Seizure detection, seizure prediction, and closed-loop warning systems in epilepsy

Data Mining: Practical Machine Learning Tools and Techniques

Witten, I. H., Frank, E., & Hall, M. A. (2011) · Elsevier eBooks · doi:10.1016/c2009-0-19715-5 · Cited by 25,543

Book Review: Pattern Recognition and Machine Learning

Nasrabadi, N. M. (2007) · Journal of Electronic Imaging · doi:10.1117/1.2819119 · Cited by 22,066

Pattern Recognition and Machine Learning

(2006) · doi:10.1007/978-0-387-45528-0 · Cited by 9,824

Early Identification of Refractory Epilepsy

Kwan, P., & Brodie, M. J. (2000) · New England Journal of Medicine · doi:10.1056/nejm200002033420503 · Cited by 5,204

Incidence of Epilepsy and Unprovoked Seizures in Rochester, Minnesota: 1935–1984

Hauser, W. A., Annegers, J. F., & Kurland, L. T. (1993) · Epilepsia · doi:10.1111/j.1528-1157.1993.tb02586.x · Cited by 2,084

Responsive cortical stimulation for the treatment of medically intractable partial epilepsy

Morrell, M. J. (2011) · Neurology · doi:10.1212/wnl.0b013e3182302056 · Cited by 1,282

Cardiovascular effects of human insular cortex stimulation

Oppenheimer, S. M., Gelb, A., Girvin, J. P., & Hachinski, V. C. (1992) · Neurology · doi:10.1212/wnl.42.9.1727 · Cited by 1,272

High-performance genetically targetable optical neural silencing by light-driven proton pumps

Chow, B. Y., Han, X., Dobry, A. S., Qian, X., Chuong, A. S., Li, M., Henninger, M. A., Belfort, G. M., Lin, Y., Monahan, P. E., et al. (2010) · Nature · doi:10.1038/nature08652 · Cited by 1,188

Machine Learning: An Algorithmic Perspective

Marsland, S. (2009) · Cited by 1,075

Prediction of seizure likelihood with a long-term, implanted seizure advisory system in patients with drug-resistant epilepsy: a first-in-man study

Cook, M. J., O'Brien, T. J., Berkovic, S. F., Murphy, M. A., Morokoff, A. P., Fabinyi, G., D'Souza, W. J., Yerra, R., Archer, J. S., Litewka, L., et al. (2013) · The Lancet Neurology · doi:10.1016/s1474-4422(13)70075-9 · Cited by 881

Epilepsy

Devinsky, O., Vezzani, A., O'Brien, T. J., Jetté, N., Scheffer, I. E., de Curtis, M., & Perucca, P. (2018) · Nature Reviews Disease Primers · doi:10.1038/nrdp.2018.24 · Cited by 998

A Long Short-Term Memory deep learning network for the prediction of epileptic seizures using EEG signals

Tsiouris, Κ. Μ., Pezoulas, V. C., Zervakis, M. E., Konitsiotis, S., Koutsouris, D., & Fotiadis, D. I. (2018) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2018.05.019 · Cited by 665

The temple university hospital EEG data corpus

Obeid, I., & Picone, J. (2016) · Frontiers in Neuroscience · doi:10.3389/fnins.2016.00196 · Cited by 528

Seizure prediction – ready for a new era

Kuhlmann, L., Lehnertz, K., Richardson, M. P., Schelter, B., & Zaveri, H. P. (2018) · Nature Reviews Neurology · doi:10.1038/s41582-018-0055-2 · Cited by 450

A review of epileptic seizure detection using machine learning classifiers

Siddiqui, M. K., Morales-Menéndez, R., Huang, X., & Hussain, N. (2020) · Brain Informatics · doi:10.1186/s40708-020-00105-1 · Cited by 488

