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Abstract

Phase-2 studies showed that focal seizures could be detected by algorithms using heart rate variability (HRV) in patients with marked autonomic ictal changes. However, wearable surface electrocardiogram (ECG) devices use electrode-patches that need to be changed often, and may cause skin irritation. We report the first study of automated seizure detection using a subcutaneously implantable cardiac monitor (ICM), (Confirm Rx^TM, Abbott). For this proof-of-concept (Phase-1) study, we recruited six patients admitted to long-term video-EEG monitoring. Fifteen-minute epochs of ECG-signals were saved for each seizure and for control (non-seizure) epochs in the epilepsy monitoring unit (EMU) and in the patients´ home environment (1-8 months). We analyzed the ICM signals offline, using a previously developed HRV algorithm. Thirteen seizures were recorded in the EMU and 41 seizures were recorded in the home-monitoring period. The algorithm accurately identified 50 of 54 focal seizures (sensitivity: 92.6 %; 95% confidence interval: 85.6-99.6%). Twelve of the 13 seizures in the EMU were detected (Sensitivity: 92.3%, 95% CI: 77.2-100%), and 38 of the 41 seizures in the out-of-hospital setting were detected (Sensitivity: 92.7%, 95% CI: 84.7-100%). Four false detections were found in the 141 control (non-seizure) epochs (false alarm rate: 2.7 / 24 hours). Our results suggest that automated seizure detection using long-term, subcutaneous ICM device is feasible and accurate in patients with focal seizures and autonomic ictal changes.