Getting Under the Skin of Seizure Monitoring: A Subcutaneous EEG Tool to Keep a Tally Over the Long Haul

Article Clinical Neurology

Seizure forecasting using minimally invasive, ultra-long-term subcutaneous EEG: Generalizable cross-patient models

Tal Pal Attia et al.

Summary: This study presents a generalized approach for forecasting seizures in epilepsy patients using recurrent neural networks and deep learning classifiers. The results show that the cross-patient classifiers achieved better than chance performance in four out of six patients, indicating the potential of this method for seizure prediction.

EPILEPSIA (2022)

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Article Clinical Neurology

Detecting temporal lobe seizures in ultra long-term subcutaneous EEG using algorithm-based data reduction

Line S. Remvig et al.

Summary: The objective of this study was to evaluate the performance of a subcutaneous EEG-based automatic seizure detection algorithm. The results showed that this algorithm has high sensitivity and clinically applicable specificity. Ultra long-term subcutaneous EEG has the potential to improve objective seizure quantification.

CLINICAL NEUROPHYSIOLOGY (2022)

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Article Clinical Neurology

Signal quality and power spectrum analysis of remote ultra long-term subcutaneous EEG

Pedro F. Viana et al.

Summary: Ultra long-term subcutaneous electroencephalography (sqEEG) monitoring is a new modality with great potential for both health and disease, including epileptic seizure detection and forecasting. The spectral characteristics of minimally invasive, ultra long-term sqEEG are similar to scalp EEG, whereas the signal is highly stationary. Our findings reinforce the suitability of this system for chronic implantation on diverse clinical applications, from seizure detection and forecasting to brain-computer interfaces.

EPILEPSIA (2021)

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Review Clinical Neurology