Automated epilepsy detection techniques from electroencephalogram signals: a review study
Epilepsy is a serious neurological condition which contemplates as top 5 reasons for
avoidable mortality from ages 5–29 in the worldwide. The avoidable deaths due to epilepsy …
avoidable mortality from ages 5–29 in the worldwide. The avoidable deaths due to epilepsy …
Time series analysis via network science: Concepts and algorithms
There is nowadays a constant flux of data being generated and collected in all types of real
world systems. These data sets are often indexed by time, space, or both requiring …
world systems. These data sets are often indexed by time, space, or both requiring …
A new framework for automatic detection of patients with mild cognitive impairment using resting-state EEG signals
Mild cognitive impairment (MCI) can be an indicator representing the early stage of
Alzheimier's disease (AD). AD, which is the most common form of dementia, is a major …
Alzheimier's disease (AD). AD, which is the most common form of dementia, is a major …
A long short-term memory based framework for early detection of mild cognitive impairment from EEG signals
Mild cognitive impairment (MCI) is an irreparable progressive neuro-degenerative disorder,
which seems to be a precursor to Alzheimer's disease (AD) that may lead to dementia in …
which seems to be a precursor to Alzheimer's disease (AD) that may lead to dementia in …
Epileptic seizures detection in EEG signals using fusion handcrafted and deep learning features
Epilepsy is a brain disorder disease that affects people's quality of life.
Electroencephalography (EEG) signals are used to diagnose epileptic seizures. This paper …
Electroencephalography (EEG) signals are used to diagnose epileptic seizures. This paper …
EEG-Based Seizure detection using linear graph convolution network with focal loss
Y Zhao, C Dong, G Zhang, Y Wang, X Chen… - Computer methods and …, 2021 - Elsevier
Abstract Background and Objectives: Epilepsy is a clinical phenomenon caused by sudden
abnormal and excessive discharge of brain neurons. It affects around 70 million people all …
abnormal and excessive discharge of brain neurons. It affects around 70 million people all …
Holistic approaches to music genre classification using efficient transfer and deep learning techniques
SK Prabhakar, SW Lee - Expert Systems with Applications, 2023 - Elsevier
With the rapid development of high-tech multimedia technologies, many musical resource
assets are available online and it has always triggered an interest in the classification of …
assets are available online and it has always triggered an interest in the classification of …
A unified framework and method for EEG-based early epileptic seizure detection and epilepsy diagnosis
Z Chen, G Lu, Z Xie, W Shang - IEEE Access, 2020 - ieeexplore.ieee.org
Electroencephalogram (EEG) contains important physiological information that can reflect
the activity of human brain, making it useful for epileptic seizure detection and epilepsy …
the activity of human brain, making it useful for epileptic seizure detection and epilepsy …
Detecting abnormal pattern of epileptic seizures via temporal synchronization of EEG signals
Objective: Synchronization phenomena of epileptic electroencephalography (EEG) have
long been studied. In this study, we aim at investigating the spatial-temporal synchronization …
long been studied. In this study, we aim at investigating the spatial-temporal synchronization …
Epileptic seizure detection based on stockwell transform and bidirectional long short-term memory
Automatic seizure detection plays a significant role in monitoring and diagnosis of epilepsy.
This paper presents an efficient automatic seizure detection method based on Stockwell …
This paper presents an efficient automatic seizure detection method based on Stockwell …