Epileptic Seizures Detection Using Deep Learning Techniques: A Review

A variety of screening approaches have been proposed to diagnose epileptic seizures, using Electroencephalography (EEG) and Magnetic Resonance Imaging (MRI) modalities. Artificial intelligence encompasses a variety of areas, and one of its branches is deep learning. Before the rise of deep learning, conventional machine learning algorithms involving feature extraction were performed. This limited their performance to the ability of those handcrafting the features. However, in deep learning, the extraction of features and classification is entirely automated. The advent of these techniques in many areas of medicine such as diagnosis of epileptic seizures, has made significant advances. In this study, a comprehensive overview of the types of deep learning methods exploited to diagnose epileptic seizures from various modalities has been studied. Additionally, hardware implementation and cloud-based works are discussed as they are most suited for applied medicine.

[1]  Kevin H. Leung,et al.  Direct attenuation correction of brain PET images using only emission data via a deep convolutional encoder-decoder (Deep-DAC) , 2019, European Radiology.

[2]  U. Rajendra Acharya,et al.  A new approach to characterize epileptic seizures using analytic time-frequency flexible wavelet transform and fractal dimension , 2017, Pattern Recognit. Lett..

[3]  John Thomas,et al.  EEG CLassification Via Convolutional Neural Network-Based Interictal Epileptiform Event Detection , 2018, 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[4]  U. Rajendra Acharya,et al.  A deep convolutional neural network model for automated identification of abnormal EEG signals , 2018, Neural Computing and Applications.

[5]  A. Tzallas,et al.  Automated Epileptic Seizure Detection Methods: A Review Study , 2012 .

[6]  Rabab Kreidieh Ward,et al.  Robust Detection of Epileptic Seizures Using Deep Neural Networks , 2018, 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[7]  Subhrajit Roy,et al.  Deep Learning Enabled Automatic Abnormal EEG Identification , 2018, 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[8]  Raúl Alcaraz,et al.  Detection of Negative Stress through Spectral Features of Electroencephalographic Recordings and a Convolutional Neural Network , 2021, Sensors.

[9]  Maribel Peró-Cebollero,et al.  Relationship between Quality of Life and the Complexity of Default Mode Network in Resting State Functional Magnetic Resonance Image in Down Syndrome , 2020, International journal of environmental research and public health.

[10]  Clinton Fookes,et al.  Deep facial analysis: A new phase I epilepsy evaluation using computer vision , 2018, Epilepsy & Behavior.

[11]  Le Trung Thanh,et al.  Deep Learning for Epileptic Spike Detection , 2018 .

[12]  T Rajendran,et al.  An Overview of EEG Seizure Detection Units and Identifying their Complexity-A Review , 2018 .

[13]  H. Adeli,et al.  Automated seizure prediction , 2018, Epilepsy & Behavior.

[14]  Robertas Alzbutas,et al.  Convolutional neural network for detection and classification of seizures in clinical data , 2019, Medical & Biological Engineering & Computing.

[15]  Jianguo Liu,et al.  Deep Learning Classification for Epilepsy Detection Using a Single Channel Electroencephalography (EEG) , 2019, ICDLT.

[16]  Saeid Nahavandi,et al.  Coronary artery disease detection using artificial intelligence techniques: A survey of trends, geographical differences and diagnostic features 1991-2020 , 2020, Comput. Biol. Medicine.

[17]  Jungjoon Kim,et al.  Wave2Vec: Vectorizing Electroencephalography Bio-Signal for Prediction of Brain Disease , 2018, International journal of environmental research and public health.

[18]  Hadj Batatia,et al.  Epileptic Seizure Detection Using a Convolutional Neural Network , 2019, Advances in Predictive, Preventive and Personalised Medicine.

[19]  Min Hong,et al.  Deep Learning in Physiological Signal Data: A Survey , 2020, Sensors.

