Seizure prediction and forecasting: a scoping review

Current Opinion in Neurology, Год журнала: 2025, Номер 38(2), С. 135 - 139

Опубликована: Янв. 20, 2025

This scoping review summarizes key developments in the field of seizure forecasting. Developments have been made along several modalities forecasting, including long term intracranial and subcutaneous encephalogram, wearable physiologic monitoring, diaries. However, clinical translation these tools is limited by various factors. One lack validation on an external dataset. Moreover, widespread practice comparing models to a chance forecaster may be inadequate. Instead, model should able at least surpass moving average forecaster, which serves as 'napkin test' (i.e., can computed back napkin). The impact frequency performance also accounted for when across studies. Surprisingly, despite potential poor quality forecasts, some individuals with epilepsy still want access imprecise forecasts even alter their behavior based upon them. Promising advances development but current not yet overcome hurdles. Future studies will need address potentially dangerous patient behaviors well account validation, napkin test, dependent metrics.

Язык: Английский

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Evaluating the accuracy of monitoring seizure cycles with seizure diaries

Epilepsia, Год журнала: 2025, Номер unknown

Опубликована: Фев. 24, 2025

Abstract Objective Epileptic seizures occurring in cyclical patterns is increasingly recognized as a significant opportunity to advance epilepsy management. Current methods for detecting seizure cycles rely on intrusive techniques or specialized biomarkers, thereby limiting their accessibility. This study evaluates non‐invasive cycle detection method using diaries and compares its accuracy with identified from intracranial electroencephalography (iEEG) interictal epileptiform discharges (IEDs). Methods Using data previously published first in‐human iEEG device trial ( n = 10), we analyzed through diary reports, seizures, IEDs. Cycle similarities across IEDs were evaluated at periods of 1 45 days spectral coherence, accuracy, precision, recall, the false‐positive rate. Results A coherence analysis raw signals showed moderately similar periodic components between seizures/day (median .43, IQR .68). In contrast, there was low IEDs/day .11, .18) .12, .19). Accuracy, recall scores, rates significantly higher than chance all participants (accuracy (mean ± standard deviation): .95 .02; precision: .56 .19; recall: rate: .02 .01). However, scores IED both did not perform above chance, average. Recall compared good reporters, under‐reporters, over‐reporters, generally performing better reporters under‐reporters over‐reporters. Significance These findings suggest that can be even individuals who under‐ over‐report seizures. approach offers an accessible alternative monitoring more invasive methods.

Язык: Английский

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Forecasting epileptic seizures with wearable devices: A hybrid short‐ and long‐horizon pseudo‐prospective approach

Epilepsia, Год журнала: 2025, Номер unknown

Опубликована: Май 24, 2025

Abstract Objective Seizure unpredictability can be debilitating and dangerous for people with epilepsy. Accurate seizure forecasters could improve quality of life those epilepsy but must practical long‐term use. This study presents the first validation a seizure‐forecasting system using ultra‐long‐term, non‐invasive wearable data. Methods Eleven participants were recruited continuous monitoring, capturing heart rate step count via wrist‐worn devices seizures electroencephalography (average recording duration 337 days). Two hybrid models—combining machine learning cycle‐based methods—were proposed to forecast at both short (minutes) long (up 44 days) horizons. Results The Warning System (SWS), designed forecasting near‐term seizures, Risk (SRS), risk, outperformed traditional models. In addition, SRS reduced high‐risk time by 29% while increasing sensitivity 11%. Significance These improvements mark significant advancement in making more effective.

Язык: Английский

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Seizure forecasting: Bifurcations in the long and winding road

Epilepsia, Год журнала: 2022, Номер 64(S4)

Опубликована: Май 23, 2022

To date, the unpredictability of seizures remains a source suffering for people with epilepsy, motivating decades research into methods to forecast seizures. Originally, only few scientists and neurologists ventured this niche endeavor, which, given difficulty task, soon turned long winding road. Over past decade, however, our narrow field has seen major acceleration, trials chronic electroencephalographic devices subsequent discovery cyclical patterns in occurrence Now, burgeoning science seizure timing is emerging, which turn informs best forecasting strategies upcoming clinical trials. Although finish line might be view, many challenges remain make reality. This review covers most recent scientific, technical, medical developments, discusses methodology detail, sets number goals future studies.

Язык: Английский

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Seizure forecasting: Where do we stand?