Clinical utility of EEG in diagnosing and monitoring epilepsy in adults

Tatum, W. O., Rubboli, G., Kaplan, P. W., Mirsattari, S., Radhakrishnan, K., Gloss, D. S., Caboclo, L. O. S. F., Drislane, F. W., Koutroumanidis, M., Schomer, D. L., et al. (2018) · Clinical Neurophysiology · doi:10.1016/j.clinph.2018.01.019 · Cited by 323

Epileptic Seizures Prediction Using Deep Learning Techniques

Usman, S. M., Khalid, S., & Aslam, M. H. (2020) · IEEE Access · doi:10.1109/access.2020.2976866 · Cited by 245

Automated seizure detection systems and their effectiveness for each type of seizure

Ulate-Campos, A., Coughlin, F., Gaínza-Lein, M., Fernández, I. S., Pearl, P. L., & Loddenkemper, T. (2016) · Seizure · doi:10.1016/j.seizure.2016.06.008 · Cited by 233

Low-Complexity Seizure Prediction From iEEG/sEEG Using Spectral Power and Ratios of Spectral Power

Zhang, Z., & Parhi, K. K. (2015) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2015.2477264 · Cited by 229

Automated seizure prediction

Acharya, U. R., Hagiwara, Y., & Adeli, H. (2018) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2018.09.030 · Cited by 214

Dynamic coupling between the central and autonomic nervous systems during sleep: a review

de Zambotti, M., Trinder, J., Silvani, A., Colrain, I. M., & Baker, F. C. (2018) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2018.03.027 · Cited by 194

Wearable technology in epilepsy: The views of patients, caregivers, and healthcare professionals

Bruno, E., Simblett, S., Lang, A., Biondi, A., Odoi, C., Schulze-Bonhage, A., Wykes, T., & Richardson, M. P. (2018) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2018.05.044 · Cited by 191

Wearable sensors for clinical applications in epilepsy, Parkinson’s disease, and stroke: A mixed-methods systematic review

Johansson, D., Malmgren, K., & Alt Murphy, M. (2018) · Journal of Neurology · doi:10.1007/s00415-018-8786-y · Cited by 188

A new era in electroencephalographic monitoring? Subscalp devices for ultra–long‐term recordings

Duun‐Henriksen, J., Baud, M. O., Richardson, M. P., Cook, M. J., Kouvas, G., Heasman, J. M., Friedman, D. J., Peltola, J., Zibrandtsen, I. C., & Kjær, T. W. (2020) · Epilepsia · doi:10.1111/epi.16630 · Cited by 183

Epileptic Seizure Prediction Based on Multivariate Statistical Process Control of Heart Rate Variability Features

Fujiwara, K., Miyajima, M., Yamakawa, T., Abe, E., Suzuki, Y., Sawada, Y., Kano, M., Maehara, T., Ohta, K., Sasai-Sakuma, T., et al. (2015) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2015.2512276 · Cited by 177

Electrophoretic drug delivery for seizure control

Proctor, C. M., Slézia, A., Kaszás, A., Ghestem, A., del Agua, I., Pappa, A., Bernard, C., Williamson, A., & Malliaras, G. G. (2018) · Science Advances · doi:10.1126/sciadv.aau1291 · Cited by 174

Classification of epileptic EEG recordings using signal transforms and convolutional neural networks

San-Segundo, R., Gil-Martín, M., D’Haro, L. F., & Pardo, J. M. (2019) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2019.04.031 · Cited by 175

A review of intranasal formulations for the treatment of seizure emergencies

Kapoor, M., Cloyd, J. C., & Siegel, R. A. (2016) · Journal of Controlled Release · doi:10.1016/j.jconrel.2016.07.001 · Cited by 176

Early Seizure Detection Algorithm Based on Intracranial EEG and Random Forest Classification

Donos, C., Dümpelmann, M., & Schulze‐Bonhage, A. (2015) · International Journal of Neural Systems · doi:10.1142/s0129065715500239 · Cited by 157

Flexible Electrodes for In Vivo and In Vitro Electrophysiological Signal Recording