[20]  Navid Ghassemi,et al.  Material Recognition for Automated Progress Monitoring using Deep Learning Methods , 2020, ArXiv.

[21]  Terence O'Brien,et al.  Epileptic Seizure Prediction Using Big Data and Deep Learning: Toward a Mobile System , 2017, EBioMedicine.

[22]  U. Rajendra Acharya,et al.  Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals , 2017, Comput. Biol. Medicine.

[23]  Xianrui Zhang,et al.  Conditional Adversarial Domain Adaptation Neural Network for Motor Imagery EEG Decoding , 2020, Entropy.

[24]  Vishnu S. Pendyala,et al.  Machine Learning Algorithms , 2018, Optimization Techniques and Applications with Examples.

[25]  Rajeev Sharma,et al.  Classification of epileptic seizures in EEG signals based on phase space representation of intrinsic mode functions , 2015, Expert Syst. Appl..

[26]  Justin Dauwels,et al.  Epileptiform spike detection via convolutional neural networks , 2016, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[27]  Kensuke Kawai,et al.  Seizure detection by convolutional neural network-based analysis of scalp electroencephalography plot images , 2019, NeuroImage: Clinical.

[28]  Saeid Nahavandi,et al.  An Overview on Artificial Intelligence Techniques for Diagnosis of Schizophrenia Based on Magnetic Resonance Imaging Modalities: Methods, Challenges, and Future Works , 2021, ArXiv.

[29]  Rubén San-Segundo-Hernández,et al.  Classification of epileptic EEG recordings using signal transforms and convolutional neural networks , 2019, Comput. Biol. Medicine.

[30]  Tayfun Gokmen,et al.  The Next Generation of Deep Learning Hardware: Analog Computing , 2019, Proceedings of the IEEE.

[31]  Jiening Zhan,et al.  Temporal Graph Convolutional Networks for Automatic Seizure Detection , 2019, MLHC.

[32]  Saeid Sanei,et al.  Deep Neural Architectures for Mapping Scalp to Intracranial EEG , 2018, Int. J. Neural Syst..

[33]  Jochen Triesch,et al.  Residual Deep Convolutional Neural Network for EEG Signal Classification in Epilepsy , 2019, ArXiv.

[34]  L. M. Morales Chacón,et al.  Surgical Outcome in Extratemporal Epilepsies Based on Multimodal Pre-Surgical Evaluation and Sequential Intraoperative Electrocorticography , 2021, Behavioral sciences.

[35]  Qiang Cheng,et al.  Automated Classification of Seizures against Nonseizures: A Deep Learning Approach , 2019, ArXiv.

[36]  Rahib H. Abiyev,et al.  Identification of Epileptic EEG Signals Using Convolutional Neural Networks , 2020, Applied Sciences.

[37]  Geraldine B. Boylan,et al.  Neonatal seizure detection using convolutional neural networks , 2017, 2017 IEEE 27th International Workshop on Machine Learning for Signal Processing (MLSP).

[38]  Sofia Chatziioannou,et al.  Imaging with PET/CT in Patients with Epilepsy , 2018, Epilepsy Surgery and Intrinsic Brain Tumor Surgery.

[39]  Christian Meisel,et al.  Deep learning from wristband sensor data: towards wearable, non-invasive seizure forecasting. , 2019, 1906.00511.

[40]  Sanjeev Kumar,et al.  Methods of denoising of electroencephalogram signal: a review , 2015 .

[41]  Nassir Navab,et al.  Convolutional neural networks for real-time epileptic seizure detection , 2018, Comput. methods Biomech. Biomed. Eng. Imaging Vis..

[42]  Kebin Jia,et al.  A Multi-view Deep Learning Method for Epileptic Seizure Detection using Short-time Fourier Transform , 2017, BCB.

[43]  Sabine Van Huffel,et al.  Neonatal Seizure Detection Using Deep Convolutional Neural Networks , 2019, Int. J. Neural Syst..

