[Retracted] EEG‐Based Epileptic Seizure Detection via Machine/Deep Learning Approaches: A Systematic Review
I Ahmad, X Wang, M Zhu, C Wang, Y Pi… - Computational …, 2022 - Wiley Online Library
Epileptic seizure is one of the most chronic neurological diseases that instantaneously
disrupts the lifestyle of affected individuals. Toward developing novel and efficient …
disrupts the lifestyle of affected individuals. Toward developing novel and efficient …
A review of epileptic seizure detection using machine learning classifiers
Epilepsy is a serious chronic neurological disorder, can be detected by analyzing the brain
signals produced by brain neurons. Neurons are connected to each other in a complex way …
signals produced by brain neurons. Neurons are connected to each other in a complex way …
Applying deep learning for epilepsy seizure detection and brain mapping visualization
Deep Convolutional Neural Network (CNN) has achieved remarkable results in computer
vision tasks for end-to-end learning. We evaluate here the power of a deep CNN to learn …
vision tasks for end-to-end learning. We evaluate here the power of a deep CNN to learn …
Scalp EEG classification using deep Bi-LSTM network for seizure detection
Automatic seizure detection technology not only reduces workloads of neurologists for
epilepsy diagnosis but also is of great significance for treatments of epileptic patients. A …
epilepsy diagnosis but also is of great significance for treatments of epileptic patients. A …
Cognitive IoT-cloud integration for smart healthcare: case study for epileptic seizure detection and monitoring
M Alhussein, G Muhammad, MS Hossain… - Mobile Networks and …, 2018 - Springer
We propose a cognitive Internet of Things (IoT)–cloud-based smart healthcare framework,
which communicates with smart devices, sensors, and other stakeholders in the healthcare …
which communicates with smart devices, sensors, and other stakeholders in the healthcare …
EEG signal processing for epilepsy seizure detection using 5-level Db4 discrete wavelet transform, GA-based feature selection and ANN/SVM classifiers
Epilepsy is a neurobiological disease caused by abnormal electrical activity of the human
brain. It is important to detect the epileptic seizures to help the epileptic patients. Using brain …
brain. It is important to detect the epileptic seizures to help the epileptic patients. Using brain …
Epileptic eeg classification by using time-frequency images for deep learning
Epilepsy is one of the most common brain disorders worldwide. The most frequently used
clinical tool to detect epileptic events and monitor epilepsy patients is the EEG recordings …
clinical tool to detect epileptic events and monitor epilepsy patients is the EEG recordings …
On the use of wavelet domain and machine learning for the analysis of epileptic seizure detection from EEG signals
Epileptic patients suffer from an epileptic brain seizure caused by the temporary and
unpredicted electrical interruption. Conventionally, the electroencephalogram (EEG) signals …
unpredicted electrical interruption. Conventionally, the electroencephalogram (EEG) signals …
Automated FBSE-EWT based learning framework for detection of epileptic seizures using time-segmented EEG signals
Epilepsy is a neurological disorder that has severely affected many people's lives across the
world. Electroencephalogram (EEG) signals are used to characterize the brain's state and …
world. Electroencephalogram (EEG) signals are used to characterize the brain's state and …
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 …