Zhu, M., Wang, H., Li, S., Liang, X., Zhang, M., Dai, X., & Zhang, Y. (2021) · Advanced Healthcare Materials · doi:10.1002/adhm.202100646 · Cited by 163

Seizure detection using wearable sensors and machine learning: Setting a benchmark

Tang, J., El Atrache, R., Yu, S., Asif, U., Jackson, M., Roy, S., Mirmomeni, M., Cantley, S., Sheehan, T., Schubach, S., et al. (2021) · Epilepsia · doi:10.1111/epi.16967 · Cited by 146

Seizure Diaries and Forecasting With Wearables: Epilepsy Monitoring Outside the Clinic

Brinkmann, B. H., Karoly, P. J., Nurse, E. S., Dumanis, S. B., Nasseri, M., Viana, P. F., Schulze‐Bonhage, A., Freestone, D. R., Worrell, G. A., Richardson, M. P., et al. (2021) · Frontiers in Neurology · doi:10.3389/fneur.2021.690404 · Cited by 153

An Effective Dual Self-Attention Residual Network for Seizure Prediction

Yang, X., Zhao, J., Sun, Q. L., Lu, J., & Ma, X. (2021) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2021.3103210 · Cited by 147

Evaluating five different adaptive decomposition methods for EEG signal seizure detection and classification

Carvalho, V. R., Moraes, M. F. D., Braga, A. P., & Mendes, E. M. A. M. (2020) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2020.102073 · Cited by 153

FPGA-based real-time epileptic seizure classification using Artificial Neural Network

Sarić, R., Jokić, D. Ž., Beganović, N., Pokvić, L. G., & Badnjević, A. (2020) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2020.102106 · Cited by 137

Seizure detection using scalp‐ EEG

Baumgartner, C., & Koren, J. P. (2018) · Epilepsia · doi:10.1111/epi.14052 · Cited by 136

Non-EEG seizure detection systems and potential SUDEP prevention: State of the art

de Vel, A. V., Cuppens, K., Bonroy, B., Milošević, M., Jansen, K., Huffel, S. V., Vanrumste, B., Cras, P. P., Lagae, L., & Ceulemans, B. (2016) · Seizure · doi:10.1016/j.seizure.2016.07.012 · Cited by 117

Novel techniques for automated seizure registration: Patients' wants and needs

Hoppe, C., Feldmann, M., Blachut, B., Surges, R., Elger, C. E., & Helmstaedter, C. (2015) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2015.08.006 · Cited by 116

Forecasting cycles of seizure likelihood

Karoly, P. J., Cook, M. J., Maturana, M. I., Nurse, E. S., Payne, D. E., Brinkmann, B. H., Grayden, D. B., Dumanis, S. B., Richardson, M. P., Worrell, G. A., et al. (2020) · Epilepsia · doi:10.1111/epi.16485 · Cited by 110

Detection of Epileptic Seizures Using Phase–Amplitude Coupling in Intracranial Electroencephalography

Edakawa, K., Yanagisawa, T., Kishima, H., Fukuma, R., Oshino, S., Khoo, H. M., Kobayashi, M., Tanaka, M., & Yoshimine, T. (2016) · Scientific Reports · doi:10.1038/srep25422 · Cited by 114

Crowdsourcing seizure detection: algorithm development and validation on human implanted device recordings

Baldassano, S. N., Brinkmann, B. H., Ung, H., Blevins, T., Conrad, E. C., Leyde, K. W., Cook, M. J., Khambhati, A. N., Wagenaar, J., Worrell, G. A., et al. (2017) · Brain · doi:10.1093/brain/awx098 · Cited by 113

FGANet: fNIRS-Guided Attention Network for Hybrid EEG-fNIRS Brain-Computer Interfaces

Kwak, Y., Song, W., & Kim, S. (2022) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2022.3149899 · Cited by 113

