[PDF] bracu.ac.bd

Epileptic seizure detection by exploiting eeg signals using different decomposition techniques and machine learning approaches

R Karim, S Nitol, MM Rahman - 2018 - dspace.bracu.ac.bd
In recent years, detecting epileptic seizure has gained a high demand in the field of
research. It is such a common and high talked brain disorder, since more than 65 million …
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Automatic Epileptic Seizure Classification using MODWT and SVM

J Prasanna, GS Thomas, MSP Subathra… - 2019 2nd …, 2019 - ieeexplore.ieee.org
Epilepsy is the neurological disorder that makes tough for epileptic patients to survive a
natural life. Because classifying the electroencephalography (EEG) records is a difficult job …
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[PDF] researchgate.net

Identification of epileptic seizures in EEG signals using time-scale decomposition (ITD), discrete wavelet transform (DWT), phase space reconstruction (PSR) and …

W Zeng, M Li, C Yuan, Q Wang, F Liu… - Artificial Intelligence …, 2020 - Springer
Traditionally, detection of epileptic seizures based on the visual inspection of neurologists is
tedious, laborious and subjective. To overcome such disadvantages, numerous seizure …
被引用次数：38 相关文章 所有 6 个版本

A hybrid model for epileptic seizure classification using wavelet packet decomposition and SVM

M Panigrahi, DK Behera, KC Patra - Advances in Intelligent Computing …, 2021 - Springer
The synaptic disturbance in the prefrontal portion of the brain induces epileptic seizures.
Electroencephalography is a noninvasive tool for diagnosing the different brain disorders …
被引用次数：3 相关文章 所有 2 个版本

EEG Signal Classification using Discrete Wavelet Transform (DWT) and Gaussian Support Vector Machine (SVM) for Epileptics

R Mardiati, D Zulherman, R Widadi - 2023 17th International …, 2023 - ieeexplore.ieee.org
As a potentially life-threatening neurological disorder, epilepsy needs early treatment to
prevent the deterioration of the patient's condition. Electroencephalogram (EEG) technology …
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Epileptic EEG signal classification using wavelet transform and SVM

S Taran, C Dhiman, M Kumar - jpconf.iop.org
Automated epileptical seizure identification utilizing electroencephalograms (EEGs) has
been a prime area of extensive research. The different frequency bands that make up the …
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[PDF] arxiv.org

A hybrid automated detection of epileptic seizures in EEG based on wavelet and machine learning techniques

A Hamad, AE Hassanien, AA Fahmy… - arXiv preprint arXiv …, 2018 - arxiv.org
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 …
被引用次数：7 相关文章 所有 3 个版本

Classification and discrimination of focal and non-focal EEG signals using hybrid features and support vector machine

HD Praveena, C Subhas… - International Journal of …, 2021 - inderscienceonline.com
In the current scenario, computerised epileptic seizure detection is an emerging research
area in the field of medical diagnosis. In this paper, electroencephalogram (EEG) signals …
被引用次数：4 相关文章 所有 4 个版本

An EEG based real-time epilepsy seizure detection approach using discrete wavelet transform and machine learning methods

M Shen, P Wen, B Song, Y Li - Biomedical Signal Processing and Control, 2022 - Elsevier
Epilepsy is one of the most common complex brain disorders which is a chronic non-
communicable disease caused by paroxysmal abnormal super-synchronous electrical …
被引用次数：58 相关文章 所有 2 个版本

A comparative study of epileptic seizure detection framework using SVM and ELM

BB Shabarinath, K CHALLAGULLA… - … and Control Systems …, 2019 - ieeexplore.ieee.org
Poverty and lack of health awareness are major reasons for illnesses, particularly neurology-
related problems in India. Epilepsy is one such problem that affects the brain by causing …
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