[44]  Prasant Kumar Pattnaik,et al.  A Review on Epileptic Seizure Detection and Prediction Using Soft Computing Techniques , 2019, Smart Techniques for a Smarter Planet.

[45]  Xuhui Chen,et al.  Cost-Sensitive Deep Active Learning for Epileptic Seizure Detection , 2018, BCB.

[46]  Samuel Burns Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow , 2019 .

[47]  Archana Verma,et al.  Epileptic Seizure Detection Using Deep Recurrent Neural Networks in EEG Signals , 2020 .

[48]  R. B. Pachori,et al.  Tunable-Q Wavelet Transform Based Multiscale Entropy Measure for Automated Classification of Epileptic EEG Signals , 2017 .

[49]  Joelle Pineau,et al.  Learning Robust Features using Deep Learning for Automatic Seizure Detection , 2016, MLHC.

[50]  Jianbin Tang,et al.  SeizureNet: Multi-Spectral Deep Feature Learning for Seizure Type Classification , 2019, MLCN/RNO-AI@MICCAI.

[51]  Afshin Shoeibi,et al.  A Hierarchical Classification Method for Breast Tumor Detection , 2016 .

[52]  U. Rajendra Acharya,et al.  Automated EEG-based screening of depression using deep convolutional neural network , 2018, Comput. Methods Programs Biomed..

[53]  Dong Yu,et al.  Deep Learning and Its Applications to Signal and Information Processing [Exploratory DSP] , 2011, IEEE Signal Processing Magazine.

[54]  Kensuke Kawai,et al.  Autoencoding of long-term scalp electroencephalogram to detect epileptic seizure for diagnosis support system , 2019, Comput. Biol. Medicine.

[55]  Magdy A. Bayoumi,et al.  Epileptic Seizure Detection using Deep Convolutional Autoencoder , 2018, 2018 IEEE International Workshop on Signal Processing Systems (SiPS).

[56]  John Thomas,et al.  A deep Learning Scheme for Automatic Seizure Detection from Long-Term Scalp EEG , 2018, 2018 52nd Asilomar Conference on Signals, Systems, and Computers.

[57]  Kebin Jia,et al.  A Multi-View Deep Learning Framework for EEG Seizure Detection , 2019, IEEE Journal of Biomedical and Health Informatics.

[58]  Dario Pompili,et al.  Deep Learning with Edge Computing for Localization of Epileptogenicity Using Multimodal rs-fMRI and EEG Big Data , 2017, 2017 IEEE International Conference on Autonomic Computing (ICAC).

[59]  Ying Liang,et al.  Automated Detection of High-Frequency Oscillations in Epilepsy Based on a Convolutional Neural Network , 2019, Front. Comput. Neurosci..

[60]  Saeid Nahavandi,et al.  Deep Learning for Neuroimaging-based Diagnosis and Rehabilitation of Autism Spectrum Disorder: A Review , 2020, Comput. Biol. Medicine.

[61]  Oliver Chiu-sing Choy,et al.  Spatial temporal GRU convnets for vision-based real time epileptic seizure detection , 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018).

[62]  Yann LeCun,et al.  1.1 Deep Learning Hardware: Past, Present, and Future , 2019, 2019 IEEE International Solid- State Circuits Conference - (ISSCC).

[63]  Nitish Srivastava,et al.  Multimodal learning with deep Boltzmann machines , 2012, J. Mach. Learn. Res..

[64]  Ling Liu,et al.  A Deep Learning Method for Prediction of Benign Epilepsy with Centrotemporal Spikes , 2018, ISBRA.

[65]  Petr Klimes,et al.  Deep-learning for seizure forecasting in canines with epilepsy , 2019, Journal of neural engineering.

[66]  Toshihisa Tanaka,et al.  Fully Data-driven Convolutional Filters with Deep Learning Models for Epileptic Spike Detection , 2019, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[67]  Navid Ghassemi,et al.  Epileptic seizures detection in EEG signals using TQWT and ensemble learning , 2019, 2019 9th International Conference on Computer and Knowledge Engineering (ICCKE).

