Spectral Analysis of Acceleration Data for Detection of Generalized Tonic-Clonic Seizures

Generalized tonic-clonic seizures (GTCSs) can be underestimated and can also increase mortality rates. The monitoring devices used to detect GTCS events in daily life are very helpful for early intervention and precise estimation of seizure events. Several studies have introduced methods for GTCS de...

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Bibliographic Details
Main Authors: Hyo Sung Joo, Su-Hyun Han, Jongshill Lee, Dong Pyo Jang, Joong Koo Kang, Jihwan Woo
Format: Article
Language:English
Published: MDPI AG 2017-02-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/17/3/481
Description
Summary:Generalized tonic-clonic seizures (GTCSs) can be underestimated and can also increase mortality rates. The monitoring devices used to detect GTCS events in daily life are very helpful for early intervention and precise estimation of seizure events. Several studies have introduced methods for GTCS detection using an accelerometer (ACM), electromyography, or electroencephalography. However, these studies need to be improved with respect to accuracy and user convenience. This study proposes the use of an ACM banded to the wrist and spectral analysis of ACM data to detect GTCS in daily life. The spectral weight function dependent on GTCS was used to compute a GTCS-correlated score that can effectively discriminate between GTCS and normal movement. Compared to the performance of the previous temporal method, which used a standard deviation method, the spectral analysis method resulted in better sensitivity and fewer false positive alerts. Finally, the spectral analysis method can be implemented in a GTCS monitoring device using an ACM and can provide early alerts to caregivers to prevent risks associated with GTCS.
ISSN:1424-8220