Reflex seizures, traits, and epilepsies: from physiology to pathology

Koepp, M. J., Caciagli, L., Pressler, R., Lehnertz, K., & Beniczky, S. (2015) · The Lancet Neurology · doi:10.1016/s1474-4422(15)00219-7 · Cited by 117

Non-EEG seizure-detection systems and potential SUDEP prevention: State of the art

de Vel, A. V., Cuppens, K., Bonroy, B., Milošević, M., Jansen, K., Huffel, S. V., Vanrumste, B., Lagae, L., & Ceulemans, B. (2013) · Seizure · doi:10.1016/j.seizure.2013.02.012 · Cited by 109

EEG-Based Seizure detection using linear graph convolution network with focal loss

Zhao, Y., Dong, C., Zhang, G., Wang, Y., Chen, X., Jia, W., Yuan, Q., Xu, F., & Zheng, Y. (2021) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2021.106277 · Cited by 105

Emergency management of febrile status epilepticus: Results of the FEBSTAT study

Seinfeld, S. A., Shinnar, S., Sun, S. S., Hesdorffer, D. C., Deng, X., Shinnar, R. C., O’Hara, K., Nordli, D. R., Frank, L. M., Gallentine, W. B., et al. (2014) · Epilepsia · doi:10.1111/epi.12526 · Cited by 105

Automatic Analysis of EEGs Using Big Data and Hybrid Deep Learning Architectures

Golmohammadi, M., Torbati, A. H. H. N., de Diego, S. L., Obeid, I., & Picone, J. (2019) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2019.00076 · Cited by 111

Automated Detection of Convulsive Seizures Using a Wearable Accelerometer Device

Kusmakar, S., Karmakar, C. K., Yan, B., O'Brien, T. J., Muthuganapathy, R., & Palaniswami, M. S. (2018) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2018.2845865 · Cited by 101

Neuroelectronics and Biooptics

Krook-Magnuson, E. I., Gelinas, J. N., Soltész, I., & Buzsáki, G. (2015) · JAMA Neurology · doi:10.1001/jamaneurol.2015.0608 · Cited by 98

Automatic detection of abnormal EEG signals using wavelet feature extraction and gradient boosting decision tree

Albaqami, H., Hassan, G. M., Subaşı, A., & Datta, A. (2021) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2021.102957 · Cited by 97

Epilepsy detection in 121 patient populations using hypercube pattern from EEG signals

Taşçı, İ., Taşçı, B., Barua, P. D., Doğan, Ş., Tuncer, T., Palmer, E. E., Fujita, H., & Acharya, U. R. (2023) · Information Fusion · doi:10.1016/j.inffus.2023.03.022 · Cited by 95

Epileptic seizure detection and prediction using stacked bidirectional long short term memory

D.K., T., B.G., P., & Xiong, F. (2019) · Pattern Recognition Letters · doi:10.1016/j.patrec.2019.10.034 · Cited by 93

Timing in the treatment of status epilepticus: From basics to the clinic

Gaínza‐Lein, M., Fernández, I. S., Ulate-Campos, A., Loddenkemper, T., & Ostendorf, A. P. (2018) · Seizure · doi:10.1016/j.seizure.2018.05.021 · Cited by 90

A Comprehensive Review of Emerging Trends and Innovative Therapies in Epilepsy Management

Ghosh, S., Sinha, J. K., Ghosh, S. K., Sharma, H., Bhaskar, R., & Narayanan, K. B. (2023) · Brain Sciences · doi:10.3390/brainsci13091305 · Cited by 96

The Emergence of Single Neurons in Clinical Neurology

Cash, S. S., & Hochberg, L. R. (2015) · Neuron · doi:10.1016/j.neuron.2015.03.058 · Cited by 87

Deep Classification of Epileptic Signals

Ahmedt‐Aristizabal, D., Fookes, C., Nguyen, K., & Sridharan, S. (2018) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2018.8512249 · Cited by 89