[68]  Maurice Abou Jaoude,et al.  Detection of mesial temporal lobe epileptiform discharges on intracranial electrodes using deep learning , 2019, Clinical Neurophysiology.

[69]  Qin Lin,et al.  Classification of Epileptic EEG Signals with Stacked Sparse Autoencoder Based on Deep Learning , 2016, ICIC.

[70]  Yongtian He,et al.  Deep learning for electroencephalogram (EEG) classification tasks: a review , 2019, Journal of neural engineering.

[71]  Saeid Nahavandi,et al.  A comprehensive comparison of handcrafted features and convolutional autoencoders for epileptic seizures detection in EEG signals , 2021, Expert Syst. Appl..

[72]  Pradip Sircar,et al.  Computer-Aided Diagnosis of Epilepsy Using Bispectrum of EEG Signals , 2019, Application of Biomedical Engineering in Neuroscience.

[73]  N. J. Stevenson,et al.  Descriptor : A dataset of neonatal EEG recordings with seizure annotations , 2019 .

[74]  Mehran Ebrahimi,et al.  Identifying lesions in paediatric epilepsy using morphometric and textural analysis of magnetic resonance images , 2019, NeuroImage: Clinical.

[75]  Rong-Ching Wu,et al.  Alternative Diagnosis of Epilepsy in Children Without Epileptiform Discharges Using Deep Convolutional Neural Networks , 2020, Int. J. Neural Syst..

[76]  C. Bazil,et al.  Sleep and Epilepsy: a Focused Review of Pathophysiology, Clinical Syndromes, Co-morbidities, and Therapy , 2021, Neurotherapeutics.

[77]  Dong Yu,et al.  Deep Learning and Its Applications to Signal and Information Processing , 2011 .

[78]  Jyoteesh Malhotra,et al.  Stacked Autoencoders Based Deep Learning Approach for Automatic Epileptic Seizure Detection , 2018, 2018 First International Conference on Secure Cyber Computing and Communication (ICSCCC).

[79]  Sridha Sridharan,et al.  Deep Classification of Epileptic Signals , 2018, 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[80]  Xiaoqi Ma,et al.  Transfer Learning and Fusion Model for Classification of Epileptic PET Images , 2019, Innovation in Medicine and Healthcare Systems, and Multimedia.

[81]  Joseph Picone,et al.  Automatic Analysis of EEGs Using Big Data and Hybrid Deep Learning Architectures , 2017, Front. Hum. Neurosci..

[82]  Rabab K. Ward,et al.  Epileptic Seizure Detection: A Deep Learning Approach , 2018, 1803.09848.

[83]  J. B. Romaine,et al.  EEG—Single-Channel Envelope Synchronisation and Classification for Seizure Detection and Prediction , 2021, Brain sciences.

[84]  M. Shamim Hossain,et al.  Applying Deep Learning for Epilepsy Seizure Detection and Brain Mapping Visualization , 2019, ACM Trans. Multim. Comput. Commun. Appl..

[85]  Geoffrey E. Hinton,et al.  ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.

[86]  Harikumar Rajaguru,et al.  Multilayer Autoencoders and EM - PCA with Genetic Algorithm for Epilepsy Classification from EEG , 2018, 2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA).

[87]  Dumitru Erhan,et al.  Going deeper with convolutions , 2014, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[88]  Mokhtar Mohammadi,et al.  Epileptic Seizure Detection using Deep Learning Approach , 2019, UHD Journal of Science and Technology.

[89]  Saeid Nahavandi,et al.  CNN AE: Convolution Neural Network combined with Autoencoder approach to detect survival chance of COVID 19 patients , 2021, ArXiv.

