Table 1.

Performance metrics of HMM-Gaussian, feature-based, and Kaggle-winning methods.

Dog	Method	FN	FP (rate/hr)	Latency (s)
1	HMM-Gaussian	0	5 (6.2e-4)	−12.1 ± 6.9
1	Feature	0	116 (1.4e-2)	−18.5 ± 4.9
1	Feature*	0	71 (8.8e-3)	−15.7 ± 3.8
1	Kaggle	0	3 (3.7e-4)	−10.1 ± 5.5
2	HMM-Gaussian	0	6 (4.6e-3)	−10.7 ± 8.1
2	Feature	2 (0.057)	430 (0.33)	−19.0 ± 12.7
2	Feature*	2 (0.057)	232 (0.18)	−15.6 ± 5.1
2	Kaggle	0	7 (5.4e-3)	−8.6 ± 4.2

Feature* indicates that the method was trained specifically to limit false positives during bursts.

FN = false negatives (missed seizures); FP = false positives. Latency is measured relative to UEO.