Automated seizure detection accuracy for ambulatory EEG recordings.

OBJECTIVE

To investigate the accuracy of preselected software automatic seizure files to detect at least one seizure per study in prolonged ambulatory EEG recording.

METHODS

All the prolonged ambulatory EEG recordings (>24 hours) read at the Northwestern Memorial Hospital from January 2013 to October 2017 were included. We selected only the first study of each patient. We reviewed the studies entirely, and processed the recordings through 1 of 3 different detection software that are commercially available (Persyst 11, Persyst 12, and Gotman TM Event Detection). The proportion of patients with at least one electrographic seizure (≥10 seconds) correctly identified by a seizure detector was calculated. Finally, we evaluated whether the type of seizure (focal vs generalized) may affect the chances of being automatically detected.

RESULTS

We read 1,478 ambulatory EEG studies entirely (2,323 days of EEG recording; average 1.6 d/study). From the first study of each patient (1,257 studies), we found electrographic seizures in 70 (5.6%) studies. In 37 of 70 patients (53%), the automatic detectors correctly identified at least one seizure. Detections happened slightly more frequently in generalized seizures (14/20, 70%) compared to focal seizures (23/50, 46%) ( = 0.06).

CONCLUSION

Seizures were found in 5.6% of the studies. Automatic seizure detectors identified at least one electrographic seizure in only 53% of the studies. They performed slightly better detecting generalized than focal seizures. Therefore, the review of only automatically selected segments may be of decreased value to identify seizures, in particular when focal seizures are suspected.