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

Seizario: Novel Mobile Algorithms for Seizure and Fall Detection

Helmy, A., & Helmy, A. (2015) · IEEE Globecom Workshops (GC Wkshps) · doi:10.1109/glocomw.2015.7414193 · Cited by 15

Phase-amplitude coupling between infraslow and high-frequency activities well discriminates between the preictal and interictal states

Hashimoto, H., Khoo, H. M., Yanagisawa, T., Tani, N., Oshino, S., Kishima, H., & Hirata, M. (2021) · Scientific Reports · doi:10.1038/s41598-021-96479-1 · Cited by 15

A Wearable ForeSeiz Headband for Forecasting Real-Time Epileptic Seizures

Prathaban, B. P., Баласубраманиан, Р., & Kalpana, R. (2021) · IEEE Sensors Journal · doi:10.1109/jsen.2021.3120307 · Cited by 15

EEG-based seizure detection in patients with intellectual disability: Which EEG and clinical factors are important?

Wang, L., Long, X., Aarts, R. M., van Dijk, J. P., & Arends, J. B. A. M. (2018) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2018.12.003 · Cited by 15

Performance analysis of EEG seizure detection features

Niknazar, H., Mousavi, S. R., Niknazar, M., Mardanlou, V., & Coelho, B. N. (2020) · Epilepsy Research · doi:10.1016/j.eplepsyres.2020.106483 · Cited by 15

Detection of Generalized Tonic Clonic Seizures and Falls in Unconstraint Environment Using Smartphone Accelerometer

Zia, S., Khan, A. N., Zaidi, S., & Ali, S. E. (2021) · IEEE Access · doi:10.1109/access.2021.3063765 · Cited by 14

Cloud-based mobile platform for EEG signal analysis

Emir, D., Vrtagić, S., Bandić, L., Kevrić, J., Subaşı, A., & Qaisar, S. M. (2016) · International Conference on Electronic Devices, Systems and Applications · doi:10.1109/icedsa.2016.7818497 · Cited by 14

Epileptic seizure prediction using power analysis in beta band of EEG signals

Sharma, A. (2015) · International Conference on Soft Computing Techniques and Implementations (ICSCTI) · doi:10.1109/icscti.2015.7489552 · Cited by 14

Seizure-specific wavelet (Seizlet) design for epileptic seizure detection using CorrEntropy ellipse features based on seizure modulus maximas patterns

Behnam, M., & Pourghassem, H. (2016) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2016.10.011 · Cited by 14

Adaptive Epileptic Seizure Prediction Based on EEG Synchronization

Ibrahim, S., & Majzoub, S. (2017) · Journal of biomimetics, biomaterials and biomedical engineering · doi:10.4028/www.scientific.net/jbbbe.33.52 · Cited by 14

Seizure detection and epileptogenic zone localisation on heavily skewed MEG data using RUSBoost machine learning technique

Bhanot, N., Mariyappa, N., Anitha, H., Bhargava, G. K., Velmurugan, J., & Sinha, S. (2020) · International Journal of Neuroscience · doi:10.1080/00207454.2020.1858828 · Cited by 13

An approach to detect and predict epileptic seizures with high accuracy using convolutional neural networks and single-lead-ECG signal

Ghaempour, M., Hassanli, K., & Abiri, E. (2024) · Biomedical Physics & Engineering Express · doi:10.1088/2057-1976/ad29a3 · Cited by 13

Fusion Algorithm for Imbalanced EEG Data Processing in Seizure Detection

Jiang, Z., & Zhao, W. (2021) · Seizure · doi:10.1016/j.seizure.2021.06.023 · Cited by 13

Ambulatory EEG: Crossing the divide during a pandemic

Tatum, W. O., Desai, N. N., & Feyissa, A. M. (2021) · Epilepsy & Behavior Reports · doi:10.1016/j.ebr.2021.100500 · Cited by 13

Detect, predict, and prevent acute seizures and status epilepticus

Loddenkemper, T. (2023) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2023.109141 · Cited by 13

Towards an Online Seizure Advisory System—An Adaptive Seizure Prediction Framework Using Active Learning Heuristics

