disorders that greatly impair patient' daily lives. Traditional epileptic diagnosis relies on tedious visual screening by neurologists from lengthy EEG recording that requires the presence of…

Artificial Intelligence · Computer Science 2016-11-18 Forrest Sheng Bao , Donald Yu-Chun Lie , Yuanlin Zhang

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

More than 50 million individuals are affected by epilepsy, a chronic neurological disorder characterized by unprovoked, recurring seizures and psychological symptoms. Researchers are working to automatically detect or predict epileptic…

Signal Processing · Electrical Eng. & Systems 2023-06-22 Palak Handa , Sakshi Tiwari , Nidhi Goel

Epilepsy is the second most common brain disorder after migraine. Automatic detection of epileptic seizures can considerably improve the patients' quality of life. Current Electroencephalogram (EEG)-based seizure detection systems encounter…

Signal Processing · Electrical Eng. & Systems 2018-03-28 Ramy Hussein , Hamid Palangi , Rabab Ward , Z. Jane Wang

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

The prediction of epileptic seizure has always been extremely challenging in medical domain. However, as the development of computer technology, the application of machine learning introduced new ideas for seizure forecasting. Applying…

Machine Learning · Computer Science 2019-10-08 Haotian Liu , Lin Xi , Ying Zhao , Zhixiang Li

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 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

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…

In recent years, machine learning has become an increasingly powerful tool for supporting seizure detection and monitoring in epilepsy care. Traditional approaches focus on identifying seizures only after they begin, which limits the…

Machine Learning · Computer Science 2025-10-30 Ria Jayanti , Tanish Jain

With the advancement in artificial intelligence (AI) and machine learning (ML) techniques, researchers are striving towards employing these techniques for advancing clinical practice. One of the key objectives in healthcare is the early…

Machine Learning · Computer Science 2020-02-06 Khansa Rasheed , Adnan Qayyum , Junaid Qadir , Shobi Sivathamboo , Patrick Kwan , Levin Kuhlmann , Terence O'Brien , Adeel Razi

Machine learning (ML)-based analysis of electroencephalograms (EEGs) is playing an important role in advancing neurological care. However, the difficulties in automatically extracting useful metadata from clinical records hinder the…

Computation and Language · Computer Science 2021-09-14 Samarth Rawal , Yogatheesan Varatharajah

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

In a clinical setting, epilepsy patients are monitored via video electroencephalogram (EEG) tests. A video EEG records what the patient experiences on videotape while an EEG device records their brainwaves. Currently, there are no existing…

Computer Vision and Pattern Recognition · Computer Science 2021-11-30 Siddharth Sharma , Florian Dubost , Christopher Lee-Messer , Daniel Rubin

Reliable seizure detection in mouse models is essential for preclinical epilepsy research, yet manual review of synchronized video-EEG recordings is labor-intensive and single-modality systems fail for complementary reasons: video-based…

Computer Vision and Pattern Recognition · Computer Science 2026-04-30 Tong Lu , Ke Xu , Zimo Zhang , Zitong Zhao , Danwei Weng , Ruiyu Wang , Miao Liu , Zizuo Zhang , Jingyi Yao , Yixuan Zhao , Wenchao Zhang , Min Wang , Guoming Luan , Minmin Luo , Zhifeng Yue

Epilepsy, affecting approximately 50 million people globally, is characterized by abnormal brain activity and remains challenging to treat. The diagnosis of epilepsy relies heavily on electroencephalogram (EEG) data, where specialists…

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 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 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

Epilepsy represents the most prevalent neurological disease in the world. One-third of people suffering from mesial temporal lobe epilepsy (MTLE) exhibit drug resistance, urging the need to develop new treatments. A key part in anti-seizure…

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