Silicon-Integrated High-Density Electrocortical Interfaces

Ha, S., Akinin, A., Park, J., Kim, C., Wang, H., Maier, C., Mercier, P. P., & Cauwenberghs, G. (2016) · Proceedings of the IEEE · doi:10.1109/jproc.2016.2587690 · Cited by 84

Using scalp EEG and intracranial EEG signals for predicting epileptic seizures: Review of available methodologies

Usman, S. M., Khalid, S., Akhtar, R., Bortolotto, Z. A., Bashir, Z. I., & Qiu, H. (2019) · Seizure · doi:10.1016/j.seizure.2019.08.006 · Cited by 84

A GENERALIZABLE MODEL FOR SEIZURE PREDICTION BASED ON DEEP LEARNING USING CNN-LSTM ARCHITECTURE

Shahbazi, M., & Aghajan, H. K. (2018) · IEEE Global Conference on Signal and Information Processing · doi:10.1109/globalsip.2018.8646505 · Cited by 83

A hybrid Local Binary Pattern and wavelets based approach for EEG classification for diagnosing epilepsy

Khan, K. A., Shanir, P. P. M., Khan, Y. U., & Farooq, O. (2019) · Expert Systems with Applications · doi:10.1016/j.eswa.2019.112895 · Cited by 81

Seizure prediction in patients with focal hippocampal epilepsy

Aarabi, A., & He, B. (2017) · Clinical Neurophysiology · doi:10.1016/j.clinph.2017.04.026 · Cited by 80

Closed-Loop Neuromodulation in Physiological and Translational ResearchPreprint

Zanos, S. P. (2018) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a034314 · Cited by 89

Non-EEG based ambulatory seizure detection designed for home use: What is available and how will it influence epilepsy care?

van Andel, J. M., Thijs, R. D., de Weerd, A., Arends, J. B. A. M., & Leijten, F. S. S. (2016) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2016.01.003 · Cited by 78

On the proper selection of preictal period for seizure prediction

Bandarabadi, M., Rasekhi, J., Teixeira, C., Karami, M. R., & Dourado, A. (2015) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2015.03.010 · Cited by 76

Multimodal seizure detection: A review

Leijten, F. S. S. (2018) · Epilepsia · doi:10.1111/epi.14047 · Cited by 78

Residual and bidirectional LSTM for epileptic seizure detection

Zhao, W., Wang, W., Patnaik, L. M., Zhang, B., Weng, S.-J., Xiao, S., Wei, D., & Zhou, H.-F. (2024) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2024.1415967 · Cited by 86

Wearable Epileptic Seizure Prediction System with Machine-Learning-Based Anomaly Detection of Heart Rate Variability

Yamakawa, T., Miyajima, M., Fujiwara, K., Kano, M., Suzuki, Y., Watanabe, Y., Watanabe, S., Hoshida, T., Inaji, M., & Maehara, T. (2020) · Sensors · doi:10.3390/s20143987 · Cited by 74

Why Does the Cortex Reorganize after Sensory Loss?

Kalia, A., Phillips, F., Merabet, L. B., & Sinha, P. (2018) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2018.04.004 · Cited by 82

Gated recurrent networks for seizure detection

Golmohammadi, M., Ziyabari, S., Shah, V., von Weltin, E., Campbell, C., Obeid, I., & Picone, J. (2017) · IEEE Signal Processing in Medicine and Biology Symposium · doi:10.1109/spmb.2017.8257020 · Cited by 74

Patient-centered design criteria for wearable seizure detection devices

Patel, A. D., Moss, R., Rust, S. W., Patterson, J., Strouse, R., Gedela, S., Haines, J., & Lin, S. M. (2016) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2016.09.012 · Cited by 72

EEG analysis of seizure patterns using visibility graphs for detection of generalized seizures

Wang, L., Long, X., Arends, J. B. A. M., & Aarts, R. M. (2017) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2017.07.013 · Cited by 69

Seizure reporting technologies for epilepsy treatment: A review of clinical information needs and supporting technologies