Ramachandran, V. R. K., Alblas, H. J., Le, D. V., & Meratnia, N. (2018) · Sensors · doi:10.3390/s18061698 · Cited by 13

Feasibility of Nitrogen Doped Ultrananocrystalline Diamond Microelectrodes for Electrophysiological Recording From Neural Tissue

Wong, Y. T., Ahnood, A., Maturana, M. I., Kentler, W. G., Ganesan, K., Grayden, D. B., Hamish Meffin, A., Prawer, S., Ibbotson, M. R., & Burkitt, A. N. (2018) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2018.00085 · Cited by 14

Prediction of epileptic seizures using fNIRS and machine learning

Guevara, E., Flores-Castro, J.-A., Peng, K., Nguyen, D. K., Lesage, F., Pouliot, P., & Rosas-Romero, R. (2019) · Journal of Intelligent & Fuzzy Systems · doi:10.3233/jifs-190738 · Cited by 13

Effects of epileptic seizures on the quality of biosignals recorded from wearables

Böttcher, S., Zabler, N., Jackson, M. C., Bruno, E., Biondi, A., Epitashvili, N., Vieluf, S., Dümpelmann, M., Richardson, M. P., Brinkmann, B. H., et al. (2024) · Epilepsia · doi:10.1111/epi.18138 · Cited by 11

Microneedle electrodes: materials, fabrication methods, and electrophysiological signal monitoring-narrative review

Singh, O. P., El-Badawy, I. M., Sornambikai, S., & O’Mahony, C. (2025) · Biomedical Microdevices · doi:10.1007/s10544-024-00732-z · Cited by 13

Low-cost wearable bluetooth sensor for epileptic episodes detection

Ramirez-Alaminos, J. M., Sendra, S., Lloret, J., & Navarro‐Ortiz, J. (2017) · International Conference on Communications · doi:10.1109/icc.2017.7997413 · Cited by 12

Epilepsy EEG classification using morphological component analysis

Mahapatra, A. G., Singh, B., Wagatsuma, H., & Horio, K. (2018) · EURASIP Journal on Advances in Signal Processing · doi:10.1186/s13634-018-0568-2 · Cited by 12

Optical Flow Estimation Improves Automated Seizure Detection in Neonatal EEG

Martin, J. R., Gabriel, P., Gold, J. J., Haas, R., Davis, S. L., Gonda, D. D., Sharpe, C. M., Wilson, S. B., Nierenberg, N. C., Scheuer, M. L., et al. (2020) · Journal of Clinical Neurophysiology · doi:10.1097/wnp.0000000000000767 · Cited by 12

Sensing and Monitoring of Epileptical Seizure Under IoT Platform

Gupta, A. K., Chakraborty, C., & Gupta, B. (2019) · Advances in healthcare information systems and administration book series · doi:10.4018/978-1-7998-0261-7.ch009 · Cited by 12

Deep learning–based detection of generalized convulsive seizures using a wrist‐worn accelerometer

Spahr, A., Bernini, A., Ducouret, P., Baumgartner, C., Koren, J. P., Imbach, L., Beniczky, S., Larsen, S. A., Rheims, S., Fabricius, M. E., et al. (2025) · Epilepsia · doi:10.1111/epi.18406 · Cited by 13

Advancements and Challenges of Artificial Intelligence-Assisted Electroencephalography in Epilepsy Management

Chen, Y., Ou, Z., Zhou, D., & Wu, X. (2025) · Journal of Clinical Medicine · doi:10.3390/jcm14124270 · Cited by 11

Automatic epileptic seizure detection with an ultra lightweight 3D-CNN model

Xie, C., Qiu, S., Zhou, C., Song, X., Yang, J., Huang, J., Wang, W., & Jiao, H. (2025) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2025.108260 · Cited by 11

Big data in status epilepticus

Baldassano, S. N., Hill, C. E., Shankar, A., Bernabei, J. M., Khankhanian, P., & Litt, B. (2019) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2019.106457 · Cited by 11

Attention-based Graph ResNet with focal loss for epileptic seizure detection

Dong, C., Zhao, Y., Zhang, G., Xue, M., Chu, D., He, J., & Ge, X. (2021) · Journal of Ambient Intelligence and Smart Environments · doi:10.3233/ais-210086 · Cited by 11

