Seizure detection using heart rate variability: A prospective validation study

Jesper Jeppesen, Anders Fuglsang-Frederiksen, Peter Johansen, Jakob Christensen, Stephan Wüstenhagen, Hatice Tankisi, Erisela Qerama, Sándor Beniczky

Publikation: Bidrag til tidsskriftArtikelForskningpeer review


Although several validated seizure detection algorithms are available for convulsive seizures, detection of nonconvulsive seizures remains challenging. In this phase 2 study, we have validated a predefined seizure detection algorithm based on heart rate variability (HRV) using patient-specific cutoff values. The validation data set was independent from the previously published data set. Electrocardiography (ECG) was recorded using a wearable device (ePatch) in prospectively recruited patients. The diagnostic gold standard was inferred from video-EEG monitoring. Because HRV-based seizure detection is suitable only for patients with marked ictal autonomic changes, we defined responders as the patients who had a>50 beats/min ictal change in heart rate. Eleven of the 19 included patients with seizures (57.9%) fulfilled this criterion. In this group, the algorithm detected 20 of the 23 seizures (sensitivity: 87.0%). The algorithm detected all but one of the 10 recorded convulsive seizures and all of the 8 focal impaired awareness seizures, and it missed 2 of the 4 focal aware seizures. The median sensitivity per patient was 100% (in nine patients all seizures were detected). The false alarm rate was 0.9/24 h (0.22/night). Our results suggest that HRV-based seizure detection has high performance in patients with marked autonomic changes.

Sider (fra-til)S41-S46
Vol/bind61 Suppl 1
Tidlig onlinedato7 maj 2020
StatusUdgivet - nov. 2020

Bibliografisk note

© 2020 International League Against Epilepsy.


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