Bidwell, J., Khuwatsamrit, T., Askew, B., Ehrenberg, J. A., & Helmers, S. L. (2015) · Seizure · doi:10.1016/j.seizure.2015.09.006 · Cited by 68

Deep learning for robust detection of interictal epileptiform discharges

Geng, D., Alkhachroum, A. M., Bicchi, M. M., Jagid, J. R., Cajigas, I., & Chen, Z. S. (2021) · Journal of Neural Engineering · doi:10.1088/1741-2552/abf28e · Cited by 67

Classification of EEG Signals for Prediction of Epileptic Seizures

Aslam, M. H., Usman, S. M., Khalid, S., Anwar, A., Alroobaea, R., Hussain, S., Almotiri, J., Ullah, S. S., & Yasin, A. (2022) · Applied Sciences · doi:10.3390/app12147251 · Cited by 68

Automated analysis of seizure semiology and brain electrical activity in presurgery evaluation of epilepsy: A focused survey

Ahmedt‐Aristizabal, D., Fookes, C., Dionisio, S. A., Nguyen, K., Cunha, J. P. S., & Sridharan, S. (2017) · Epilepsia · doi:10.1111/epi.13907 · Cited by 68

Epileptic Seizure Detection and Experimental Treatment: A Review

Kim, T.-H., Nguyen, P., Pham, N., Bui, N., Truong, H., Ha, S., & Vu, T. N. (2020) · Frontiers in Neurology · doi:10.3389/fneur.2020.00701 · Cited by 69

Manifold Learning for Latent Variable Inference in Dynamical Systems

Talmon, R., Mallat, S., Zaveri, H. P., & Coifman, R. R. (2015) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2015.2432731 · Cited by 67

Intelligent automated drug administration and therapy: future of healthcare

Sharma, R., Singh, D., Gaur, P., & Joshi, D. (2021) · Drug Delivery and Translational Research · doi:10.1007/s13346-020-00876-4 · Cited by 68

Artificial intelligence‐enhanced epileptic seizure detection by wearables

Yu, S., Atrache, R. E., Tang, J., Jackson, M. C., Makarucha, A. J., Cantley, S., Sheehan, T., Vieluf, S., Zhang, B., Rogers, J. L., et al. (2023) · Epilepsia · doi:10.1111/epi.17774 · Cited by 64

A Generalised Seizure Prediction with Convolutional Neural Networks for Intracranial and Scalp Electroencephalogram Data AnalysisPreprint

Truong, N. D., Nguyen, A. D., Kuhlmann, L., Bonyadi, M. R., Yang, J., & Kavehei, O. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1707.01976 · Cited by 64

Generalized Models for the Classification of Abnormal Movements in Daily Life and its Applicability to Epilepsy Convulsion Recognition

Villar, J. R., Vergara, P. M., Menéndez‐González, M., de la Cal, E., González, V. M., & Sedano, J. (2016) · International Journal of Neural Systems · doi:10.1142/s0129065716500374 · Cited by 64

A personalized and evolutionary algorithm for interpretable EEG epilepsy seizure prediction

Pinto, M. F., Leal, A., Lopes, F., Dourado, A., Martins, P., & Teixeira, C. (2021) · Scientific Reports · doi:10.1038/s41598-021-82828-7 · Cited by 63

Theoretical and methodological analysis of EEG based seizure detection and prediction: An exhaustive review

Cherian, R., & Kanaga, E. G. M. (2022) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2022.109483 · Cited by 63

Role of Artificial Intelligence in Fighting Antimicrobial Resistance in Pediatrics

Fanelli, U., Pappalardo, M., Chiné, V., Gismondi, P., Neglia, C., Argentiero, A., Calderaro, A., Prati, A., & Esposito, S. (2020) · Antibiotics · doi:10.3390/antibiotics9110767 · Cited by 61

An Overview of EEG-based Machine Learning Methods in Seizure Prediction and Opportunities for Neurologists in this Field