Application of identity vectors for EEG classification

Ward, C. R., & Iyad Obeid, A. (2018) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2018.09.015 · Cited by 11

Innovations in the Neurosurgical Management of Epilepsy

Hoffman, C. E., Parker, W. E., Rapoport, B. I., Zhao, M., Ma, H., & Schwartz, T. H. (2020) · World Neurosurgery · doi:10.1016/j.wneu.2020.03.031 · Cited by 11

Exploring human epileptic activity at the single-neuron level

Tankus, A. (2016) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2016.02.014 · Cited by 12

Predictive modeling of evoked intracranial EEG response to medial temporal lobe stimulation in patients with epilepsy

Acharya, G., Davis, K. A., & Nozari, E. (2024) · Communications Biology · doi:10.1038/s42003-024-06859-2 · Cited by 10

Identification of abnormal movements with 3D accelerometer sensors for seizure recognition

Villar, J. R., Menéndez‐González, M., de la Cal, E., Sedano, J., & González, V. M. (2016) · Journal of Applied Logic · doi:10.1016/j.jal.2016.11.024 · Cited by 10

Epileptic seizure detection based on video and EEG recordings

Aghaei, H., Kiani, M. M., & Aghajan, H. K. (2017) · IEEE Biomedical Circuits and Systems Conference (BioCAS) · doi:10.1109/biocas.2017.8325156 · Cited by 10

A Channel Selection Method for Epileptic EEG Signals

Chakrabarti, S., Swetapadma, A., & Pattnaik, P. K. (2018) · Advances in intelligent systems and computing · doi:10.1007/978-981-13-1951-8_51 · Cited by 10

Epileptic seizure prediction and identification of epileptogenic region using EEG signal

Sharma, A., Rai, J. K., & Tewari, R. P. (2015) · International Conference on Green Computing and Internet of Things (ICGCIoT) · doi:10.1109/icgciot.2015.7380644 · Cited by 10

Detecting changes in transient complex systems via dynamic network inference

Tran, H. M., Bukkapatnam, S., & Garg, M. (2018) · IISE Transactions · doi:10.1080/24725854.2018.1491075 · Cited by 10

Automated Epileptic Seizure Detection System Based on a Wearable Prototype and Cloud Computing to Assist People with Epilepsy

Cruz, N. E., Solarte, J., & González‐Vargas, A. M. (2018) · Communications in computer and information science · doi:10.1007/978-3-030-00353-1_18 · Cited by 10

MFCC-CNN: A patient-independent seizure prediction model

Zhang, F., Zhang, B., Guo, S., & Zhang, X. (2024) · Neurological Sciences · doi:10.1007/s10072-024-07718-y · Cited by 9

Implementing a Smart Method to Eliminate Artifacts of Vital Signals.

Javadpour, A., & Mohammadi, A. (2015) · PubMed Central · Cited by 9

Detection of preictal state in epileptic seizures using ensemble classifier

Usman, S. M., Khalid, S., Jabbar, S., & Bashir, S. (2021) · Epilepsy Research · doi:10.1016/j.eplepsyres.2021.106818 · Cited by 9

A hybrid complex-valued neural network framework with applications to electroencephalogram (EEG)

Du, H., Riddell, R. P., & Wang, X. (2023) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2023.104862 · Cited by 12

Devices for Ambulatory Monitoring of Sleep-Associated Disorders in Children with Neurological Diseases

Ulate-Campos, A., Tsuboyama, M., & Loddenkemper, T. (2017) · Children · doi:10.3390/children5010003 · Cited by 9

E EG - Based Epileptic Seizures Detection with Adaptive Learning Capability

Ibrahim, S., & Majzoub, S. (2017) · International Journal on Electrical Engineering and Informatics · doi:10.15676/ijeei.2017.9.4.13 · Cited by 9

Noninvasive Seizure Localization With Single-Photon Emission Computed Tomography Is Impacted by Preictal/Early Ictal Network Dynamics

Stamoulis, C., Connolly, J., Axeen, E. T., Kaulas, H., Bolton, J. B., Dorfman, K., Halford, J. J., Duffy, F. H., Treves, S. T., & Pearl, P. L. (2018) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2018.2880575 · Cited by 9

