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Prospective evaluation of generalized tonic-clonic seizure multimodal detection:
comparison between pediatric and adult cohorts in EMU
F. Onoratia, G. Regaliaa, W. Curt LaFrance Jrb, A. S. Blumc, J. Bidwelld, P. De Lisoe, R. El Atrachef, T. Loddenkemperf, F. Mohammadpour-Touserkanif, R. Sarkisg, D. Friedmanh, J. Jeschkeh, R. Picarda,i
“fixed and frozen” AI-based GTCS detection algorithm
(lower bound of CI for PPA>70% and
FAR<2) for both pediatric and adult populations.
FAR for pediatric
is significantly (p-value<0.01)
,most likely because children were
in the EMU.
, the overall
FAR drops dramatically
, which is as low as
(considering 8 hours of sleep per
1FA every 100 nights of sleep
will examine the
prospective detection performance
and overall impact in
Onorati, F., Regalia, G., et al. (2017). Multicenter clinical assessment of improved wearable multimodal convulsive seizure detectors. Epilepsia,
Regalia et al. (2019). Multimodal wrist-worn devices for seizure detection and advancing research : Focus on the Empatica wristbands.
Epilepsy Res. 153:79 82.doi:10.1016/j.eplepsyres.2019.02.007.
510(k) Premarket Notification (K181861), https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfPMN/pmn.cfm?ID=K181861,12/20/2018.
Regalia, G., et al. (2019). Sleep assessment by means of awrist actigraphy-based algorithm: agreement with polysomnography in an
ambulatory study on older adults,
show the performance as measured in the
presented for the
a. Empatica Inc, Boston, MA, USA
b. Division of Neuropsychiatry and Behavioral Neurology, Rhode Island Hospital, Brown University, Providence, Rhode Island, USA
c. Department of Neurology, Rhode Island Hospital, Brown University, Providence, Rhode Island, USA
d. Harvard Medical School, Boston, MA, USA
e. Neurology Unit, Department of Neuroscience and Neurorehabilitation, Bambino Gesù Children’s Hospital, IRCCS, Rome, Italy
f. Department of Neurology, Boston Children’s Hospital, Boston, MA, USA
g. Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
h. Department of Neurology, New York University Langone Medical Center, New York, New York, USA
i. MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA, USA
wristband (Empatica Inc., Boston, MA) runs an
AI-based GTCSs detection algorithm
that can trigger an alert to designated
caregivers for prompt intervention (Figure 1).
•The combination of wrist
(EDA) has been shown effective in the
generalized tonic-clonic seizures
(GTCSs), with sensitivity > 94 % and 1 false alarm every 5days on retrospective studies
Figure 1 Embrace wristband detects an event and transmits an alert to a smartphone, which generates notifications via a cloud-based service to designated caregivers.
•To assess the
effectiveness and safety
of the seizure detection device,
where a predefined
detection algorithm (i.e.,
“fixed and frozen”
)is applied to an
EMU test cohort 
PPA (cPPA) [95% CI]
#FA (@ Rest)
#Days (@ Rest)
FAR (@ Rest)
54 (53) 98.1% (94.8%) [90.3% -97%] 38.19 383 (6)
96.9% (91.5%) [83.4%
36.9 218 (4) 161 (82.1) 1.35 (0.049)
22 (22) 100% (92.4%) [91% -93.1%] 40 165 (2)
Figure 2 Histograms of FA, days of recordings and FAR across all the patients in the study.
Table 1 Prospective performance analysis of the on the test cohort
We present the results of a prospective inpatient analysis of Embrace wristband. FDA designated
endpoints are met for ages 6 and up. The average number of false alarms is close to zero per night.
: the lower bound of the
95%confidence interval (CI) of positive percentage agreement (PPA)
is higher than
false alarm rate per 24h
(FAR) is lower than
Materials & Methods
Secondary endpoint -FAR
was found to be
•The percentage of
patients with 0FAs
pediatrics and 0.17 for adults).
(18 from pediatrics) were
of type GTCS
Omitting these, overall corrected
(0.049 for pediatrics and 0.017 for adults).
Primary endpoint -PPA
53 out of 54 GTCSs
(PPA =98.1%, cPPA =94.8%).
31 out of 32 GTCSs
detected (PPA =96.9%, cPPA =91.5%)
22 out of 22 GTCSs
(PPA =100% and cPPA =92.4%).
patients diagnosed with epilepsy were studied in the
(36 females, 6-21 years)
(33 females, 22-63 years).
(9,806 hours, 5,727 from pediatrics) of data were collected (median:49.23 hours/patient);
Three board-certified neurologists independently
marked seizures from
(i.e., at least 2 out of 3) was used for
the final labels of GTCS or non-GTCS.
(17 pediatrics) experienced a total of
54 primary or secondary GTCSs
(17 pediatrics), while 110 patients experienced no
“fixed and frozen” GTCS detection algorithm
was used to prospectively analyze the data.
•PPA is also reported as corrected PPA (
), due to the presence of
multiple seizures per patient
PPA 95%confidence limits (CI)
were computed with a
non-parametric bootstrapping approach
was evaluated on
all the recordings
and by considering only the periods of
as identified by a
proprietary algorithm