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Multicenter Study
. 2018 Jan 30;90(5):e428-e434.
doi: 10.1212/WNL.0000000000004893. Epub 2018 Jan 5.

Automated real-time detection of tonic-clonic seizures using a wearable EMG device

Sándor Beniczky  1 , Isa Conradsen  2 , Oliver Henning  2 , Martin Fabricius  2 , Peter Wolf  2
Affiliations
Multicenter Study

Automated real-time detection of tonic-clonic seizures using a wearable EMG device

Sándor Beniczky et al. Neurology. .

Abstract

Objective: To determine the accuracy of automated detection of generalized tonic-clonic seizures (GTCS) using a wearable surface EMG device.

Methods: We prospectively tested the technical performance and diagnostic accuracy of real-time seizure detection using a wearable surface EMG device. The seizure detection algorithm and the cutoff values were prespecified. A total of 71 patients, referred to long-term video-EEG monitoring, on suspicion of GTCS, were recruited in 3 centers. Seizure detection was real-time and fully automated. The reference standard was the evaluation of video-EEG recordings by trained experts, who were blinded to data from the device. Reading the seizure logs from the device was done blinded to all other data.

Results: The mean recording time per patient was 53.18 hours. Total recording time was 3735.5 hours, and device deficiency time was 193 hours (4.9% of the total time the device was turned on). No adverse events occurred. The sensitivity of the wearable device was 93.8% (30 out of 32 GTCS were detected). Median seizure detection latency was 9 seconds (range -4 to 48 seconds). False alarm rate was 0.67/d.

Conclusions: The performance of the wearable EMG device fulfilled the requirements of patients: it detected GTCS with a sensitivity exceeding 90% and detection latency within 30 seconds.

Classification of evidence: This study provides Class II evidence that for people with a history of GTCS, a wearable EMG device accurately detects GTCS (sensitivity 93.8%, false alarm rate 0.67/d).

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Figures

Figure 1
Figure 1. Wearable seizure detection device (Epileptic seizure Detector Developed by IctalCare)
(A) The wearable device placed on the brachial biceps muscles. (B, C) The wearable device, which is connected to the self-adhesive patch, containing the recording electrodes and the ground electrode. (D) Remote control of the device.
Figure 2
Figure 2. EMG-based seizure detection algorithm
(A) The EMG signals recorded by Epileptic seizure Detector Developed by IctalCare (EDDI) during a generalized tonic-clonic seizure (high-pass filter: 150 Hz). (B) The number of zero-crossings calculated from the signal in (A). The horizontal axis in both (A) and (B) is the time (in seconds). When the number of zero-crossings exceeds the threshold (dotted horizontal line) for the prespecified time window (yellow line), then the seizure alarm is triggered (red vertical arrow).
Figure 3
Figure 3. Standards for Reporting of Diagnostic Accuracy flowchart of the study
DBS = deep brain stimulation; EDDI = Epileptic seizure Detector Developed by IctalCare; GTCS = generalized tonic-clonic seizure.
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