Seizure prediction—ready for a new era

L Kuhlmann, K Lehnertz, MP Richardson… - Nature Reviews …, 2018 - nature.com
Epilepsy is a common disorder characterized by recurrent seizures. An overwhelming
majority of people with epilepsy regard the unpredictability of seizures as a major issue …

Machine learning and wearable devices of the future

S Beniczky, P Karoly, E Nurse, P Ryvlin, M Cook - Epilepsia, 2021 - Wiley Online Library
Abstract Machine learning (ML) is increasingly recognized as a useful tool in healthcare
applications, including epilepsy. One of the most important applications of ML in epilepsy is …

[HTML][HTML] A taxonomy of seizure dynamotypes

ML Saggio, D Crisp, JM Scott, P Karoly, L Kuhlmann… - Elife, 2020 - elifesciences.org
Seizures are a disruption of normal brain activity present across a vast range of species and
conditions. We introduce an organizing principle that leads to the first objective Taxonomy of …

Virtual resection predicts surgical outcome for drug-resistant epilepsy

LG Kini, JM Bernabei, F Mikhail, P Hadar, P Shah… - Brain, 2019 - academic.oup.com
Patients with drug-resistant epilepsy often require surgery to become seizure-free. While
laser ablation and implantable stimulation devices have lowered the morbidity of these …

[HTML][HTML] Forecasting seizure likelihood with wearable technology

RE Stirling, DB Grayden, W D'Souza, MJ Cook… - Frontiers in …, 2021 - frontiersin.org
The unpredictability of epileptic seizures exposes people with epilepsy to potential physical
harm, restricts day-to-day activities, and impacts mental well-being. Accurate seizure …

From seizure detection to smart and fully embedded seizure prediction engine: A review

J Yang, M Sawan - IEEE Transactions on Biomedical Circuits …, 2020 - ieeexplore.ieee.org
Recent review papers have investigated seizure prediction, creating the possibility of
preempting epileptic seizures. Correct seizure prediction can significantly improve the …

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

SN Baldassano, BH Brinkmann, H Ung, T Blevins… - Brain, 2017 - academic.oup.com
There exist significant clinical and basic research needs for accurate, automated seizure
detection algorithms. These algorithms have translational potential in responsive …

[HTML][HTML] A comparison of neuroelectrophysiology databases

P Subash, A Gray, M Boswell, SL Cohen, R Garner… - Scientific Data, 2023 - nature.com
As data sharing has become more prevalent, three pillars-archives, standards, and analysis
tools-have emerged as critical components in facilitating effective data sharing and …

Closed-loop neural prostheses with on-chip intelligence: A review and a low-latency machine learning model for brain state detection

B Zhu, U Shin, M Shoaran - IEEE transactions on biomedical …, 2021 - ieeexplore.ieee.org
The application of closed-loop approaches in systems neuroscience and therapeutic
stimulation holds great promise for revolutionizing our understanding of the brain and for …

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

SM Usman, S Khalid, R Akhtar, Z Bortolotto, Z Bashir… - Seizure, 2019 - Elsevier
Patients suffering from epileptic seizures are usually treated with medication and/or surgical
procedures. However, in more than 30% of cases, medication or surgery does not effectively …