Maimaiti, B., Meng, H., Lv, Y., Qiu, J., Zhu, Z., Xie, Y., Li, Y., Yu-Cheng, Zhao, W., Liu, J., et al. (2021) · Neuroscience · doi:10.1016/j.neuroscience.2021.11.017 · Cited by 62

Sustained efficacy of closed loop electrical stimulation for long-term treatment of absence epilepsy in rats

Kozák, G., & Berényi, A. (2017) · Scientific Reports · doi:10.1038/s41598-017-06684-0 · Cited by 60

Hitting the brakes: pathological subthalamic nucleus activity in Parkinson’s disease gait freezing

Georgiades, M., Shine, J. M., Gilat, M., McMaster, J., Owler, B., Mahant, N., & Lewis, S. J. G. (2019) · Brain · doi:10.1093/brain/awz325 · Cited by 59

Semi-supervised automatic seizure detection using personalized anomaly detecting variational autoencoder with behind-the-ear EEG

You, S., Cho, B. H., Shon, Y., Seo, D., & Kim, I. Y. (2021) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2021.106542 · Cited by 58

A Comparison of Machine Learning Classifiers for Energy-Efficient Implementation of Seizure Detection

Manzouri, F., Heller, S., Dümpelmann, M., Woias, P., & Schulze‐Bonhage, A. (2018) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2018.00043 · Cited by 57

Prediction of epileptic seizures with convolutional neural networks and functional near-infrared spectroscopy signals

Rosas-Romero, R., Guevara, E., Peng, K., Nguyen, D. K., Lesage, F., Pouliot, P., & Lima-Saad, W.-E. (2019) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2019.103355 · Cited by 60

Predicting Short-term Survival after Liver Transplantation using Machine Learning

Liu, C., Soong, R., Lee, W., Jiang, G.-W., & Lin, Y.-C. (2020) · Scientific Reports · doi:10.1038/s41598-020-62387-z · Cited by 58

Artificial Intelligence in Epilepsy

Kaur, T., Diwakar, A., Kirandeep, K., Mirpuri, P., Tripathi, M., Chandra, P. S., & Gandhi, T. K. (2021) · Neurology India · doi:10.4103/0028-3886.317233 · Cited by 56

An IoT Platform for Epilepsy Monitoring and Supervising

Vergara, P. M., de la Cal, E., Villar, J. R., González, V. M., & Sedano, J. (2017) · Journal of Sensors · doi:10.1155/2017/6043069 · Cited by 56

A European survey on current practices in epilepsy monitoring units and implications for patients' safety

Rubboli, G., Beniczky, S., Claus, S. P., Canevini, M. P., Kahane, P., Stefan, H., Boas, W. V. E., Velis, D. N., Reus, E., Gil‐Nagel, A., et al. (2015) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2015.02.004 · Cited by 54

Brain–Computer Interface (BCI) Applications in Mapping of Epileptic Brain Networks Based on Intracranial-EEG: An Update

Alkawadri, R. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00191 · Cited by 53

Epileptic seizure onset detection based on EEG and ECG data fusion

Qaraqe, M., Ismail, M., Serpedin, E., & Haneef, Z. (2016) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2016.02.039 · Cited by 52

An Automatic Prediction of Epileptic Seizures Using Cloud Computing and Wireless Sensor Networks

Sareen, S., Sood, S. K., & Gupta, S. K. (2016) · Journal of Medical Systems · doi:10.1007/s10916-016-0579-1 · Cited by 52

Real-time seizure prediction using RLS filtering and interpolated histogram feature based on hybrid optimization algorithm of Bayesian classifier and Hunting search

Behnam, M., & Pourghassem, H. (2016) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2016.04.014 · Cited by 51

Early Seizure Detection with an Energy-Efficient Convolutional Neural Network on an Implantable Microcontroller