A Review on Epileptic Seizure Detection and Prediction Using Soft Computing Techniques

Chakrabarti, S., Swetapadma, A., & Pattnaik, P. K. (2019) · Studies in fuzziness and soft computing · doi:10.1007/978-3-030-03131-2_3 · Cited by 9

A New Wavelet-Based Neural Network for Classification of Epileptic-Related States using EEG

Guerra, E. J., Alarcon‐Aquino, V., Gómez‐Gil, P., Ramírez-Cortés, J. M., & García-Treviño, E. S. (2019) · Journal of Signal Processing Systems · doi:10.1007/s11265-019-01456-7 · Cited by 9

Application of self-organizing map to identify nocturnal epileptic seizures

Pisano, B., Teixeira, C., Dourado, A., & Fanni, A. (2019) · Neural Computing and Applications · doi:10.1007/s00521-019-04327-1 · Cited by 9

Deep Learning Approaches for Epileptic Seizure Prediction: A Review

Soliman, S., Fouad, A. M., Mourad, E., Hossam, S., Ehab, M., Selim, S., & Darweesh, M. S. (2022) · Novel Intelligent and Leading Emerging Sciences Conference (NILES) · doi:10.1109/niles56402.2022.9942420 · Cited by 8

Primary payer status in patients with seizures: A nationwide study during 1997-2014 in the United States

Eslami, V., Stowers, J. A., Afra, P., & Seifi, A. (2021) · Epilepsy Research · doi:10.1016/j.eplepsyres.2020.106501 · Cited by 8

Epileptic seizure prediction based on features extracted from lagged Poincaré plots

Behbahani, S., Dabanloo, N. J., Nasrabadi, A. M., & Dourado, A. (2022) · International Journal of Neuroscience · doi:10.1080/00207454.2022.2106435 · Cited by 8

Deep brain stimulation probing performance is enhanced by pairing stimulus with epileptic seizure

Medeiros, D. D. C., Raspante, L. B. D. P., Mourão, F. A. G., Carvalho, V. R., Mendes, E. M. A. M., & Moraes, M. F. D. (2018) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2018.09.048 · Cited by 8

Sounds of seizures

Shum, J. W. H., Fogarty, A. S., Dugan, P. C., Holmes, M., Leeman-Markowski, B. A., Liu, A. A., Fisher, R. S., & Friedman, D. J. (2020) · Seizure · doi:10.1016/j.seizure.2020.03.008 · Cited by 8

Epilepsy Seizure Detection: A Heavy Tail Approach

Servín-Aguilar, J. G., Rizo-Domínguez, L., Pardiñas-Mir, J. A., Vargas‐Rosales, C., & Padilla-Cantoya, I. R. (2020) · IEEE Access · doi:10.1109/access.2020.3038397 · Cited by 8

A multimodal, implantable sensor array and measurement system to investigate the suppression of focal epileptic seizure using hypothermia

Csernyus, B., Szabó, Á., Fiáth, R., Zátonyi, A., Lázár, C., Pongracz, A., & Fekete, Z. (2021) · Journal of Neural Engineering · doi:10.1088/1741-2552/ac15e6 · Cited by 9

Epilepsy Seizure Prediction from EEG Signal Using Machine Learning Techniques

Sidaoui, B., & Sadouni, K. (2023) · Advances in Electrical and Computer Engineering · doi:10.4316/aece.2023.02006 · Cited by 8

Machine Learning Based Epileptic Seizure Detection for Responsive Neurostimulator System Optimization

Shen, Y. (2020) · Journal of Physics Conference Series · doi:10.1088/1742-6596/1453/1/012089 · Cited by 8

Epilepsy and the smell of fear

Maa, E. H., Arnold, J., & Bush, C. (2021) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2021.108078 · Cited by 8

SeizNet: An AI-Enabled Implantable Sensor Network System for Seizure Prediction

Saeizadeh, A., Schonholtz, D., Uvaydov, D., Guida, R., Demirors, E., Johari, P., Jimenez, J. M., Neimat, J. S., & Melodia, T. (2024) · Annual Conference on Wireless On-demand Network Systems and Services (WONS) · doi:10.23919/wons60642.2024.10449556 · Cited by 7

