Abstract
| Original language | English |
|---|---|
| Journal | I E E E Transactions on Biomedical Engineering |
| Volume | 59 |
| Issue number | 2 |
| Pages (from-to) | 579-585 |
| ISSN | 0018-9294 |
| DOIs | |
| Publication status | Published - 2012 |
Keywords
- Tonic–clonic
- Epilepsy
- Surface electromyography (sEMG)
- Seizure detection
Cite this
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Automated Algorithm for Generalized Tonic–Clonic Epileptic Seizure Onset Detection Based on sEMG Zero-Crossing Rate. / Conradsen, Isa; Beniczky, Sándor; Hoppe, Karsten; Wolf, Peter; Sørensen, Helge Bjarup Dissing.
In: I E E E Transactions on Biomedical Engineering, Vol. 59, No. 2, 2012, p. 579-585.Research output: Contribution to journal › Journal article › Research › peer-review
TY - JOUR
T1 - Automated Algorithm for Generalized Tonic–Clonic Epileptic Seizure Onset Detection Based on sEMG Zero-Crossing Rate
AU - Conradsen, Isa
AU - Beniczky, Sándor
AU - Hoppe, Karsten
AU - Wolf, Peter
AU - Sørensen, Helge Bjarup Dissing
PY - 2012
Y1 - 2012
N2 - Patients are not able to call for help during a generalized tonic–clonic epileptic seizure. Our objective was to develop a robust generic algorithm for automatic detection of tonic–clonic seizures, based on surface electromyography (sEMG) signals suitable for a portable device. Twenty-two seizures were analyzed from 11 consecutive patients. Our method is based on a high-pass filtering with a cutoff at 150 Hz, and monitoring a count of zero crossings with a hysteresis of $\pm 50\,\mu \hbox{V}$ . Based on data from one sEMG electrode (on the deltoid muscle), we achieved a sensitivity of 100% with a mean detection latency of 13.7 s, while the rate of false detection was limited to 1 false alarm per 24 h. The overall performance of the presented generic algorithm is adequate for clinical implementation.
AB - Patients are not able to call for help during a generalized tonic–clonic epileptic seizure. Our objective was to develop a robust generic algorithm for automatic detection of tonic–clonic seizures, based on surface electromyography (sEMG) signals suitable for a portable device. Twenty-two seizures were analyzed from 11 consecutive patients. Our method is based on a high-pass filtering with a cutoff at 150 Hz, and monitoring a count of zero crossings with a hysteresis of $\pm 50\,\mu \hbox{V}$ . Based on data from one sEMG electrode (on the deltoid muscle), we achieved a sensitivity of 100% with a mean detection latency of 13.7 s, while the rate of false detection was limited to 1 false alarm per 24 h. The overall performance of the presented generic algorithm is adequate for clinical implementation.
KW - Tonic–clonic
KW - Epilepsy
KW - Surface electromyography (sEMG)
KW - Seizure detection
U2 - 10.1109/TBME.2011.2178094
DO - 10.1109/TBME.2011.2178094
M3 - Journal article
C2 - 22156944
VL - 59
SP - 579
EP - 585
JO - I E E E Transactions on Biomedical Engineering
JF - I E E E Transactions on Biomedical Engineering
SN - 0018-9294
IS - 2
ER -