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Burst-suppression (BS) is a reliable electroencephalogram (EEG) indicator of excessive deep anesthesia common in mammals. Since some intermittent events are known to follow a power-law, we investigated the power-law hypothesis in BS by…

Neurons and Cognition · Quantitative Biology 2020-05-15 Chika Koyama , Taichi Haruna , Satoshi Hagihira , Kazuto Yamashita

We investigate several quantifiers of the electroencephalogram (EEG) signal with respect to their ability to indicate depth of anesthesia. For 17 patients anesthetized with Sevoflurane, three established measures (two spectral and one based…

Chaotic Dynamics · Physics 2009-10-31 G. Widman , T. Schreiber , B. Rehberg , A. Hoeft , C. E. Elger

Brain waves still cannot reliably distinguish between awake and asleep states. Here, I present new original indices, voltage subthreshold wave $\tau$ and abovethreshold wave burst, for advanced LFP/EEG readings. Assuming that $\tau$ is a…

Neurons and Cognition · Quantitative Biology 2024-11-19 Chika Koyama

Electroencephalography (EEG) is an important clinical tool for grading injury caused by lack of oxygen or blood to the brain during birth. Characteristics of low-voltage waveforms, known as inter-bursts, are related to different grades of…

Signal Processing · Electrical Eng. & Systems 2019-07-08 Sumit A. Raurale , Saif Nalband , Geraldine B. Boylan , Gordon Lightbody , John M. O'Toole

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

The study of electroencephalographic (EEG) bursts in preterm infants provides valuable information about maturation or prognostication after perinatal asphyxia. Over the last two decades, a number of works proposed algorithms to…

Neurons and Cognition · Quantitative Biology 2017-06-02 X. Navarro , F. Porée , M. Kuchenbuch , M. Chavez , A. Beuchée , G. Carrault

Inherent fuzzy entropy is an objective measurement of electroencephalography (EEG) complexity, reflecting the robustness of brain systems. In this study, we present a novel application of multi-scale relative inherent fuzzy entropy using…

Human-Computer Interaction · Computer Science 2019-05-28 Zehong Cao , Chin-Teng Lin , Kuan-Lin Lai , Li-Wei Ko , Jung-Tai King , Jong-Ling Fuh , Shuu-Jiun Wang

Multiscale inherent fuzzy entropy is an objective measurement of electroencephalography (EEG) complexity, reflecting the habituation of brain systems. Entropy dynamics are generally believed to reflect the ability of the brain to adapt to a…

Signal Processing · Electrical Eng. & Systems 2019-05-28 Zehong Cao , Weiping Ding , Yu-Kai Wang , Farookh Khadeer Hussain , Adel Al-Jumaily , Chin-Teng Lin

Post-operative cognitive decline is a well-known phenomenon and of crucial importance especially in the elderly. General anesthesia can be accomplished by inhalation-based (volatile) or total intravenous anesthesia (TIVA). While their…

Neurons and Cognition · Quantitative Biology 2022-02-16 Amitai Bickel , Alexey Gavrilov , Shimon Ivry , Neta B Maimon , Lior Molcho , Nathan Intrator

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

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

Electroencephalography (EEG) is an important clinical tool for reviewing sleep-wake cycling in neonates in intensive care. Trace alternant (TA)-a characteristic pattern of EEG activity during quiet sleep in term neonates-is defined by…

Signal Processing · Electrical Eng. & Systems 2020-05-13 Sumit A. Raurale , Geraldine B. Boylan , Gordon Lightbody , John M. O'Toole

We recently developed original electroencephalogram indices focusing on microwaves of flattish period (named $\tau$), which correlated with volatile anesthesia concentration in dogs. However, this mechanism remains unclear. $\tau$ was…

Neurons and Cognition · Quantitative Biology 2021-05-28 Chika Koyama , Taichi Haruna , Kazuto Yamashita

Since the manual detection of electrographic seizures in continuous electroencephalogram (EEG) monitoring is very time-consuming and requires a trained expert, attempts to develop automatic seizure detection are diverse and ongoing. Machine…

Signal Processing · Electrical Eng. & Systems 2019-08-02 Poomipat Boonyakitanont , Apiwat Lek-uthai , Krisnachai Chomtho , Jitkomut Songsiri

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

In this article we present the results of our research related to the study of correlations between specific visual stimulation and the elicited brain's electro-physiological response collected by EEG sensors from a group of participants.…

Machine Learning · Computer Science 2017-08-04 Iaroslav Omelianenko

Electroencephalography (EEG) is commonly used by physicians for the diagnosis of numerous neurological disorders. Due to the large volume of EEGs requiring interpretation and the specific expertise involved, artificial intelligence-based…

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

Over the past few decades, electroencephalography (EEG) monitoring has become a pivotal tool for diagnosing neurological disorders, particularly for detecting seizures. Epilepsy, one of the most prevalent neurological diseases worldwide,…

Machine Learning · Computer Science 2025-08-08 Andrea Pollastro , Francesco Isgrò , Roberto Prevete

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
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