Out-of-hospital multimodal seizure detection: a pilot study

Jonas Munch Nielsen*, Ástrós Eir Kristinsdóttir, Ivan Chrilles Zibrandtsen, Paolo Masulli, Martin Ballegaard, Tobias Søren Andersen, Troels Wesenberg Kjær

*Corresponding author af dette arbejde

Publikation: Bidrag til tidsskriftArtikelForskningpeer review


BACKGROUND: Out-of-hospital seizure detection aims to provide clinicians and patients with objective seizure documentation in efforts to improve the clinical management of epilepsy. In-patient studies have found that combining different modalities helps improve the seizure detection accuracy. In this study, the objective was to evaluate the viability of out-of-hospital seizure detection using wearable ECG, accelerometry and behind-the-ear electroencephalography (EEG). Furthermore, we examined the signal quality of out-of-hospital EEG recordings.

METHODS: Seventeen patients were monitored for up to 5 days. A support vector machine based seizure detection algorithm was applied using both in-patient seizures and out-of-hospital electrographic seizures in one patient. To assess the content of noise in the EEG signal, we compared the root-mean-square (RMS) of the recordings to a reference threshold derived from manually categorised segments of EEG recordings.

RESULTS: In total 1427 hours of continuous EEG was recorded. In one patient, we identified 15 electrographic focal impaired awareness seizures with a motor component. After training our algorithm on in-patient data, we found a sensitivity of 91% and a false alarm rate (FAR) of 18/24 hours for the detection of out-of-hospital seizures using a combination of EEG and ECG recordings. We estimated that 30.1% of the recorded EEG signal was physiological EEG, with an RMS value within the reference threshold.

CONCLUSION: We found that detection of out-of-hospital focal impaired awareness seizures with a motor component is possible and that applying multiple modalities improves the diagnostic accuracy compared with unimodal EEG. However, significant challenges remain regarding a high FAR and that only 30.1% of the EEG data represented usable signal.

Sider (fra-til)e000442
TidsskriftBMJ Neurology Open
Udgave nummer2
StatusUdgivet - 2023

Bibliografisk note

© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.


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