[90]  Norman Delanty,et al.  Widespread cortical morphologic changes in juvenile myoclonic epilepsy: Evidence from structural MRI , 2012, Epilepsia.

[91]  Kebin Jia,et al.  Wave2Vec: Deep representation learning for clinical temporal data , 2019, Neurocomputing.

[92]  Geoffrey E. Hinton,et al.  Deep Learning , 2015, Nature.

[93]  Fadwa Al-Azzo,et al.  Classification and discrimination of focal and non-focal EEG signals based on deep neural network , 2017, 2017 International Conference on Current Research in Computer Science and Information Technology (ICCIT).

[94]  Terence O'Brien,et al.  Machine Learning for Predicting Epileptic Seizures Using EEG Signals: A Review , 2020, IEEE Reviews in Biomedical Engineering.

[95]  K Lehnertz,et al.  Indications of nonlinear deterministic and finite-dimensional structures in time series of brain electrical activity: dependence on recording region and brain state. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[96]  Roohallah Alizadehsani,et al.  CNN-KCL: Automatic myocarditis diagnosis using convolutional neural network combined with k-means clustering. , 2020, Mathematical biosciences and engineering : MBE.

[97]  Rabab K. Ward,et al.  Optimized deep neural network architecture for robust detection of epileptic seizures using EEG signals , 2019, Clinical Neurophysiology.

[98]  Hilal Kaya,et al.  A new framework using deep auto-encoder and energy spectral density for medical waveform data classification and processing , 2019, Biocybernetics and Biomedical Engineering.

[99]  Boris C. Bernhardt,et al.  Deep Convolutional Networks for Automated Detection of Epileptogenic Brain Malformations , 2018, MICCAI.

[100]  Ruben Morales-Menendez,et al.  A review of epileptic seizure detection using machine learning classifiers , 2020, Brain Informatics.

[101]  J. T. Turner,et al.  Deep Belief Networks used on High Resolution Multichannel Electroencephalography Data for Seizure Detection , 2017, AAAI Spring Symposia.

[102]  Development and Analysis of Deep Learning Architectures , 2020, Studies in Computational Intelligence.

[103]  Mustafa Talha Avcu,et al.  Seizure Detection Using Least Eeg Channels by Deep Convolutional Neural Network , 2019, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[104]  Rohan Akut,et al.  Wavelet based deep learning approach for epilepsy detection , 2019, Health Information Science and Systems.

[105]  Fenglong Ma,et al.  A novel channel-aware attention framework for multi-channel EEG seizure detection via multi-view deep learning , 2018, 2018 IEEE EMBS International Conference on Biomedical & Health Informatics (BHI).

[106]  Navid Ghassemi,et al.  Automatic diagnosis of COVID-19 from CT images using CycleGAN and transfer learning , 2021, Applied Soft Computing.

[107]  Mohamad Sawan,et al.  Towards accurate prediction of epileptic seizures: A review , 2017, Biomed. Signal Process. Control..

[108]  Ralph G Andrzejak,et al.  Nonrandomness, nonlinear dependence, and nonstationarity of electroencephalographic recordings from epilepsy patients. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

[109]  U Rajendra Acharya,et al.  A Deep Learning Model for Automated Sleep Stages Classification Using PSG Signals , 2019, International journal of environmental research and public health.

[110]  Jasmin Kevric,et al.  Performance evaluation of empirical mode decomposition, discrete wavelet transform, and wavelet packed decomposition for automated epileptic seizure detection and prediction , 2018, Biomed. Signal Process. Control..

[111]  U. Rajendra Acharya,et al.  MMSFL-OWFB: A novel class of orthogonal wavelet filters for epileptic seizure detection , 2018, Knowl. Based Syst..

[112]  U. Rajendra Acharya,et al.  Automated detection of diabetic subject using pre-trained 2D-CNN models with frequency spectrum images extracted from heart rate signals , 2019, Comput. Biol. Medicine.