Epilepsia, Год журнала: 2023, Номер 64(S3)

Опубликована: Фев. 13, 2023

A lot of mileage has been made recently on the long and winding road toward seizure forecasting. Here we briefly review some selected milestones passed along way, which were discussed at International Conference for Technology Analysis Seizures-ICTALS 2022-convened University Bern, Switzerland. Major impetus was gained from wearable implantable devices that record not only electroencephalography, but also data motor behavior, acoustic signals, various signals autonomic nervous system. This multimodal monitoring can be performed ultralong timescales covering months or years. Accordingly, features metrics extracted these now assess dynamics with a greater degree completeness. Most prominently, this allowed confirmation long-suspected cyclical nature interictal epileptiform activity, risk, seizures. The cover daily, multi-day, yearly cycles. Progress fueled by approaches originating interdisciplinary field network science. Considering epilepsy as large-scale disorder yielded novel perspectives pre-ictal evolving epileptic brain. In addition to discrete predictions will take place in specified prediction horizon, community broadened scope probabilistic forecasts risk continuously time. shift gears triggered incorporation additional quantify performance forecasting algorithms, should compared chance constrained stochastic null models. An imminent task utmost importance is find optimal ways communicate output seizure-forecasting algorithms patients, caretakers, clinicians, so they have socioeconomic impact improve patients' well-being.

Язык: Английский

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Feasibility, Safety, and Performance of Full-Head Subscalp EEG Using Minimally Invasive Electrode Implantation

Neurology, Год журнала: 2024, Номер 102(12)

Опубликована: Июнь 6, 2024

Current practice in clinical neurophysiology is limited to short recordings with conventional EEG (days) that fail capture a range of brain (dys)functions at longer timescales (months). The future ability optimally manage chronic disorders, such as epilepsy, hinges upon finding methods monitor electrical activity daily life. We developed device for full-head subscalp (Epios) and tested here the feasibility safely insert electrode leads beneath scalp by minimally invasive technique (primary outcome). As secondary outcome, we verified noninferiority measuring physiologic oscillations pathologic discharges compared EEG, established standard care.

Язык: Английский

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Critical biomarkers for responsive deep brain stimulation and responsive focal cortex stimulation in epilepsy field

Fundamental Research, Год журнала: 2024, Номер 5(1), С. 103 - 114

Опубликована: Июнь 24, 2024

To derive critical signal features from intracranial electroencephalograms of epileptic patients in order to design instructions for feedback-type electrical stimulation systems. The Detrended Fluctuation Analysis (DFA) exponent is chosen as the classification exponent, and disparities between indicators representing distinct seizure states efficacy rudimentary machine learning models are computed. DFA exhibited a statistically significant variation among pre-ictal, ictal period, post-ictal stages. Linear Discriminant model demonstrates highest accuracy three basic models, whereas Naive Bayesian necessitates least amount computational storage space. set exponents employed an intermediary variable process. resultant possesses capability function feedback trigger program systems variety, specifically within domain neural modulation epilepsy.

Язык: Английский

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Necessary for seizure forecasting outcome metrics: seizure frequency and benchmark model

Epilepsy Research, Год журнала: 2024, Номер 208, С. 107474 - 107474

Опубликована: Ноя. 8, 2024

Язык: Английский

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Necessary for seizure forecasting outcome metrics: seizure frequency and benchmark model

medRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Май 16, 2024

Work is ongoing to advance seizure forecasting, but the performance metrics used evaluate model effectiveness can sometimes lead misleading outcomes. For example, some improve when tested on patients with a particular range of frequencies (SF). This study illustrates connection between SF and metrics. Additionally, we compared benchmarks for testing performance: moving average (MA) or commonly permutation benchmark. Three data sets were evaluations: (1) Self-reported diaries 3,994 Seizure Tracker patients; (2) Automatically detected (and manually reported edited) generalized tonic-clonic seizures from 2,350 Empatica Embrace 2 Mate App diary users, (3) Simulated datasets varying SFs. Metrics calibration discrimination computed each dataset, comparing MA across values. Most found depend SF. The outperformed matched in all cases. findings highlight SF's role forecasting accuracy model's suitability as underscores need considering patient studies suggests may provide better standard evaluating future models.

Язык: Английский

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Automated algorithms for seizure forecast: a systematic review and meta-analysis

Journal of Neurology, Год журнала: 2024, Номер unknown

Опубликована: Сен. 6, 2024

Язык: Английский

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