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Related papers: Quantification of depth of anesthesia by nonlinear…

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Background: Electroencephalographic (EEG) indicators for anaesthesia depth are being developed. Here, we propose novel EEG parameters created by using two kinds of waveforms discriminated by voltage thresholds from a new perspective.…

Neurons and Cognition · Quantitative Biology 2019-10-08 Chika Koyama , Taichi Haruna , Satoshi Hagihira , Kazuto Yamashita

The amount of power in different frequency bands of the electroencephalogram (EEG) carries information about the behavioral state of a subject. Hence, neurologists treating epileptic patients monitor the temporal evolution of the different…

Neurons and Cognition · Quantitative Biology 2020-06-17 Melisa Maidana Capitán , Nuria Cámpora , Claudio Sebastián , Sigvard Silvia Kochen , Inés Samengo

Electroencephalogram (EEG) provides noninvasive measures of brain activity and is found to be valuable for diagnosis of some chronic disorders. Specifically, pre-treatment EEG signals in alpha and theta frequency bands have demonstrated…

Applications · Statistics 2023-05-24 Bin Yang , Xingche Guo , Ji Meng Loh , Qinxia Wang , Yuanjia Wang

To evaluate EEG data, one can count local maxima and minima on a fine scale, in a sliding window analysis. This straightforward calculation, which simplifies and improves previous work on permutation entropy, directly defines a good proxy…

Applications · Statistics 2017-10-03 Christoph Bandt

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

An Electroencephalogram (EEG) is a non-invasive exam that records the brain's electrical activity. This is used to help diagnose conditions such as different brain problems. EEG signals are taken for epilepsy detection, and with Discrete…

Machine Learning · Computer Science 2024-05-28 Rabel Guharoy , Nanda Dulal Jana , Suparna Biswas , Lalit Garg

Purpose: Understanding fluctuations of seizure severity within individuals is important for defining treatment outcomes and response to therapy, as well as developing novel treatments for epilepsy. Current methods for grading seizure…

Purpose: The understanding of brain activity, and in particular events such as epileptic seizures, lies on the characterisation of the dynamics of the neural networks. The theory of non-linear dynamics provides signal analysis techniques…

Medical Physics · Physics 2007-05-23 C. Silva , I. R. Pimentel , A. Andrade , J. P. Foreid , E. Ducla-Soares

Objectives. Accurately predicting transitions to anesthetic drugs overdosage is a critical challenge in general anesthesia as it requires the identification of EEG indicators relevant for anticipating the evolution of the depth of…

Neurons and Cognition · Quantitative Biology 2025-12-18 Christophe Sun , Pierre-Olivier Michel , François David , Nathalie Rouach , Dan Longrois , David Holcman

Current pain assessment within hospitals often relies on self-reporting or non-specific EKG vital signs. This system leaves critically ill, sedated, and cognitively impaired patients vulnerable to undertreated pain and opioid overuse.…

Machine Learning · Computer Science 2025-10-08 Aavid Mathrawala , Dhruv Kurup , Josie Lau

In current clinical practice, electroencephalograms (EEG) are reviewed and analyzed by well-trained neurologists to provide supports for therapeutic decisions. The way of manual reviewing is labor-intensive and error prone. Automatic and…

Signal Processing · Electrical Eng. & Systems 2019-06-07 Xinghua Yao , Qiang Cheng , Guo-Qiang Zhang

Invasive electroencephalograph (EEG) recordings of ten patients suffering from focal epilepsy were analyzed using the method of renormalized entropy. Introduced as a complexity measure for the different regimes of a dynamical system, the…

Medical Physics · Physics 2009-10-31 K. Kopitzki , P. C. Warnke , J. Timmer

Objective: The detection of epileptic seizures from scalp electroencephalogram (EEG) signals can facilitate early diagnosis and treatment. Previous studies suggested that the Gaussianity of EEG distributions changes depending on the…

Signal Processing · Electrical Eng. & Systems 2021-03-03 Akira Furui , Ryota Onishi , Akihito Takeuchi , Tomoyuki Akiyama , Toshio Tsuji

Pain remains one of the most pressing health challenges, yet its measurement still relies heavily on self-report, limiting monitoring in non-communicative patients and hindering translational research. Neural oscillations recorded with…

Neurons and Cognition · Quantitative Biology 2025-09-16 D. A. Blanco-Mora , A. Dierolf , J. Gonçalves , M. van Der Meulen

Epileptic seizures are neurological disorders characterized by abnormal and excessive electrical activity in the brain, resulting in recurrent seizure events. Electroencephalogram (EEG) signals are widely used for seizure diagnosis due to…

Machine Learning · Computer Science 2026-04-02 Ferdaus Anam Jibon , Fazlul Hasan Siddiqui , F. Deeba , Gahangir Hossain

Electroencephalogram (EEG) is an important diagnostic test that physicians use to record brain activity and detect seizures by monitoring the signals. There have been several attempts to detect seizures and abnormalities in EEG signals with…

Machine Learning · Computer Science 2022-03-22 Kwanhyung Lee , Hyewon Jeong , Seyun Kim , Donghwa Yang , Hoon-Chul Kang , Edward Choi

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

The underlying dynamics for the electroencephalographic (EEG) recordings from humans but especially epilepsy patients are usually not completely known. However, the ictal activity is claimed to be characterized by synchronous oscillations…

Biological Physics · Physics 2010-08-09 Caglar Tuncay

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 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
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