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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| Format: | Article |
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MDPI AG
2017-02-01
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| Series: | Sensors |
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| Online Access: | http://www.mdpi.com/1424-8220/17/3/481 |
| _version_ | 1798039513979682816 |
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| author | Hyo Sung Joo Su-Hyun Han Jongshill Lee Dong Pyo Jang Joong Koo Kang Jihwan Woo |
| author_facet | Hyo Sung Joo Su-Hyun Han Jongshill Lee Dong Pyo Jang Joong Koo Kang Jihwan Woo |
| author_sort | Hyo Sung Joo |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-11T21:54:56Z |
| format | Article |
| id | doaj.art-86e758da54264561bb6d41584d89080b |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T21:54:56Z |
| publishDate | 2017-02-01 |
| publisher | MDPI AG |
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| series | Sensors |
| spelling | doaj.art-86e758da54264561bb6d41584d89080b2022-12-22T04:01:08ZengMDPI AGSensors1424-82202017-02-0117348110.3390/s17030481s17030481Spectral Analysis of Acceleration Data for Detection of Generalized Tonic-Clonic SeizuresHyo Sung Joo0Su-Hyun Han1Jongshill Lee2Dong Pyo Jang3Joong Koo Kang4Jihwan Woo5Department of Biomedical Engineering, University of Ulsan, Ulsan 44610, KoreaDepartment of Neurology, Chung-Ang University College of Medicine, Seoul 06973, KoreaDepartment of Biomedical Engineering, Hanyang University, Seoul 04763, KoreaDepartment of Biomedical Engineering, Hanyang University, Seoul 04763, KoreaLGT Neuro Medical Center, Seoul 06106, KoreaDepartment of Biomedical Engineering, University of Ulsan, Ulsan 44610, KoreaGeneralized 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.http://www.mdpi.com/1424-8220/17/3/481epilepsyseizure detectionaccelerometerspectral analysis |
| spellingShingle | Hyo Sung Joo Su-Hyun Han Jongshill Lee Dong Pyo Jang Joong Koo Kang Jihwan Woo Spectral Analysis of Acceleration Data for Detection of Generalized Tonic-Clonic Seizures Sensors epilepsy seizure detection accelerometer spectral analysis |
| title | Spectral Analysis of Acceleration Data for Detection of Generalized Tonic-Clonic Seizures |
| title_full | Spectral Analysis of Acceleration Data for Detection of Generalized Tonic-Clonic Seizures |
| title_fullStr | Spectral Analysis of Acceleration Data for Detection of Generalized Tonic-Clonic Seizures |
| title_full_unstemmed | Spectral Analysis of Acceleration Data for Detection of Generalized Tonic-Clonic Seizures |
| title_short | Spectral Analysis of Acceleration Data for Detection of Generalized Tonic-Clonic Seizures |
| title_sort | spectral analysis of acceleration data for detection of generalized tonic clonic seizures |
| topic | epilepsy seizure detection accelerometer spectral analysis |
| url | http://www.mdpi.com/1424-8220/17/3/481 |
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