Near-Real-Time Epileptic Seizure Detection with Reduced EEG Electrodes: A BiLSTM-Wavelet Approach on the EPILEPSIAE Dataset

Afsari, K., Barachi, M. E., & Ritz, C. H. (2026) · Brain Sciences · doi:10.3390/brainsci16010119 · Cited by 7

Novel targets and stimulation paradigms for deep brain stimulation

Jesus, S. D., Almeida, L., Peng-Chen, Z., Okun, M. S., & Hess, C. W. (2015) · Expert Review of Neurotherapeutics · doi:10.1586/14737175.2015.1083421 · Cited by 7

A Scoring Framework and Apparatus for Epilepsy Seizure Detection Using a Wearable Belt

Al-Zghoul, S., & Alajlouni, S. (2022) · Journal of Medical Signals & Sensors · doi:10.4103/jmss.jmss_138_21 · Cited by 7

Online analysis of local field potentials for seizure detection in freely moving rats.

Zare, M., Nazari, M., Shojaei, A., Raoufy, M. R., & Mirnajafi‐Zadeh, J. (2020) · PubMed Central · doi:10.22038/ijbms.2019.38722.9183 · Cited by 7

An easy-to-use artificial intelligence preoperative lymph node metastasis predictor (LN-MASTER) in rectal cancer based on a privacy-preserving computing platform: multicenter retrospective cohort study

Guan, X., Yu, G., Zhang, W., Wen, R., Wei, R., Jiao, S., Zhao, Q., Lou, Z., Hao, L., Liu, E., et al. (2023) · International Journal of Surgery · doi:10.1097/js9.0000000000000067 · Cited by 7

MMA: metadata supported multi-variate attention for onset detection and prediction

Ravindranath, M., Candan, K. S., Sapino, M. L., & Appavu, B. L. (2024) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-024-01008-z · Cited by 7

HACMAC: A reliable human activity-based medium access control for implantable body sensor networks

Ramachandran, V. R. K., Havinga, P., & Meratnia, N. (2016) · Wearable and Implantable Body Sensor Networks · doi:10.1109/bsn.2016.7516292 · Cited by 7

SmartCED: An Android application for neonatal seizures detection

Cattani, L., Saini, H. P., Ferrari, G., Pisani, F., & Raheli, R. (2016) · IEEE International Symposium on Medical Measurements and Applications (MeMeA) · doi:10.1109/memea.2016.7533708 · Cited by 7

Cepstrum Coefficient Analysis from Low-Frequency to High-Frequency Applied to Automatic Epileptic Seizure Detection with Bio-Electrical Signals

Ren, H., Qu, J., Chai, Y., Huang, L., & Tang, Q. (2018) · Applied Sciences · doi:10.3390/app8091528 · Cited by 7

Characteristics of Future Models of Integrated Outpatient Care

Leviton, A., Oppenheimer, J. E., Chiujdea, M., Antonetty, A., Ojo, O. W., Garcia, S. M., Weas, S., Fleegler, E. W., Chan, E., & Loddenkemper, T. (2019) · Healthcare · doi:10.3390/healthcare7020065 · Cited by 9

Epileptic Seizure Classification based on Supervised Learning Models

Aileni, R. M., Pasca, S., & Florescu, A. (2019) · International Symposium on Advanced Topics in Electrical Engineering · doi:10.1109/atee.2019.8725004 · Cited by 7

Detection and Classification Methods for EEG Epileptic Seizures

Panda, S. (2019) · International Journal of Advanced Trends in Computer Science and Engineering · doi:10.30534/ijatcse/2019/40862019 · Cited by 6

Fuzzy rule learning with ACO in epilepsy crisis identification

Vergara, P. M., Villar, J. R., de la Cal, E., Menéndez‐González, M., & Sedano, J. (2015) · International Conference on Innovations in Information Technology · doi:10.1109/innovations.2015.7381552 · Cited by 6

Caring electronically for young outpatients who have epilepsy

Oppenheimer, J. E., Leviton, A., Chiujdea, M., Antonetty, A., Ojo, O. W., Garcia, S. M., Weas, S., Fleegler, E. W., Chan, E., & Loddenkemper, T. (2018) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2018.06.018 · Cited by 5

