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

Autor:	Line S. Remvig, Jonas Duun-Henriksen, Franz Fürbass, Manfred Hartmann, Pedro F. Viana, Anne Mette Kappel Overby, Sigge Weisdorf, Mark P. Richardson, Sándor Beniczky, Troels W. Kjaer
Rok vydání:	2022
Předmět:	Epilepsy Long-term monitoring Electroencephalography Seizure detection Temporal Lobe Sensory Systems Epilepsy Temporal Lobe Neurology Seizures Physiology (medical) Humans Subcutaneous EEG Neurology (clinical) Outpatient monitoring Algorithms
Zdroj:	Remvig, L S, Duun-Henriksen, J, Fürbass, F, Hartmann, M, Viana, P F, Kappel Overby, A M, Weisdorf, S, Richardson, M P, Beniczky, S & Kjaer, T W 2022, ' Detecting temporal lobe seizures in ultra long-term subcutaneous EEG using algorithm-based data reduction ', Clinical Neurophysiology, vol. 142, pp. 86-93 . https://doi.org/10.1016/j.clinph.2022.07.504
ISSN:	1388-2457
Popis:	Objective: Ultra long-term monitoring with subcutaneous EEG (sqEEG) offers objective outpatient recording of electrographic seizures as an alternative to self-reported epileptic seizure diaries. This methodology requires an algorithm-based automatic seizure detection to indicate periods of potential seizure activity to reduce the time spent on visual review. The objective of this study was to evaluate the performance of a sqEEG-based automatic seizure detection algorithm. Methods: A multicenter cohort of subjects using sqEEG were analyzed, including nine people with epilepsy (PWE) and 12 healthy subjects, recording a total of 965 days. The automatic seizure detections of a deep-neural-network algorithm were compared to annotations from three human experts. Results: Data reduction ratios were 99.6% in PWE and 99.9% in the control group. The cross-PWE sensitivity was 86% (median 80%, range 69–100% when PWE were evaluated individually), and the corresponding median false detection rate was 2.4 detections per 24 hours (range: 2.0–13.0). Conclusions: Our findings demonstrated that step one in a sqEEG-based semi-automatic seizure detection/review process can be performed with high sensitivity and clinically applicable specificity. Significance: Ultra long-term sqEEG bears the potential of improving objective seizure quantification.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e8637cd4e32921b7f8cd42245575d7c3 https://doi.org/10.1016/j.clinph.2022.07.504 Zobrazit plný text záznamu Full Text from ScienceDirect