[113]  Chandan Chakraborty,et al.  Application of Higher Order cumulant Features for Cardiac Health Diagnosis using ECG signals , 2013, Int. J. Neural Syst..

[114]  Magdy Bayoumi,et al.  Automatic epileptic seizure detection based on empirical mode decomposition and deep neural network , 2018, 2018 IEEE 14th International Colloquium on Signal Processing & Its Applications (CSPA).

[115]  Chris Rorden,et al.  Deep learning applied to whole‐brain connectome to determine seizure control after epilepsy surgery , 2018, Epilepsia.

[116]  Michel J. A. M. van Putten,et al.  Deep learning for detection of focal epileptiform discharges from scalp EEG recordings , 2018, Clinical Neurophysiology.

[117]  Nejra Beganovic,et al.  FPGA-based real-time epileptic seizure classification using Artificial Neural Network , 2020, Biomed. Signal Process. Control..

[118]  Bo Yan,et al.  An EEG signal classification method based on sparse auto-encoders and support vector machine , 2016, 2016 IEEE/CIC International Conference on Communications in China (ICCC).

[119]  U. Rajendra Acharya,et al.  Characterization of focal EEG signals: A review , 2019, Future Gener. Comput. Syst..

[120]  Mehmet Sirac Ozerdem,et al.  Epilepsy Detection by Using Scalogram Based Convolutional Neural Network from EEG Signals. , 2019 .

[121]  Tinoosh Mohsenin,et al.  Wearable seizure detection using convolutional neural networks with transfer learning , 2016, 2016 IEEE International Symposium on Circuits and Systems (ISCAS).

[122]  Sachin S. Talathi,et al.  Deep Recurrent Neural Networks for seizure detection and early seizure detection systems , 2017, ArXiv.

[123]  Ali H. Shoeb,et al.  Application of machine learning to epileptic seizure onset detection and treatment , 2009 .

[124]  Andrew Zisserman,et al.  Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.

[125]  Toshihisa Tanaka,et al.  Localization of Epileptic Foci by Using Convolutional Neural Network Based on iEEG , 2019, AIAI.

[126]  Naoya Higuchi,et al.  Application of Deep Learning in the Identification of Cerebral Hemodynamics Data Obtained from Functional Near-Infrared Spectroscopy: A Preliminary Study of Pre- and Post-Tooth Clenching Assessment , 2020, Journal of clinical medicine.

[127]  Krisnachai Chomtho,et al.  A review of feature extraction and performance evaluation in epileptic seizure detection using EEG , 2019, Biomed. Signal Process. Control..

[128]  Yanli Zhang,et al.  Epileptic Seizure Detection Based on Stockwell Transform and Bidirectional Long Short-Term Memory , 2020, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[129]  Li Fei-Fei,et al.  ImageNet: A large-scale hierarchical image database , 2009, CVPR.

[130]  Jean Gotman,et al.  DeepIED: An epileptic discharge detector for EEG-fMRI based on deep learning , 2017, NeuroImage: Clinical.

[131]  Jeny Rajan,et al.  Automatic detection and localization of Focal Cortical Dysplasia lesions in MRI using fully convolutional neural network , 2019, Biomed. Signal Process. Control..

[132]  Krisnachai Chomtho,et al.  A Comparison of Deep Neural Networks for Seizure Detection in EEG Signals , 2019, bioRxiv.

[133]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[134]  Jasmin Kevric,et al.  Epileptic seizure detection using hybrid machine learning methods , 2017, Neural Computing and Applications.

[135]  Navid Ghassemi,et al.  Deep neural network with generative adversarial networks pre-training for brain tumor classification based on MR images , 2020, Biomed. Signal Process. Control..

[136]  Subhrajit Roy,et al.  SeizureNet: A Deep Convolutional Neural Network for Accurate Seizure Type Classification and Seizure Detection , 2019, ArXiv.