Novel ML-Based Algorithm for Detecting Seizures from Single-Channel EEG

Dweiri, Y. M., & Omari, T. K. A. (2024) · NeuroSci · doi:10.3390/neurosci5010004 · Cited by 6

Neurostimulation using mechanical motion of magnetic particles wiggled by external oscillating magnetic gradients

Nacev, A. N., Weinberg, I. N., Mair, L. O., Hilaman, R., Algarín, J. M., Jafari, S., Ijanaten, S., da Silva, C., Baker-McKee, J., Chowdhury, S., et al. (2017) · International IEEE/EMBS Conference on Neural Engineering · doi:10.1109/ner.2017.8008380 · Cited by 6

Automatic detection of PTZ-induced seizures based on functional brain connectivity network in rats

Akbarian, B., & Erfanian, A. (2017) · International IEEE/EMBS Conference on Neural Engineering · doi:10.1109/ner.2017.8008417 · Cited by 6

Analysis of epileptic seizure predictions based on intracranial EEG records

Carrera, E. V., & Quinga, F. (2018) · IEEE Colombian Conference on Communications and Computing (COLCOM) · doi:10.1109/colcomcon.2018.8466719 · Cited by 6

Onset Detection of Epileptic Seizures From Accelerometry Signal

Kusmakar, S., Karmakar, C. K., Yan, B., O'Brien, T. J., Muthuganapathy, R., & Palaniswami, M. S. (2018) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2018.8513669 · Cited by 6

Suppression of acute and chronic mesial temporal epilepsy by contralateral sensing and closed-loop optogenetic stimulation with proportional-plus-off control

Lin, B.-H., Ju, M., & Lin, C. K. (2019) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2019.03.006 · Cited by 6

Mobiles Anfallsmonitoring bei Epilepsiepatienten

Schulze‐Bonhage, A., Böttcher, S., Glasstetter, M., Epitashvili, N., Bruno, E., Richardson, M. P., Laerhoven, K. V., & Dümpelmann, M. (2019) · Der Nervenarzt · doi:10.1007/s00115-019-00822-x · Cited by 6

Use of electrographic seizures and interictal epileptiform discharges for improving performance in seizure prediction

Sudalaimani, C., Asha, S. A., Parvathy, K., Thomas, T. E., Devanand, P., Sasi, P. M., Menon, R. N., Ashalatha, R., & Thomas, S. V. (2015) · IEEE Recent Advances in Intelligent Computational Systems · doi:10.1109/raics.2015.7488419 · Cited by 6

Development of LabVIEW platform for EEG signal analysis

Wadekar, R. S., Kasambe, P. V., & Rathod, S. S. (2017) · doi:10.1109/i2c2.2017.8321942 · Cited by 6

Automatic detection of naturally occurring epilepsy in dogs using intracranial electroencephalogram signals

Fasil, O. K., & Rajesh, R. (2020) · Procedia Computer Science · doi:10.1016/j.procs.2020.04.010 · Cited by 6

BrainForest: Neuromorphic Multiplier-Less Bit-Serial Weight-Memory-Optimized 1024-Tree Brain-State Classification Processor

O’Leary, G., Koerner, J., Kanchwala, M., Filho, J. S., Xu, J., Valiante, T. A., & Genov, R. (2024) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2024.3481160 · Cited by 5

A Two-Stage Prediction + Detection Framework for Real-Time Epileptic Seizure Monitoring

Qiu, S., Wang, W., Zhou, C., Song, X., Yang, J., & Jiao, H. (2025) · IEEE Transactions on Instrumentation and Measurement · doi:10.1109/tim.2025.3558236 · Cited by 5

Multivariate Matching Pursuit Decomposition and Normalized Gabor Entropy for Quantification of Preictal Trends in Epilepsy

Liu, R., Karumuri, B. K., Adkinson, J. A., Hutson, T. N., VLACHOS, I. K., & Iasemidis, L. D. (2018) · Entropy · doi:10.3390/e20060419 · Cited by 5

Classification of epileptic EEG data by using ensemble empirical mode decomposition

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