Hugle, M., Heller, S., Watter, M., Blum, M., Manzouri, F., Dumpelmann, M., Schulze‐Bonhage, A., Woias, P., & Boedecker, J. (2018) · International Joint Conference on Neural Networks (IJCNN) · doi:10.1109/ijcnn.2018.8489493 · Cited by 50

A framework for seizure detection using effective connectivity, graph theory, and multi-level modular network

Akbarian, B., & Erfanian, A. (2020) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2020.101878 · Cited by 50

Seizure Forecasting and the Preictal State in Canine Epilepsy

Varatharajah, Y., Iyer, R. K., Berry, B. M., Worrell, G. A., & Brinkmann, B. H. (2016) · International Journal of Neural Systems · doi:10.1142/s0129065716500465 · Cited by 51

Deep Architectures for Automated Seizure Detection in Scalp EEGsPreprint

Golmohammadi, M., Ziyabari, S., Shah, V., de Diego, S. L., Obeid, I., & Picone, J. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1712.09776 · Cited by 51

Shorter latency of real-time epileptic seizure detection via probabilistic prediction

Xu, Y., Yang, J., Ming, W., Wang, S., & Sawan, M. (2023) · Expert Systems with Applications · doi:10.1016/j.eswa.2023.121359 · Cited by 47

Time Series Classification by Sequence Learning in All-Subsequence Space

Nguyen, T. L., Gsponer, S., & Ifrim, G. (2017) · IEEE International Conference on Data Engineering (ICDE) · doi:10.1109/icde.2017.142 · Cited by 48

Deep Architectures for Spatio-Temporal Modeling: Automated Seizure Detection in Scalp EEGs

Golmohammadi, M., Ziyabari, S., Shah, V., Obeid, I., & Picone, J. (2018) · International Conference on Machine Learning and Applications · doi:10.1109/icmla.2018.00118 · Cited by 47

Automated Pain Assessment in Children Using Electrodermal Activity and Video Data Fusion via Machine Learning

Susam, B. T., Riek, N. T., Akçakaya, M., Xu, X., de Sa, V. R., Nezamfar, H., Díaz, D., Craig, K. D., Goodwin, M. S., & Huang, J. S. (2021) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2021.3096137 · Cited by 47

Early seizure detection for closed loop direct neurostimulation devices in epilepsy

Dümpelmann, M. (2019) · Journal of Neural Engineering · doi:10.1088/1741-2552/ab094a · Cited by 47

A review on the pattern detection methods for epilepsy seizure detection from EEG signals

Sharmila, A., & Geethanjali, P. (2019) · Biomedizinische Technik/Biomedical Engineering · doi:10.1515/bmt-2017-0233 · Cited by 46

Capturing time-varying brain dynamics

Lehnertz, K., Geier, C., Rings, T., & Stahn, K. (2017) · EPJ Nonlinear Biomedical Physics · doi:10.1051/epjnbp/2017001 · Cited by 48

Seizure prediction: Methods

Carney, P. R., Myers, S. M., & Geyer, J. D. (2011) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2011.09.001 · Cited by 121

Status epilepticus prevention, ambulatory monitoring, early seizure detection and prediction in at-risk patients

Amengual‐Gual, M., Ulate-Campos, A., & Loddenkemper, T. (2018) · Seizure · doi:10.1016/j.seizure.2018.09.013 · Cited by 38

Automated seizure prediction

Acharya, U. R., Hagiwara, Y., & Adeli, H. (2018) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2018.09.030 · Cited by 214

EEG seizure detection and prediction algorithms: a survey

Alotaiby, T. N., Alshebeili, S. A., Alshawi, T. A., Ahmad, I., & El‐Samie, F. E. A. (2014) · EURASIP Journal on Advances in Signal Processing · doi:10.1186/1687-6180-2014-183 · Cited by 293

Epileptic seizure prediction using EEG signals - a survey

Sharma, A. (2025) · International Journal of Biomedical Engineering and Technology · doi:10.1504/ijbet.2025.150081