[137]  Ihsan Ullah,et al.  An Automated System for Epilepsy Detection using EEG Brain Signals based on Deep Learning Approach , 2018, Expert Syst. Appl..

[138]  Joseph Picone,et al.  Deep Architectures for Automated Seizure Detection in Scalp EEGs , 2017, ArXiv.

[139]  Arjan Hillebrand,et al.  Simultaneous MEG and EEG to detect ripples in people with focal epilepsy , 2019, Clinical Neurophysiology.

[140]  S. Nahavandi,et al.  Automated Detection and Forecasting of COVID-19 using Deep Learning Techniques: A Review , 2020, ArXiv.

[141]  Ram Bilas Pachori,et al.  Classification of seizure and non-seizure EEG signals based on EMD-TQWT method , 2017, 2017 22nd International Conference on Digital Signal Processing (DSP).

[142]  Yash Paul Various epileptic seizure detection techniques using biomedical signals: a review , 2018, Brain Informatics.

[143]  Martin Valtierra-Rodriguez,et al.  Wavelet Transform-Statistical Time Features-Based Methodology for Epileptic Seizure Prediction Using Electrocardiogram Signals , 2020, Mathematics.

[144]  Dongrui Wu,et al.  Deep Multi-View Feature Learning for EEG-Based Epileptic Seizure Detection , 2019, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[145]  U. Rajendra Acharya,et al.  Deep learning for healthcare applications based on physiological signals: A review , 2018, Comput. Methods Programs Biomed..

[146]  Salvatore Cuomo,et al.  EEG signal analysis for epileptic seizures detection by applying Data Mining techniques , 2019, Internet Things.

[147]  Michel J A M van Putten,et al.  Neonatal seizure detection , 2008, Clinical Neurophysiology.

[148]  Saeid Nahavandi,et al.  Uncertainty-Aware Semi-Supervised Method Using Large Unlabeled and Limited Labeled COVID-19 Data , 2021, ACM Trans. Multim. Comput. Commun. Appl..

[149]  Saeid Nahavandi,et al.  Time series forecasting of new cases and new deaths rate for COVID-19 using deep learning methods , 2021, Results in Physics.

[150]  Junzhong Zou,et al.  Automatic epileptic EEG detection using convolutional neural network with improvements in time-domain , 2019, Biomed. Signal Process. Control..

[151]  Saeid Sanei,et al.  Deep learning for epileptic intracranial EEG data , 2016, 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP).

[152]  Hilal Kaya,et al.  A New Generalized Deep Learning Framework Combining Sparse Autoencoder and Taguchi Method for Novel Data Classification and Processing , 2018, Mathematical Problems in Engineering.

[153]  Jeff Craley,et al.  Integrating Convolutional Neural Networks and Probabilistic Graphical Modeling for Epileptic Seizure Detection in Multichannel EEG , 2019, IPMI.

[154]  George I. Lambrou,et al.  Signal2Image Modules in Deep Neural Networks for EEG Classification , 2019, 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[155]  The-Hanh Pham,et al.  Autism Spectrum Disorder Diagnostic System Using HOS Bispectrum with EEG Signals , 2020, International journal of environmental research and public health.

[156]  Marcello Maggio,et al.  Imaging the Functional Neuroanatomy of Parkinson’s Disease: Clinical Applications and Future Directions , 2021, International journal of environmental research and public health.

[157]  Dario Pompili,et al.  Cloud-based deep learning of big EEG data for epileptic seizure prediction , 2016, 2016 IEEE Global Conference on Signal and Information Processing (GlobalSIP).

[158]  Andreas Schulze-Bonhage,et al.  EPILEPSIAE - A European epilepsy database , 2012, Comput. Methods Programs Biomed..

[159]  Tal Hassner,et al.  Deep Face Recognition: A Survey , 2018, 2018 31st SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI).

[160]  Jinzhao Wu,et al.  A New Approach for Classification of Epilepsy EEG Signals Based on Temporal Convolutional Neural Networks , 2018, 2018 11th International Symposium on Computational Intelligence and Design (ISCID).

[161]  Tingxi Wen,et al.  Deep Convolution Neural Network and Autoencoders-Based Unsupervised Feature Learning of EEG Signals , 2018, IEEE Access.

[162]  Amir F. Atiya,et al.  Handling of uncertainty in medical data using machine learning and probability theory techniques: a review of 30 years (1991–2020) , 2020, Annals of operations research.

[163]  Ke Peng,et al.  Prediction of epileptic seizures with convolutional neural networks and functional near-infrared spectroscopy signals , 2019, Comput. Biol. Medicine.

[164]  Sangdeok Kim,et al.  Epileptic seizure detection for multi-channel EEG with deep convolutional neural network , 2018, 2018 International Conference on Electronics, Information, and Communication (ICEIC).

[165]  Qiang Cheng,et al.  A Novel Independent RNN Approach to Classification of Seizures against Non-seizures , 2019, ArXiv.

[166]  Slim Ben Saoud,et al.  FPGA implementation of EEG signal analysis system for the detection of epileptic seizure , 2018, 2018 International Conference on Advanced Systems and Electric Technologies (IC_ASET).

[167]  Weidong Zhou,et al.  Denoising Sparse Autoencoder-Based Ictal EEG Classification , 2018, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[168]  Jong-Wha Chong,et al.  A Novel Multi-scale 3D CNN with Deep Neural Network for Epileptic Seizure Detection , 2019, 2019 IEEE International Conference on Consumer Electronics (ICCE).

[169]  Victor Alves,et al.  Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images , 2016, IEEE Transactions on Medical Imaging.

[170]  Yonghua Wang,et al.  Scalp EEG epileptogenic zone recognition and localization based on long-term recurrent convolutional network , 2020, Neurocomputing.

[171]  Kebin Jia,et al.  FusionAtt: Deep Fusional Attention Networks for Multi-Channel Biomedical Signals , 2019, Sensors.

[172]  Syed Muhammad Anwar,et al.  Deep Learning Provides Exceptional Accuracy to ECoG-Based Functional Language Mapping for Epilepsy Surgery , 2020, Frontiers in Neuroscience.

[173]  Jeff Craley,et al.  Automated inter-patient seizure detection using multichannel Convolutional and Recurrent Neural Networks , 2021, Biomed. Signal Process. Control..

[174]  Yuanfa Wang,et al.  VLSI Design of SVM-Based Seizure Detection System With On-Chip Learning Capability , 2017, IEEE Transactions on Biomedical Circuits and Systems.

[175]  Wenbin Hu,et al.  Epileptic Signal Classification With Deep EEG Features by Stacked CNNs , 2020, IEEE Transactions on Cognitive and Developmental Systems.

[176]  Andong Wang,et al.  Classification of Epileptic IEEG Signals by CNN and Data Augmentation , 2020, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[177]  Francesco Carlo Morabito,et al.  Information Theoretic-Based Interpretation of a Deep Neural Network Approach in Diagnosing Psychogenic Non-Epileptic Seizures , 2018, Entropy.

[178]  Daniel M Goldenholz,et al.  Machine learning applications in epilepsy , 2019, Epilepsia.

[179]  Khan M. Iftekharuddin,et al.  Deep recurrent neural network for seizure detection , 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

[180]  Saeid Nahavandi,et al.  Applications of Deep Learning Techniques for Automated Multiple Sclerosis Detection Using Magnetic Resonance Imaging: A Review , 2021, Comput. Biol. Medicine.

[181]  R. Lavanya,et al.  Auto-encoder Based Automated Epilepsy Diagnosis , 2018, 2018 International Conference on Advances in Computing, Communications and Informatics (ICACCI).

[182]  Subhrajit Roy,et al.  ChronoNet: A Deep Recurrent Neural Network for Abnormal EEG Identification , 2018, AIME.